Node.js Developer Master Program
An intensive 4-month online weekend live engineering cohort (Sat & Sun • 4 hours/day: 2h live faculty lectures + 2h supervised coding labs) covering Node.js Developer production capstones and 580+ AI interviews, with eligible hiring-drive access under documented placement terms and tuition-refund protection where all policy conditions are met.
- Online Weekend Live Sessions (Sat & Sun • 4 Hours / Day)
- 4 Months (16 Weeks) Comprehensive Finish
- Guaranteed Placement Drives until Placed across 1,050+ top companies
- 26 Production Microservices & Capstones with GitHub code reviews
- 580+ Topic Mock Tests & 1-on-1 AI Voice Technical Interviews
Our Graduates Get Marketed to 1,050+ Global Tech Leaders & Unicorns
Continuous corporate interview referrals until job offer letter issuance:
Online Weekend Master Track: 4 Months of Live Mentorship & Placement Drives
Designed for college students and working professionals, our Online Weekend Master Track delivers intensive 4-hour live sessions every Saturday and Sunday across 16 weeks (4 Months). Complete 128+ hours of live faculty instruction, 26 production capstones, and 580+ AI interviews with unlimited corporate interview drives until you get placed!
Live Architecture & Core Mentorship
2 Hours of interactive enterprise architecture, live faculty coding, and design patterns followed by 2 Hours of supervised capstone development.
Hands-On Labs, Tests & AI Practice
2 Hours of advanced microservices, real-time queues & cloud deployment followed by 2 Hours of timed mock tests and 1-on-1 AI voice interview rounds.
4-Month Master Roadmap to Guaranteed Placement
We transform you into a battle-tested software engineer ready to clear Tier-1 technical and system design interview rounds in 4 months with weekend online sessions.
Architecture & Core Mechanics
Core OOP, memory mechanics, data structures, algorithms & clean design patterns.
Capstones & Microservices
Build production full stack SaaS, microservices, REST APIs, queues & cloud deployment.
System Design & AI Interviews
Simulate live FAANG interview rounds, timed topic mock tests and AI voice evaluations.
Corporate Drives until Placed
Resume marketing, hiring drives across 1,050+ partners, and placement guarantee.
Projected Target CTC After Program
Industry-verified compensation brackets achieved by graduates across 1,050+ hiring partners:
₹8.5L – ₹14L /yr
Software Engineer I, Junior Backend Developer, Full Stack Associate.
- 260+ Hours Live Mentorship
- 26 Capstone Projects on GitHub
- 580+ AI Technical Interview Scorecards
₹14L – ₹24L /yr
Full Stack Java Engineer, Spring Boot Microservices Specialist, Cloud Engineer.
- Kafka Event-Driven Architectures
- Redis Caching & Performance Tuning
- Docker, Kubernetes & AWS CI/CD
₹24L – ₹36L+ /yr
Senior Full Stack Engineer, Microservices Architect, Lead Consultant.
- High-Throughput System Design (LLD/HLD)
- Fault Tolerance & Distributed Transactions
- FAANG System Design Clearing Mentorship
Topic-Wise Curriculum & Practice Hub
151 Modules • 537 Deep-Dive Topics • 537 Integrated Topic Mock Tests & AI Interviews
8 curriculum topics: Variables, Data Types, Operators, Conditions, Loops, Functions, Arrays, Objects.
Variables
let; const
- Explain the core concepts and architecture of Variables.
- Apply Variables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Data Types
Core concepts, implementation patterns, engineering trade-offs and production considerations for Data Types.
- Explain the core concepts and architecture of Data Types.
- Apply Data Types in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Operators
Core concepts, implementation patterns, engineering trade-offs and production considerations for Operators.
- Explain the core concepts and architecture of Operators.
- Apply Operators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Conditions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Conditions.
- Explain the core concepts and architecture of Conditions.
- Apply Conditions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Loops
Core concepts, implementation patterns, engineering trade-offs and production considerations for Loops.
- Explain the core concepts and architecture of Loops.
- Apply Loops in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Functions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Functions.
- Explain the core concepts and architecture of Functions.
- Apply Functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Arrays
Core concepts, implementation patterns, engineering trade-offs and production considerations for Arrays.
- Explain the core concepts and architecture of Arrays.
- Apply Arrays in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Objects
Core concepts, implementation patterns, engineering trade-offs and production considerations for Objects.
- Explain the core concepts and architecture of Objects.
- Apply Objects in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Arrow functions, Destructuring, Spread, Rest, Optional chaining, Nullish coalescing, Template literals, Modules.
Arrow functions
MODERN JAVASCRIPT: Arrow functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Arrow functions.
- Apply Arrow functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Destructuring
MODERN JAVASCRIPT: Destructuring. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Destructuring.
- Apply Destructuring in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Spread
MODERN JAVASCRIPT: Spread. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Spread.
- Apply Spread in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rest
MODERN JAVASCRIPT: Rest. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rest.
- Apply Rest in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Optional chaining
MODERN JAVASCRIPT: Optional chaining. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Optional chaining.
- Apply Optional chaining in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Nullish coalescing
MODERN JAVASCRIPT: Nullish coalescing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Nullish coalescing.
- Apply Nullish coalescing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Template literals
MODERN JAVASCRIPT: Template literals. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Template literals.
- Apply Template literals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules
MODERN JAVASCRIPT: Modules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Modules.
- Apply Modules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: First-class functions, Callbacks, Higher-order functions, Closures, Lexical scope.
First-class functions
FUNCTIONS DEEPLY: First-class functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of First-class functions.
- Apply First-class functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Callbacks
FUNCTIONS DEEPLY: Callbacks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Callbacks.
- Apply Callbacks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Higher-order functions
FUNCTIONS DEEPLY: Higher-order functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Higher-order functions.
- Apply Higher-order functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Closures
FUNCTIONS DEEPLY: Closures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Closures.
- Apply Closures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lexical scope
FUNCTIONS DEEPLY: Lexical scope. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Lexical scope.
- Apply Lexical scope in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Prototype, Prototype chain, Classes, Inheritance, Composition.
Prototype
OBJECT MODEL: Prototype. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Prototype.
- Apply Prototype in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Prototype chain
OBJECT MODEL: Prototype chain. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Prototype chain.
- Apply Prototype chain in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Classes
OBJECT MODEL: Classes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Classes.
- Apply Classes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Inheritance
OBJECT MODEL: Inheritance. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Inheritance.
- Apply Inheritance in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Composition
OBJECT MODEL: Composition. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Composition.
- Apply Composition in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Custom error classes, Operational vs programmer errors, Error propagation.
Custom error classes
ERROR HANDLING: Custom error classes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Custom error classes.
- Apply Custom error classes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Operational vs programmer errors
ERROR HANDLING: Operational vs programmer errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Operational vs programmer errors.
- Apply Operational vs programmer errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error propagation
ERROR HANDLING: Error propagation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Error propagation.
- Apply Error propagation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Promise, Resolve, Reject, Then, Catch, Finally.
Promise
PROMISES: Promise. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Promise.
- Apply Promise in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Resolve
PROMISES: Resolve. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Resolve.
- Apply Resolve in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reject
PROMISES: Reject. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Reject.
- Apply Reject in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Then
PROMISES: Then. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Then.
- Apply Then in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Catch
PROMISES: Catch. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Catch.
- Apply Catch in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Finally
PROMISES: Finally. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Finally.
- Apply Finally in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Sequential calls, Concurrent calls, Failures, Timeouts.
Sequential calls
ASYNC/AWAIT: Sequential calls. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Sequential calls.
- Apply Sequential calls in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Concurrent calls
ASYNC/AWAIT: Concurrent calls. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Concurrent calls.
- Apply Concurrent calls in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Failures
ASYNC/AWAIT: Failures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Failures.
- Apply Failures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Timeouts
ASYNC/AWAIT: Timeouts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Timeouts.
- Apply Timeouts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Promise.all, Promise.allSettled, Promise.race, Promise.any.
Promise.all
PROMISE UTILITIES: Promise.all. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Promise.all.
- Apply Promise.all in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promise.allSettled
PROMISE UTILITIES: Promise.allSettled. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Promise.allSettled.
- Apply Promise.allSettled in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promise.race
PROMISE UTILITIES: Promise.race. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Promise.race.
- Apply Promise.race in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promise.any
PROMISE UTILITIES: Promise.any. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Promise.any.
- Apply Promise.any in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Task queue, Microtasks, Promises, Timers.
Task queue
JAVASCRIPT EVENT LOOP: Task queue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Task queue.
- Apply Task queue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Microtasks
JAVASCRIPT EVENT LOOP: Microtasks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Microtasks.
- Apply Microtasks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promises
JAVASCRIPT EVENT LOOP: Promises. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Promises.
- Apply Promises in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Timers
JAVASCRIPT EVENT LOOP: Timers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Timers.
- Apply Timers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Primitives, Arrays, Tuples, Objects, Function typing, Return typing.
Primitives
TYPESCRIPT: Primitives. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Primitives.
- Apply Primitives in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Arrays
TYPESCRIPT: Arrays. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Arrays.
- Apply Arrays in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tuples
TYPESCRIPT: Tuples. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Tuples.
- Apply Tuples in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Objects
TYPESCRIPT: Objects. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Objects.
- Apply Objects in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Function typing
TYPESCRIPT: Function typing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Function typing.
- Apply Function typing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Return typing
TYPESCRIPT: Return typing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Return typing.
- Apply Return typing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: Interfaces, Aliases, Unions, Intersections, Generics, Utility types, Narrowing, Discriminated unions and 2 more topics.
Interfaces
ADVANCED TYPESCRIPT: Interfaces. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Interfaces.
- Apply Interfaces in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Aliases
ADVANCED TYPESCRIPT: Aliases. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Aliases.
- Apply Aliases in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unions
ADVANCED TYPESCRIPT: Unions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Unions.
- Apply Unions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Intersections
ADVANCED TYPESCRIPT: Intersections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Intersections.
- Apply Intersections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Generics
ADVANCED TYPESCRIPT: Generics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Generics.
- Apply Generics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Utility types
ADVANCED TYPESCRIPT: Utility types. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Utility types.
- Apply Utility types in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Narrowing
ADVANCED TYPESCRIPT: Narrowing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Narrowing.
- Apply Narrowing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Discriminated unions
ADVANCED TYPESCRIPT: Discriminated unions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Discriminated unions.
- Apply Discriminated unions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mapped types concepts
ADVANCED TYPESCRIPT: Mapped types concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Mapped types concepts.
- Apply Mapped types concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Conditional-type awareness
ADVANCED TYPESCRIPT: Conditional-type awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Conditional-type awareness.
- Apply Conditional-type awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: 100 Questions, 75 Coding Tasks.
100 Questions
BACKEND TYPES: 100 Questions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of 100 Questions.
- Apply 100 Questions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
75 Coding Tasks
BACKEND TYPES: 75 Coding Tasks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of 75 Coding Tasks.
- Apply 75 Coding Tasks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Node.js runtime, V8, Libuv concepts, Npm, Modules, Package.json.
Node.js runtime
NODE.JS FUNDAMENTALS: Node.js runtime. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Node.js runtime.
- Apply Node.js runtime in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
V8
NODE.JS FUNDAMENTALS: V8. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of V8.
- Apply V8 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Libuv concepts
NODE.JS FUNDAMENTALS: Libuv concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Libuv concepts.
- Apply Libuv concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Npm
NODE.JS FUNDAMENTALS: Npm. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Npm.
- Apply Npm in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules
NODE.JS FUNDAMENTALS: Modules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Modules.
- Apply Modules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Package.json
NODE.JS FUNDAMENTALS: Package.json. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Package.json.
- Apply Package.json in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: CommonJS, ECMAScript Modules.
CommonJS
COMMONJS VS ESM: CommonJS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of CommonJS.
- Apply CommonJS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ECMAScript Modules
COMMONJS VS ESM: ECMAScript Modules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of ECMAScript Modules.
- Apply ECMAScript Modules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Timers, Pending callbacks, Poll, Check, Close callbacks, Microtasks, Process.nextTick().
Timers
NODE EVENT LOOP: Timers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Timers.
- Apply Timers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pending callbacks
NODE EVENT LOOP: Pending callbacks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Pending callbacks.
- Apply Pending callbacks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Poll
NODE EVENT LOOP: Poll. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Poll.
- Apply Poll in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Check
NODE EVENT LOOP: Check. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Check.
- Apply Check in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Close callbacks
NODE EVENT LOOP: Close callbacks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Close callbacks.
- Apply Close callbacks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Microtasks
NODE EVENT LOOP: Microtasks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Microtasks.
- Apply Microtasks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Process.nextTick()
NODE EVENT LOOP: Process.nextTick(). Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Process.nextTick().
- Apply Process.nextTick() in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Event Loop Blocking.
Event Loop Blocking
Bad:; javascript; app.get("/report", () => {; // huge CPU calculation; });; Explain how one CPU-heavy task can degrade many requests.
- Explain the core concepts and architecture of Event Loop Blocking.
- Apply Event Loop Blocking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Readable, Writable, Duplex, Transform.
Readable
NODE STREAMS: Readable. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Readable.
- Apply Readable in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Writable
NODE STREAMS: Writable. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Writable.
- Apply Writable in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Duplex
NODE STREAMS: Duplex. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Duplex.
- Apply Duplex in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transform
NODE STREAMS: Transform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Transform.
- Apply Transform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Large files, Streams, Uploads, Exports.
Large files
BACKPRESSURE: Large files. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Large files.
- Apply Large files in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streams
BACKPRESSURE: Streams. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Streams.
- Apply Streams in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Uploads
BACKPRESSURE: Uploads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Uploads.
- Apply Uploads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exports
BACKPRESSURE: Exports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Exports.
- Apply Exports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Buffer.
Buffer
Teach binary data handling.
- Explain the core concepts and architecture of Buffer.
- Apply Buffer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Filesystem APIs, Streams, Paths.
Filesystem APIs
FILE SYSTEM: Filesystem APIs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Filesystem APIs.
- Apply Filesystem APIs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streams
FILE SYSTEM: Streams. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Streams.
- Apply Streams in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Paths
FILE SYSTEM: Paths. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Paths.
- Apply Paths in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Event, Listener, Emitter.
Event
EVENTS: Event. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Event.
- Apply Event in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Listener
EVENTS: Listener. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Listener.
- Apply Listener in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Emitter
EVENTS: Emitter. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Emitter.
- Apply Emitter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Worker Threads.
Worker Threads
Use for CPU-heavy workloads where appropriate.
- Explain the core concepts and architecture of Worker Threads.
- Apply Worker Threads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Spawn, Exec, Fork.
Spawn
CHILD PROCESSES: Spawn. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Spawn.
- Apply Spawn in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exec
CHILD PROCESSES: Exec. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Exec.
- Apply Exec in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Fork
CHILD PROCESSES: Fork. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Fork.
- Apply Fork in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Clustering & Process Scaling.
Clustering & Process Scaling
Teach architecture concepts rather than presenting clustering as the only production deployment option.
- Explain the core concepts and architecture of Clustering & Process Scaling.
- Apply Clustering & Process Scaling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Http Server.
Http Server
Build API first using Node's basic HTTP understanding.; Students should understand what Express abstracts.
- Explain the core concepts and architecture of Http Server.
- Apply Http Server in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Application, Router, Middleware, Error middleware, Request, Response.
Application
EXPRESS 5: Application. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Application.
- Apply Application in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Router
EXPRESS 5: Router. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Router.
- Apply Router in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Middleware
EXPRESS 5: Middleware. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Middleware.
- Apply Middleware in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error middleware
EXPRESS 5: Error middleware. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Error middleware.
- Apply Error middleware in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Request
EXPRESS 5: Request. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Request.
- Apply Request in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Response
EXPRESS 5: Response. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Response.
- Apply Response in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Express Architecture.
Express Architecture
Recommended:; text; src/; ├── modules/; ├── controllers/; ├── services/; ├── repositories/; ├── middleware/; ├── config/; └── shared/
- Explain the core concepts and architecture of Express Architecture.
- Apply Express Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Middleware.
Middleware
Request lifecycle:; Request; Request ID; Logging; Authentication; Authorization; Validation; Controller; Response
- Explain the core concepts and architecture of Middleware.
- Apply Middleware in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Resources, URLs, HTTP semantics, Statelessness.
Resources
REST APIs: Resources. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Resources.
- Apply Resources in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
URLs
REST APIs: URLs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of URLs.
- Apply URLs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HTTP semantics
REST APIs: HTTP semantics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of HTTP semantics.
- Apply HTTP semantics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Statelessness
REST APIs: Statelessness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Statelessness.
- Apply Statelessness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Body, Params, Query, Headers.
Body
API REQUEST VALIDATION: Body. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Body.
- Apply Body in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Params
API REQUEST VALIDATION: Params. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Params.
- Apply Params in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Query
API REQUEST VALIDATION: Query. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Query.
- Apply Query in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Headers
API REQUEST VALIDATION: Headers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Headers.
- Apply Headers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Api Error Design.
Api Error Design
Example:; json; {; "code": "PAYMENT_NOT_FOUND",; "message": "Payment could not be found",; "traceId": "..."; }
- Explain the core concepts and architecture of Api Error Design.
- Apply Api Error Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Api Pagination.
Api Pagination
Compare:; Offset; vs; Cursor/Keyset
- Explain the core concepts and architecture of Api Pagination.
- Apply Api Pagination in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Filtering & Sorting.
Filtering & Sorting
Example:; GET /orders?status=PAID&sort=-createdAt
- Explain the core concepts and architecture of Filtering & Sorting.
- Apply Filtering & Sorting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Api Versioning.
Api Versioning
Understand:; /api/v1/...; and other versioning strategies.
- Explain the core concepts and architecture of Api Versioning.
- Apply Api Versioning in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Idempotency.
Idempotency
Critical backend concept.; Example:; http; POST /payments; Idempotency-Key: payment-123; Retry should not produce duplicate payment.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
11 curriculum topics: Endpoints, Schemas, Status codes, Auth requirements, TypeScript, Express, Validation, Standardized errors and 3 more topics.
Endpoints
OPENAPI: Endpoints. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Endpoints.
- Apply Endpoints in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Schemas
OPENAPI: Schemas. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Schemas.
- Apply Schemas in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Status codes
OPENAPI: Status codes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Status codes.
- Apply Status codes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Auth requirements
OPENAPI: Auth requirements. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Auth requirements.
- Apply Auth requirements in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TypeScript
OPENAPI: TypeScript. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of TypeScript.
- Apply TypeScript in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Express
OPENAPI: Express. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Express.
- Apply Express in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
OPENAPI: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Standardized errors
OPENAPI: Standardized errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Standardized errors.
- Apply Standardized errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
OPENAPI: Pagination. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Pagination.
- Apply Pagination in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Search
OPENAPI: Search. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Search.
- Apply Search in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
OpenAPI
OPENAPI: OpenAPI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of OpenAPI.
- Apply OpenAPI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: SELECT, INSERT, UPDATE, DELETE, WHERE, GROUP BY, Joins.
SELECT
SQL FUNDAMENTALS: SELECT. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of SELECT.
- Apply SELECT in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
INSERT
SQL FUNDAMENTALS: INSERT. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of INSERT.
- Apply INSERT in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
UPDATE
SQL FUNDAMENTALS: UPDATE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of UPDATE.
- Apply UPDATE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DELETE
SQL FUNDAMENTALS: DELETE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of DELETE.
- Apply DELETE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
WHERE
SQL FUNDAMENTALS: WHERE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of WHERE.
- Apply WHERE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
GROUP BY
SQL FUNDAMENTALS: GROUP BY. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of GROUP BY.
- Apply GROUP BY in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Joins
SQL FUNDAMENTALS: Joins. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Joins.
- Apply Joins in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Subqueries, CTE, Window functions, Transactions, Indexes.
Subqueries
ADVANCED SQL: Subqueries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Subqueries.
- Apply Subqueries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CTE
ADVANCED SQL: CTE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of CTE.
- Apply CTE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Window functions
ADVANCED SQL: Window functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Window functions.
- Apply Window functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
ADVANCED SQL: Transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Transactions.
- Apply Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Indexes
ADVANCED SQL: Indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Indexes.
- Apply Indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Tables, Schemas, Relationships, Constraints, Indexes, JSONB concepts, Transactions, Locks.
Tables
POSTGRESQL: Tables. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Tables.
- Apply Tables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Schemas
POSTGRESQL: Schemas. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Schemas.
- Apply Schemas in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Relationships
POSTGRESQL: Relationships. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Relationships.
- Apply Relationships in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Constraints
POSTGRESQL: Constraints. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Constraints.
- Apply Constraints in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Indexes
POSTGRESQL: Indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Indexes.
- Apply Indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JSONB concepts
POSTGRESQL: JSONB concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of JSONB concepts.
- Apply JSONB concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
POSTGRESQL: Transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Transactions.
- Apply Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Locks
POSTGRESQL: Locks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Locks.
- Apply Locks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: ACID, Isolation, Concurrent writes, Rollback.
ACID
DATABASE TRANSACTIONS: ACID. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of ACID.
- Apply ACID in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Isolation
DATABASE TRANSACTIONS: Isolation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Isolation.
- Apply Isolation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Concurrent writes
DATABASE TRANSACTIONS: Concurrent writes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Concurrent writes.
- Apply Concurrent writes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rollback
DATABASE TRANSACTIONS: Rollback. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rollback.
- Apply Rollback in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Read Committed, Repeatable Read, Serializable concepts.
Read Committed
TRANSACTION ISOLATION: Read Committed. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Read Committed.
- Apply Read Committed in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Repeatable Read
TRANSACTION ISOLATION: Repeatable Read. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Repeatable Read.
- Apply Repeatable Read in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Serializable concepts
TRANSACTION ISOLATION: Serializable concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Serializable concepts.
- Apply Serializable concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Indexes, Execution plans, Query shape, Pagination, Connection pooling.
Indexes
QUERY PERFORMANCE: Indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Indexes.
- Apply Indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Execution plans
QUERY PERFORMANCE: Execution plans. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Execution plans.
- Apply Execution plans in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Query shape
QUERY PERFORMANCE: Query shape. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Query shape.
- Apply Query shape in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
QUERY PERFORMANCE: Pagination. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Pagination.
- Apply Pagination in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection pooling
QUERY PERFORMANCE: Connection pooling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Connection pooling.
- Apply Connection pooling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Schema, Models, Relations, Queries, Migrations, Transactions.
Schema
PRISMA: Schema. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Schema.
- Apply Schema in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Models
PRISMA: Models. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Models.
- Apply Models in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Relations
PRISMA: Relations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Relations.
- Apply Relations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queries
PRISMA: Queries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Queries.
- Apply Queries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Migrations
PRISMA: Migrations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Migrations.
- Apply Migrations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
PRISMA: Transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Transactions.
- Apply Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Typeorm Awareness.
Typeorm Awareness
Teach enough for enterprise/NestJS environments.; PwC's current NestJS role explicitly lists both TypeORM and Prisma. ([LinkedIn][1])
- Explain the core concepts and architecture of Typeorm Awareness.
- Apply Typeorm Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Database, Collections, Documents, BSON, ObjectId, CRUD.
Database
MONGODB: Database. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Database.
- Apply Database in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Collections
MONGODB: Collections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Collections.
- Apply Collections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Documents
MONGODB: Documents. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Documents.
- Apply Documents in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
BSON
MONGODB: BSON. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of BSON.
- Apply BSON in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ObjectId
MONGODB: ObjectId. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of ObjectId.
- Apply ObjectId in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CRUD
MONGODB: CRUD. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of CRUD.
- Apply CRUD in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: Embed, Reference.
Embed
MONGODB DATA MODELING: Embed. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Embed.
- Apply Embed in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reference
MONGODB DATA MODELING: Reference. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Reference.
- Apply Reference in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Schemas, Models, Validation, Hooks, Relationships concepts.
Schemas
MONGOOSE: Schemas. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Schemas.
- Apply Schemas in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Models
MONGOOSE: Models. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Models.
- Apply Models in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
MONGOOSE: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Hooks
MONGOOSE: Hooks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Hooks.
- Apply Hooks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Relationships concepts
MONGOOSE: Relationships concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Relationships concepts.
- Apply Relationships concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Match, Project, Group, Lookup, Unwind, Sort, Facet.
Match
MONGODB AGGREGATION: Match. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Match.
- Apply Match in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Project
MONGODB AGGREGATION: Project. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Project.
- Apply Project in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Group
MONGODB AGGREGATION: Group. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Group.
- Apply Group in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lookup
MONGODB AGGREGATION: Lookup. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Lookup.
- Apply Lookup in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unwind
MONGODB AGGREGATION: Unwind. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Unwind.
- Apply Unwind in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sort
MONGODB AGGREGATION: Sort. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Sort.
- Apply Sort in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Facet
MONGODB AGGREGATION: Facet. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Facet.
- Apply Facet in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Single field, Compound, Unique, TTL.
Single field
MONGODB INDEXING: Single field. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Single field.
- Apply Single field in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Compound
MONGODB INDEXING: Compound. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Compound.
- Apply Compound in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unique
MONGODB INDEXING: Unique. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Unique.
- Apply Unique in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TTL
MONGODB INDEXING: TTL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of TTL.
- Apply TTL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Sql Vs Nosql.
Sql Vs Nosql
Students should answer:; Why PostgreSQL here and MongoDB there?; Do not teach MongoDB simply because Node often appears in MERN.
- Explain the core concepts and architecture of Sql Vs Nosql.
- Apply Sql Vs Nosql in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Sessions, Tokens, JWT, OAuth2.
Sessions
AUTHENTICATION: Sessions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Sessions.
- Apply Sessions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tokens
AUTHENTICATION: Tokens. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Tokens.
- Apply Tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JWT
AUTHENTICATION: JWT. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of JWT.
- Apply JWT in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
OAuth2
AUTHENTICATION: OAuth2. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of OAuth2.
- Apply OAuth2 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Password hashing, Salts, Password reset, Brute-force protection.
Password hashing
PASSWORD SECURITY: Password hashing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Password hashing.
- Apply Password hashing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Salts
PASSWORD SECURITY: Salts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Salts.
- Apply Salts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Password reset
PASSWORD SECURITY: Password reset. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Password reset.
- Apply Password reset in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Brute-force protection
PASSWORD SECURITY: Brute-force protection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Brute-force protection.
- Apply Brute-force protection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Access, Refresh, Claims, Expiry, Signature, Rotation, Revocation concepts.
Access
JWT: Access. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Access.
- Apply Access in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Refresh
JWT: Refresh. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Refresh.
- Apply Refresh in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Claims
JWT: Claims. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Claims.
- Apply Claims in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Expiry
JWT: Expiry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Expiry.
- Apply Expiry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Signature
JWT: Signature. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Signature.
- Apply Signature in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rotation
JWT: Rotation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rotation.
- Apply Rotation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Revocation concepts
JWT: Revocation concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Revocation concepts.
- Apply Revocation concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Rbac.
Rbac
Roles:; text; CUSTOMER; SUPPORT; MANAGER; ADMIN
- Explain the core concepts and architecture of Rbac.
- Apply Rbac in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Object-Level Authorization.
Object-Level Authorization
Scenario:; User authenticated correctly.; Requests another user's order.; Backend must deny it.
- Explain the core concepts and architecture of Object-Level Authorization.
- Apply Object-Level Authorization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Authorization Code, PKCE, Client Credentials, Scopes, Identity providers.
Authorization Code
OAUTH2/OIDC: Authorization Code. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Authorization Code.
- Apply Authorization Code in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PKCE
OAUTH2/OIDC: PKCE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of PKCE.
- Apply PKCE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Client Credentials
OAUTH2/OIDC: Client Credentials. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Client Credentials.
- Apply Client Credentials in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scopes
OAUTH2/OIDC: Scopes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Scopes.
- Apply Scopes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Identity providers
OAUTH2/OIDC: Identity providers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Identity providers.
- Apply Identity providers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: SQL injection, NoSQL injection, Broken access control, Mass assignment concepts, CORS, CSRF, XSS awareness, Rate limits and 2 more topics.
SQL injection
API SECURITY: SQL injection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of SQL injection.
- Apply SQL injection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
NoSQL injection
API SECURITY: NoSQL injection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of NoSQL injection.
- Apply NoSQL injection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Broken access control
API SECURITY: Broken access control. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Broken access control.
- Apply Broken access control in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mass assignment concepts
API SECURITY: Mass assignment concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Mass assignment concepts.
- Apply Mass assignment concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CORS
API SECURITY: CORS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of CORS.
- Apply CORS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CSRF
API SECURITY: CSRF. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of CSRF.
- Apply CSRF in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
XSS awareness
API SECURITY: XSS awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of XSS awareness.
- Apply XSS awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limits
API SECURITY: Rate limits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rate limits.
- Apply Rate limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secret exposure
API SECURITY: Secret exposure. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Secret exposure.
- Apply Secret exposure in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency vulnerabilities
API SECURITY: Dependency vulnerabilities. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Dependency vulnerabilities.
- Apply Dependency vulnerabilities in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Organization, Users, Authentication, RBAC, Tenant isolation, Audit trail.
Organization
MULTI-TENANT SECURITY: Organization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Organization.
- Apply Organization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Users
MULTI-TENANT SECURITY: Users. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Users.
- Apply Users in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication
MULTI-TENANT SECURITY: Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Authentication.
- Apply Authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RBAC
MULTI-TENANT SECURITY: RBAC. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of RBAC.
- Apply RBAC in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tenant isolation
MULTI-TENANT SECURITY: Tenant isolation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Tenant isolation.
- Apply Tenant isolation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Audit trail
MULTI-TENANT SECURITY: Audit trail. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Audit trail.
- Apply Audit trail in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Modules, Controllers, Providers, Dependency Injection.
Modules
NESTJS FOUNDATION: Modules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Modules.
- Apply Modules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Controllers
NESTJS FOUNDATION: Controllers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Controllers.
- Apply Controllers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Providers
NESTJS FOUNDATION: Providers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Providers.
- Apply Providers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency Injection
NESTJS FOUNDATION: Dependency Injection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Dependency Injection.
- Apply Dependency Injection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Nestjs Modules.
Nestjs Modules
Build domain modules:; text; AuthModule; UsersModule; OrdersModule; PaymentsModule
- Explain the core concepts and architecture of Nestjs Modules.
- Apply Nestjs Modules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Providers.
Providers
Teach dependency injection deeply.
- Explain the core concepts and architecture of Providers.
- Apply Providers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: Transformation, Validation.
Transformation
PIPES: Transformation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Transformation.
- Apply Transformation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
PIPES: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: Authentication, Authorization.
Authentication
GUARDS: Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Authentication.
- Apply Authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authorization
GUARDS: Authorization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Authorization.
- Apply Authorization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Response transforms, Metrics, Logging, Cross-cutting behavior.
Response transforms
INTERCEPTORS: Response transforms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Response transforms.
- Apply Response transforms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Metrics
INTERCEPTORS: Metrics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Metrics.
- Apply Metrics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logging
INTERCEPTORS: Logging. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Logging.
- Apply Logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cross-cutting behavior
INTERCEPTORS: Cross-cutting behavior. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Cross-cutting behavior.
- Apply Cross-cutting behavior in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Exception Filters.
Exception Filters
Standardize error handling.
- Explain the core concepts and architecture of Exception Filters.
- Apply Exception Filters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Custom Decorators.
Custom Decorators
Use carefully to simplify repeated context extraction.
- Explain the core concepts and architecture of Custom Decorators.
- Apply Custom Decorators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Nestjs Configuration.
Nestjs Configuration
Environment-specific configuration.
- Explain the core concepts and architecture of Nestjs Configuration.
- Apply Nestjs Configuration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: PostgreSQL, Prisma/TypeORM, MongoDB, Identity, Customer, Catalog, Orders, Payments.
PostgreSQL
NESTJS DATABASE: PostgreSQL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of PostgreSQL.
- Apply PostgreSQL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Prisma/TypeORM
NESTJS DATABASE: Prisma/TypeORM. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Prisma/TypeORM.
- Apply Prisma/TypeORM in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
MongoDB
NESTJS DATABASE: MongoDB. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of MongoDB.
- Apply MongoDB in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Identity
NESTJS DATABASE: Identity. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Identity.
- Apply Identity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Customer
NESTJS DATABASE: Customer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Customer.
- Apply Customer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Catalog
NESTJS DATABASE: Catalog. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Catalog.
- Apply Catalog in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Orders
NESTJS DATABASE: Orders. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Orders.
- Apply Orders in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Payments
NESTJS DATABASE: Payments. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Payments.
- Apply Payments in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Caching, TTL, Counters, Temporary state, Rate limiting, Sessions concepts.
Caching
REDIS: Caching. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Caching.
- Apply Caching in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TTL
REDIS: TTL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of TTL.
- Apply TTL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Counters
REDIS: Counters. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Counters.
- Apply Counters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Temporary state
REDIS: Temporary state. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Temporary state.
- Apply Temporary state in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limiting
REDIS: Rate limiting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rate limiting.
- Apply Rate limiting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sessions concepts
REDIS: Sessions concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Sessions concepts.
- Apply Sessions concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Cache-Aside.
Cache-Aside
Flow:; API → Redis → DB → Cache → Response
- Explain the core concepts and architecture of Cache-Aside.
- Apply Cache-Aside in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Cache Invalidation.
Cache Invalidation
Students must understand stale data.
- Explain the core concepts and architecture of Cache Invalidation.
- Apply Cache Invalidation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Cache Stampede.
Cache Stampede
Discuss mitigation concepts.
- Explain the core concepts and architecture of Cache Stampede.
- Apply Cache Stampede in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Distributed Locks.
Distributed Locks
Teach concepts and risks.; Do not use distributed locks blindly.
- Explain the core concepts and architecture of Distributed Locks.
- Apply Distributed Locks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Email, Reports, Imports, Notifications, Payments reconciliation.
BACKGROUND JOBS: Email. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Email.
- Apply Email in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reports
BACKGROUND JOBS: Reports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Reports.
- Apply Reports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Imports
BACKGROUND JOBS: Imports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Imports.
- Apply Imports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notifications
BACKGROUND JOBS: Notifications. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Notifications.
- Apply Notifications in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Payments reconciliation
BACKGROUND JOBS: Payments reconciliation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Payments reconciliation.
- Apply Payments reconciliation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Queue, Worker, Retries, Concurrency, Scheduled jobs, Failures.
Queue
BULLMQ: Queue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Queue.
- Apply Queue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Worker
BULLMQ: Worker. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Worker.
- Apply Worker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retries
BULLMQ: Retries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Retries.
- Apply Retries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Concurrency
BULLMQ: Concurrency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Concurrency.
- Apply Concurrency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scheduled jobs
BULLMQ: Scheduled jobs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Scheduled jobs.
- Apply Scheduled jobs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Failures
BULLMQ: Failures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Failures.
- Apply Failures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Job State.
Job State
text; WAITING; ACTIVE; COMPLETED; FAILED
- Explain the core concepts and architecture of Job State.
- Apply Job State in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Idempotent Jobs.
Idempotent Jobs
Background tasks may execute multiple times.; Design them safely.
- Explain the core concepts and architecture of Idempotent Jobs.
- Apply Idempotent Jobs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Signatures, Authentication, Retries, Duplicate delivery, Idempotency.
Signatures
WEBHOOKS: Signatures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Signatures.
- Apply Signatures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication
WEBHOOKS: Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Authentication.
- Apply Authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retries
WEBHOOKS: Retries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Retries.
- Apply Retries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Duplicate delivery
WEBHOOKS: Duplicate delivery. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Duplicate delivery.
- Apply Duplicate delivery in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
WEBHOOKS: Idempotency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Messaging, Notifications, Collaborative applications.
Messaging
REAL-TIME BACKENDS: Messaging. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Messaging.
- Apply Messaging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notifications
REAL-TIME BACKENDS: Notifications. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Notifications.
- Apply Notifications in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Collaborative applications
REAL-TIME BACKENDS: Collaborative applications. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Collaborative applications.
- Apply Collaborative applications in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Connections, Rooms, Events, Reconnect, Scaling concepts, Users, Messages, Online status and 1 more topics.
Connections
SOCKET.IO: Connections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Connections.
- Apply Connections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rooms
SOCKET.IO: Rooms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rooms.
- Apply Rooms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Events
SOCKET.IO: Events. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Events.
- Apply Events in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reconnect
SOCKET.IO: Reconnect. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Reconnect.
- Apply Reconnect in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scaling concepts
SOCKET.IO: Scaling concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Scaling concepts.
- Apply Scaling concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Users
SOCKET.IO: Users. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Users.
- Apply Users in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Messages
SOCKET.IO: Messages. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Messages.
- Apply Messages in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Online status
SOCKET.IO: Online status. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Online status.
- Apply Online status in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Redis concepts for scaling
SOCKET.IO: Redis concepts for scaling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Redis concepts for scaling.
- Apply Redis concepts for scaling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Progress, Feeds, AI tokens.
Progress
SERVER-SENT EVENTS: Progress. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Progress.
- Apply Progress in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Feeds
SERVER-SENT EVENTS: Feeds. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Feeds.
- Apply Feeds in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
AI tokens
SERVER-SENT EVENTS: AI tokens. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of AI tokens.
- Apply AI tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Multipart, Validation, Limits, Content type, Storage.
Multipart
FILE UPLOAD: Multipart. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Multipart.
- Apply Multipart in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
FILE UPLOAD: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Limits
FILE UPLOAD: Limits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Limits.
- Apply Limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Content type
FILE UPLOAD: Content type. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Content type.
- Apply Content type in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Storage
FILE UPLOAD: Storage. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Storage.
- Apply Storage in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Aws S3.
Aws S3
Use object storage rather than storing binary files directly in application databases by default.
- Explain the core concepts and architecture of Aws S3.
- Apply Aws S3 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Presigned Urls.
Presigned Urls
Teach efficient direct uploads.
- Explain the core concepts and architecture of Presigned Urls.
- Apply Presigned Urls in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Fixed Window, Sliding Window, Token Bucket concepts.
Fixed Window
API RATE LIMITING: Fixed Window. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Fixed Window.
- Apply Fixed Window in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sliding Window
API RATE LIMITING: Sliding Window. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Sliding Window.
- Apply Sliding Window in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token Bucket concepts
API RATE LIMITING: Token Bucket concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Token Bucket concepts.
- Apply Token Bucket concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Service boundaries, Loose coupling, Independent deployment, Database ownership.
Service boundaries
MICROSERVICES FUNDAMENTALS: Service boundaries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Service boundaries.
- Apply Service boundaries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Loose coupling
MICROSERVICES FUNDAMENTALS: Loose coupling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Loose coupling.
- Apply Loose coupling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Independent deployment
MICROSERVICES FUNDAMENTALS: Independent deployment. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Independent deployment.
- Apply Independent deployment in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Database ownership
MICROSERVICES FUNDAMENTALS: Database ownership. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Database ownership.
- Apply Database ownership in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Modular Monolith.
Modular Monolith
Teach first.; Do not force microservices for small systems.
- Explain the core concepts and architecture of Modular Monolith.
- Apply Modular Monolith in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: REST, Events, Queues, GRPC awareness.
REST
MICROSERVICE COMMUNICATION: REST. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of REST.
- Apply REST in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Events
MICROSERVICE COMMUNICATION: Events. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Events.
- Apply Events in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queues
MICROSERVICE COMMUNICATION: Queues. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Queues.
- Apply Queues in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
GRPC awareness
MICROSERVICE COMMUNICATION: GRPC awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of GRPC awareness.
- Apply GRPC awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Nestjs Microservices.
Nestjs Microservices
NestJS currently documents transports including Redis, RabbitMQ, Kafka, NATS, MQTT and gRPC. ([NestJS Documentation][3])
- Explain the core concepts and architecture of Nestjs Microservices.
- Apply Nestjs Microservices in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Broker, Topic, Partition, Producer, Consumer, Consumer Group, Offset, Keys.
Broker
KAFKA: Broker. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Broker.
- Apply Broker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Topic
KAFKA: Topic. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Topic.
- Apply Topic in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Partition
KAFKA: Partition. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Partition.
- Apply Partition in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Producer
KAFKA: Producer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Producer.
- Apply Producer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consumer
KAFKA: Consumer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Consumer.
- Apply Consumer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consumer Group
KAFKA: Consumer Group. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Consumer Group.
- Apply Consumer Group in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Offset
KAFKA: Offset. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Offset.
- Apply Offset in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Keys
KAFKA: Keys. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Keys.
- Apply Keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: At-most-once, At-least-once, Exactly-once concepts.
At-most-once
KAFKA DELIVERY: At-most-once. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of At-most-once.
- Apply At-most-once in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
At-least-once
KAFKA DELIVERY: At-least-once. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of At-least-once.
- Apply At-least-once in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exactly-once concepts
KAFKA DELIVERY: Exactly-once concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Exactly-once concepts.
- Apply Exactly-once concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Retry, Dead-letter topics, Poison messages.
Retry
KAFKA RETRIES: Retry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Retry.
- Apply Retry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dead-letter topics
KAFKA RETRIES: Dead-letter topics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Dead-letter topics.
- Apply Dead-letter topics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Poison messages
KAFKA RETRIES: Poison messages. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Poison messages.
- Apply Poison messages in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Idempotent Consumers.
Idempotent Consumers
Event:; PAYMENT_COMPLETED; delivered twice.; Business operation must remain correct.
- Explain the core concepts and architecture of Idempotent Consumers.
- Apply Idempotent Consumers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Exchange, Queue, Routing, Acknowledgements.
Exchange
RABBITMQ AWARENESS: Exchange. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Exchange.
- Apply Exchange in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queue
RABBITMQ AWARENESS: Queue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Queue.
- Apply Queue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Routing
RABBITMQ AWARENESS: Routing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Routing.
- Apply Routing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Acknowledgements
RABBITMQ AWARENESS: Acknowledgements. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Acknowledgements.
- Apply Acknowledgements in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Aws Sqs/Sns.
Aws Sqs/Sns
Teach cloud-managed queue/pub-sub concepts.
- Explain the core concepts and architecture of Aws Sqs/Sns.
- Apply Aws Sqs/Sns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Distributed Transactions.
Distributed Transactions
Teach why one SQL transaction cannot span independently deployed services reliably.
- Explain the core concepts and architecture of Distributed Transactions.
- Apply Distributed Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Choreography, Orchestration, Compensation.
Choreography
SAGA: Choreography. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Choreography.
- Apply Choreography in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Orchestration
SAGA: Orchestration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Orchestration.
- Apply Orchestration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Compensation
SAGA: Compensation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Compensation.
- Apply Compensation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Transactional Outbox.
Transactional Outbox
Solve dual-write problem.; text; DB transaction; ├── save order; └── save outbox event
- Explain the core concepts and architecture of Transactional Outbox.
- Apply Transactional Outbox in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Timeout, Retry, Exponential backoff, Jitter, Circuit breaker concepts.
Timeout
RESILIENCE: Timeout. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Timeout.
- Apply Timeout in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry
RESILIENCE: Retry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Retry.
- Apply Retry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exponential backoff
RESILIENCE: Exponential backoff. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Exponential backoff.
- Apply Exponential backoff in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Jitter
RESILIENCE: Jitter. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Jitter.
- Apply Jitter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Circuit breaker concepts
RESILIENCE: Circuit breaker concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Circuit breaker concepts.
- Apply Circuit breaker concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: NestJS, PostgreSQL, Redis, Kafka, Saga, Outbox, Idempotency.
NestJS
RETRY STORMS: NestJS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of NestJS.
- Apply NestJS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PostgreSQL
RETRY STORMS: PostgreSQL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of PostgreSQL.
- Apply PostgreSQL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Redis
RETRY STORMS: Redis. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Redis.
- Apply Redis in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Kafka
RETRY STORMS: Kafka. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Kafka.
- Apply Kafka in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Saga
RETRY STORMS: Saga. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Saga.
- Apply Saga in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Outbox
RETRY STORMS: Outbox. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Outbox.
- Apply Outbox in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
RETRY STORMS: Idempotency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Unit, Integration, Contract, End-to-End.
Unit
TESTING STRATEGY: Unit. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Unit.
- Apply Unit in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Integration
TESTING STRATEGY: Integration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Integration.
- Apply Integration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Contract
TESTING STRATEGY: Contract. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Contract.
- Apply Contract in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
End-to-End
TESTING STRATEGY: End-to-End. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of End-to-End.
- Apply End-to-End in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Services, Domain rules, Utilities.
Services
UNIT TESTS: Services. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Services.
- Apply Services in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Domain rules
UNIT TESTS: Domain rules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Domain rules.
- Apply Domain rules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Utilities
UNIT TESTS: Utilities. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Utilities.
- Apply Utilities in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Mocking.
Mocking
Mock external systems where appropriate.
- Explain the core concepts and architecture of Mocking.
- Apply Mocking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: HTTP, Auth, DB, Validation.
HTTP
API INTEGRATION TESTS: HTTP. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of HTTP.
- Apply HTTP in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Auth
API INTEGRATION TESTS: Auth. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Auth.
- Apply Auth in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DB
API INTEGRATION TESTS: DB. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of DB.
- Apply DB in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
API INTEGRATION TESTS: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Database Tests.
Database Tests
Prefer realistic integration behavior for critical persistence logic.
- Explain the core concepts and architecture of Database Tests.
- Apply Database Tests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Testcontainers Awareness.
Testcontainers Awareness
Use ephemeral real dependencies where practical.
- Explain the core concepts and architecture of Testcontainers Awareness.
- Apply Testcontainers Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Contract Testing.
Contract Testing
Understand producer/consumer compatibility.
- Explain the core concepts and architecture of Contract Testing.
- Apply Contract Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Load, Stress, Spike, Soak.
Load
LOAD TESTING: Load. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Load.
- Apply Load in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Stress
LOAD TESTING: Stress. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Stress.
- Apply Stress in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Spike
LOAD TESTING: Spike. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Spike.
- Apply Spike in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Soak
LOAD TESTING: Soak. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Soak.
- Apply Soak in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Requests/sec, Event-loop delay, CPU, Memory, P50, P95, P99.
Requests/sec
NODE PERFORMANCE: Requests/sec. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Requests/sec.
- Apply Requests/sec in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Event-loop delay
NODE PERFORMANCE: Event-loop delay. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Event-loop delay.
- Apply Event-loop delay in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CPU
NODE PERFORMANCE: CPU. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of CPU.
- Apply CPU in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Memory
NODE PERFORMANCE: Memory. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Memory.
- Apply Memory in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P50
NODE PERFORMANCE: P50. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of P50.
- Apply P50 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P95
NODE PERFORMANCE: P95. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of P95.
- Apply P95 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P99
NODE PERFORMANCE: P99. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of P99.
- Apply P99 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Event Loop Lag.
Event Loop Lag
Critical Node-specific production metric.
- Explain the core concepts and architecture of Event Loop Lag.
- Apply Event Loop Lag in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Heap, Allocation, Leaks, Caches, References.
Heap
MEMORY: Heap. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Heap.
- Apply Heap in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Allocation
MEMORY: Allocation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Allocation.
- Apply Allocation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Leaks
MEMORY: Leaks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Leaks.
- Apply Leaks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Caches
MEMORY: Caches. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Caches.
- Apply Caches in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
References
MEMORY: References. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of References.
- Apply References in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Global collections, Event listeners, Closures, Unbounded caches, Timers.
Global collections
MEMORY LEAK DEBUGGING: Global collections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Global collections.
- Apply Global collections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Event listeners
MEMORY LEAK DEBUGGING: Event listeners. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Event listeners.
- Apply Event listeners in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Closures
MEMORY LEAK DEBUGGING: Closures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Closures.
- Apply Closures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unbounded caches
MEMORY LEAK DEBUGGING: Unbounded caches. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Unbounded caches.
- Apply Unbounded caches in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Timers
MEMORY LEAK DEBUGGING: Timers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Timers.
- Apply Timers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Cpu Profiling.
Cpu Profiling
Identify expensive computation.
- Explain the core concepts and architecture of Cpu Profiling.
- Apply Cpu Profiling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Indexes, Connection pool, Slow queries, Locks, Pagination.
Indexes
DATABASE PERFORMANCE: Indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Indexes.
- Apply Indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection pool
DATABASE PERFORMANCE: Connection pool. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Connection pool.
- Apply Connection pool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Slow queries
DATABASE PERFORMANCE: Slow queries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Slow queries.
- Apply Slow queries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Locks
DATABASE PERFORMANCE: Locks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Locks.
- Apply Locks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
DATABASE PERFORMANCE: Pagination. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Pagination.
- Apply Pagination in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Hit Ratio, Misses, Evictions.
Hit Ratio
CACHE PERFORMANCE: Hit Ratio. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Hit Ratio.
- Apply Hit Ratio in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Misses
CACHE PERFORMANCE: Misses. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Misses.
- Apply Misses in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Evictions
CACHE PERFORMANCE: Evictions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Evictions.
- Apply Evictions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Logging.
Logging
Use structured logs.; Example:; json; {; "traceId": "...",; "service": "order-api",; "route": "/orders",; "durationMs": 92; }
- Explain the core concepts and architecture of Logging.
- Apply Logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Correlation Ids.
Correlation Ids
Trace one business request across services.
- Explain the core concepts and architecture of Correlation Ids.
- Apply Correlation Ids in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Request rate, Error rate, Latency, Event-loop lag, Queue depth, DB pool usage.
Request rate
METRICS: Request rate. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Request rate.
- Apply Request rate in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error rate
METRICS: Error rate. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Error rate.
- Apply Error rate in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Latency
METRICS: Latency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Latency.
- Apply Latency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Event-loop lag
METRICS: Event-loop lag. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Event-loop lag.
- Apply Event-loop lag in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queue depth
METRICS: Queue depth. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Queue depth.
- Apply Queue depth in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DB pool usage
METRICS: DB pool usage. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of DB pool usage.
- Apply DB pool usage in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Trace, Span, Context propagation.
Trace
OPENTELEMETRY: Trace. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Trace.
- Apply Trace in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Span
OPENTELEMETRY: Span. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Span.
- Apply Span in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Context propagation
OPENTELEMETRY: Context propagation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Context propagation.
- Apply Context propagation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Distributed Tracing.
Distributed Tracing
Trace:; Gateway; Order Service; Payment Service; PostgreSQL; Kafka; NestJS's current documentation includes a dedicated observability section covering distributed tracing. ([NestJS Documentation][3])
- Explain the core concepts and architecture of Distributed Tracing.
- Apply Distributed Tracing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Liveness, Readiness, Dependency health.
Liveness
HEALTH CHECKS: Liveness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Liveness.
- Apply Liveness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Readiness
HEALTH CHECKS: Readiness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Readiness.
- Apply Readiness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency health
HEALTH CHECKS: Dependency health. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Dependency health.
- Apply Dependency health in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
19 curriculum topics: CPU 100%, API latency high, DB healthy, CPU 35%, Requests waiting, DB pool 100%, Slow SQL, Long transactions and 11 more topics.
CPU 100%
PRODUCTION INCIDENTS: CPU 100%. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of CPU 100%.
- Apply CPU 100% in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API latency high
PRODUCTION INCIDENTS: API latency high. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of API latency high.
- Apply API latency high in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DB healthy
PRODUCTION INCIDENTS: DB healthy. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of DB healthy.
- Apply DB healthy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CPU 35%
PRODUCTION INCIDENTS: CPU 35%. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of CPU 35%.
- Apply CPU 35% in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Requests waiting
PRODUCTION INCIDENTS: Requests waiting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Requests waiting.
- Apply Requests waiting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DB pool 100%
PRODUCTION INCIDENTS: DB pool 100%. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of DB pool 100%.
- Apply DB pool 100% in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Slow SQL
PRODUCTION INCIDENTS: Slow SQL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Slow SQL.
- Apply Slow SQL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Long transactions
PRODUCTION INCIDENTS: Long transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Long transactions.
- Apply Long transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection leaks
PRODUCTION INCIDENTS: Connection leaks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Connection leaks.
- Apply Connection leaks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consumer throughput
PRODUCTION INCIDENTS: Consumer throughput. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Consumer throughput.
- Apply Consumer throughput in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Errors
PRODUCTION INCIDENTS: Errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Errors.
- Apply Errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Downstream DB
PRODUCTION INCIDENTS: Downstream DB. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Downstream DB.
- Apply Downstream DB in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Partitions
PRODUCTION INCIDENTS: Partitions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Partitions.
- Apply Partitions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Webhooks
PRODUCTION INCIDENTS: Webhooks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Webhooks.
- Apply Webhooks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retries
PRODUCTION INCIDENTS: Retries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Retries.
- Apply Retries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
PRODUCTION INCIDENTS: Idempotency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Listeners
PRODUCTION INCIDENTS: Listeners. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Listeners.
- Apply Listeners in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache
PRODUCTION INCIDENTS: Cache. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Cache.
- Apply Cache in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retained objects
PRODUCTION INCIDENTS: Retained objects. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Retained objects.
- Apply Retained objects in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Image, Container, Dockerfile, Multi-stage builds, Networks, Volumes, Environment variables.
Image
DOCKER: Image. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Image.
- Apply Image in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Container
DOCKER: Container. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Container.
- Apply Container in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dockerfile
DOCKER: Dockerfile. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Dockerfile.
- Apply Dockerfile in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Multi-stage builds
DOCKER: Multi-stage builds. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Multi-stage builds.
- Apply Multi-stage builds in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Networks
DOCKER: Networks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Networks.
- Apply Networks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Volumes
DOCKER: Volumes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Volumes.
- Apply Volumes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environment variables
DOCKER: Environment variables. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Environment variables.
- Apply Environment variables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Docker Compose.
Docker Compose
Local system:; text; Node/NestJS; PostgreSQL; MongoDB; Redis; Kafka; Worker
- Explain the core concepts and architecture of Docker Compose.
- Apply Docker Compose in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Files, Permissions, Processes, Environment, Ports, Logs.
Files
LINUX: Files. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Files.
- Apply Files in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Permissions
LINUX: Permissions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Permissions.
- Apply Permissions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Processes
LINUX: Processes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Processes.
- Apply Processes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environment
LINUX: Environment. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Environment.
- Apply Environment in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Ports
LINUX: Ports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Ports.
- Apply Ports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logs
LINUX: Logs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Logs.
- Apply Logs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Pods, Deployments, Services, ConfigMaps, Secrets, Probes, Resource limits, Autoscaling concepts and 1 more topics.
Pods
KUBERNETES: Pods. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Pods.
- Apply Pods in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Deployments
KUBERNETES: Deployments. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Deployments.
- Apply Deployments in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Services
KUBERNETES: Services. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Services.
- Apply Services in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ConfigMaps
KUBERNETES: ConfigMaps. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of ConfigMaps.
- Apply ConfigMaps in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secrets
KUBERNETES: Secrets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Secrets.
- Apply Secrets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Probes
KUBERNETES: Probes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Probes.
- Apply Probes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Resource limits
KUBERNETES: Resource limits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Resource limits.
- Apply Resource limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Autoscaling concepts
KUBERNETES: Autoscaling concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Autoscaling concepts.
- Apply Autoscaling concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rolling deployments
KUBERNETES: Rolling deployments. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rolling deployments.
- Apply Rolling deployments in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Aws Iam.
Aws Iam
Teach least privilege.
- Explain the core concepts and architecture of Aws Iam.
- Apply Aws Iam in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Aws Ec2.
Aws Ec2
Deploy Node workloads.
- Explain the core concepts and architecture of Aws Ec2.
- Apply Aws Ec2 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Rds.
Rds
Managed PostgreSQL.
- Explain the core concepts and architecture of Rds.
- Apply Rds in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: S3.
S3
Object storage.
- Explain the core concepts and architecture of S3.
- Apply S3 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Lambda.
Lambda
Teach Node.js serverless APIs.
- Explain the core concepts and architecture of Lambda.
- Apply Lambda in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Api Gateway.
Api Gateway
Core concepts, implementation patterns, engineering trade-offs and production considerations for Api Gateway.
- Explain the core concepts and architecture of Api Gateway.
- Apply Api Gateway in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Sqs.
Sqs
Managed queue.
- Explain the core concepts and architecture of Sqs.
- Apply Sqs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Sns.
Sns
Pub/sub.
- Explain the core concepts and architecture of Sns.
- Apply Sns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Partition key, Sort key, Access patterns, Secondary indexes concepts.
Partition key
DYNAMODB AWARENESS: Partition key. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Partition key.
- Apply Partition key in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sort key
DYNAMODB AWARENESS: Sort key. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Sort key.
- Apply Sort key in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Access patterns
DYNAMODB AWARENESS: Access patterns. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Access patterns.
- Apply Access patterns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secondary indexes concepts
DYNAMODB AWARENESS: Secondary indexes concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Secondary indexes concepts.
- Apply Secondary indexes concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Logs, Metrics, Alarms.
Logs
CLOUDWATCH: Logs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Logs.
- Apply Logs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Metrics
CLOUDWATCH: Metrics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Metrics.
- Apply Metrics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Alarms
CLOUDWATCH: Alarms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Alarms.
- Apply Alarms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Ci/Cd.
Ci/Cd
Pipeline:; Commit; Lint; Type Check; Unit Tests; Integration Tests; Security Scan; Docker Build; Deploy; Health Check
- Explain the core concepts and architecture of Ci/Cd.
- Apply Ci/Cd in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Github Actions.
Github Actions
Hands-on pipeline.
- Explain the core concepts and architecture of Github Actions.
- Apply Github Actions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Jenkins Awareness.
Jenkins Awareness
Relevant because enterprise Node roles still mention Jenkins. ([LinkedIn][10])
- Explain the core concepts and architecture of Jenkins Awareness.
- Apply Jenkins Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Rolling, Blue/Green, Canary, Rollback.
Rolling
DEPLOYMENT STRATEGIES: Rolling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rolling.
- Apply Rolling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Blue/Green
DEPLOYMENT STRATEGIES: Blue/Green. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Blue/Green.
- Apply Blue/Green in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Canary
DEPLOYMENT STRATEGIES: Canary. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Canary.
- Apply Canary in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rollback
DEPLOYMENT STRATEGIES: Rollback. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rollback.
- Apply Rollback in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Clean Architecture.
Clean Architecture
Separate:; Domain; Application; Infrastructure; API
- Explain the core concepts and architecture of Clean Architecture.
- Apply Clean Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Entity, Value Object, Aggregate, Bounded Context, Domain Event.
Entity
DOMAIN-DRIVEN DESIGN FUNDAMENTALS: Entity. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Entity.
- Apply Entity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Value Object
DOMAIN-DRIVEN DESIGN FUNDAMENTALS: Value Object. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Value Object.
- Apply Value Object in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Aggregate
DOMAIN-DRIVEN DESIGN FUNDAMENTALS: Aggregate. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Aggregate.
- Apply Aggregate in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Bounded Context
DOMAIN-DRIVEN DESIGN FUNDAMENTALS: Bounded Context. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Bounded Context.
- Apply Bounded Context in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Domain Event
DOMAIN-DRIVEN DESIGN FUNDAMENTALS: Domain Event. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Domain Event.
- Apply Domain Event in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Repository, Factory, Strategy, Adapter, Observer, Facade, Dependency Injection.
Repository
DESIGN PATTERNS: Repository. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Repository.
- Apply Repository in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Factory
DESIGN PATTERNS: Factory. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Factory.
- Apply Factory in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Strategy
DESIGN PATTERNS: Strategy. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Strategy.
- Apply Strategy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Adapter
DESIGN PATTERNS: Adapter. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Adapter.
- Apply Adapter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Observer
DESIGN PATTERNS: Observer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Observer.
- Apply Observer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Facade
DESIGN PATTERNS: Facade. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Facade.
- Apply Facade in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency Injection
DESIGN PATTERNS: Dependency Injection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Dependency Injection.
- Apply Dependency Injection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Low-Level Design.
Low-Level Design
Problems:; 1. Parking Lot; 2. Notification System; 3. Payment Service; 4. Task Scheduler; 5. Rate Limiter; 6. Booking System; 7. Chat Service; 8. Order System
- Explain the core concepts and architecture of Low-Level Design.
- Apply Low-Level Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: URL Shortener, Payment Backend, Chat Backend, Notification Platform, Order Management System, Ticket Booking, File Processing Platform, Learning Platform and 2 more topics.
URL Shortener
SYSTEM DESIGN: URL Shortener. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of URL Shortener.
- Apply URL Shortener in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Payment Backend
SYSTEM DESIGN: Payment Backend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Payment Backend.
- Apply Payment Backend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Chat Backend
SYSTEM DESIGN: Chat Backend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Chat Backend.
- Apply Chat Backend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notification Platform
SYSTEM DESIGN: Notification Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Notification Platform.
- Apply Notification Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Order Management System
SYSTEM DESIGN: Order Management System. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Order Management System.
- Apply Order Management System in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Ticket Booking
SYSTEM DESIGN: Ticket Booking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Ticket Booking.
- Apply Ticket Booking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
File Processing Platform
SYSTEM DESIGN: File Processing Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of File Processing Platform.
- Apply File Processing Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Learning Platform
SYSTEM DESIGN: Learning Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Learning Platform.
- Apply Learning Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Multi-Tenant SaaS
SYSTEM DESIGN: Multi-Tenant SaaS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Multi-Tenant SaaS.
- Apply Multi-Tenant SaaS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Event Processing System
SYSTEM DESIGN: Event Processing System. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Event Processing System.
- Apply Event Processing System in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Schema, Query, Mutation, Resolver, N+1 concerns.
Schema
GRAPHQL AWARENESS: Schema. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Schema.
- Apply Schema in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Query
GRAPHQL AWARENESS: Query. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Query.
- Apply Query in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mutation
GRAPHQL AWARENESS: Mutation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Mutation.
- Apply Mutation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Resolver
GRAPHQL AWARENESS: Resolver. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Resolver.
- Apply Resolver in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
N+1 concerns
GRAPHQL AWARENESS: N+1 concerns. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of N+1 concerns.
- Apply N+1 concerns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Protobuf concepts, RPC, Service contracts, Internal service communication.
Protobuf concepts
gRPC AWARENESS: Protobuf concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Protobuf concepts.
- Apply Protobuf concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RPC
gRPC AWARENESS: RPC. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of RPC.
- Apply RPC in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Service contracts
gRPC AWARENESS: Service contracts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Service contracts.
- Apply Service contracts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Internal service communication
gRPC AWARENESS: Internal service communication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Internal service communication.
- Apply Internal service communication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Api Gateway Pattern.
Api Gateway Pattern
Understand routing and cross-cutting concerns.
- Explain the core concepts and architecture of Api Gateway Pattern.
- Apply Api Gateway Pattern in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Serverless Architecture.
Serverless Architecture
Architecture:; API Gateway; Lambda; DynamoDB/RDS; SQS; Teach when serverless is appropriate and when it is not.
- Explain the core concepts and architecture of Serverless Architecture.
- Apply Serverless Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: LLM API calls, Streaming, Structured output, Tool-call concepts, Embeddings, RAG awareness, Authentication, Rate limiting and 2 more topics.
LLM API calls
AI BACKEND INTEGRATION: LLM API calls. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of LLM API calls.
- Apply LLM API calls in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streaming
AI BACKEND INTEGRATION: Streaming. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Streaming.
- Apply Streaming in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Structured output
AI BACKEND INTEGRATION: Structured output. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Structured output.
- Apply Structured output in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tool-call concepts
AI BACKEND INTEGRATION: Tool-call concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Tool-call concepts.
- Apply Tool-call concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Embeddings
AI BACKEND INTEGRATION: Embeddings. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Embeddings.
- Apply Embeddings in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RAG awareness
AI BACKEND INTEGRATION: RAG awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of RAG awareness.
- Apply RAG awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication
AI BACKEND INTEGRATION: Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Authentication.
- Apply Authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limiting
AI BACKEND INTEGRATION: Rate limiting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Rate limiting.
- Apply Rate limiting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logging
AI BACKEND INTEGRATION: Logging. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Logging.
- Apply Logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Usage tracking
AI BACKEND INTEGRATION: Usage tracking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Usage tracking.
- Apply Usage tracking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Prompt injection awareness, Unauthorized retrieval, API keys, Quotas, Output validation, Cost limits.
Prompt injection awareness
AI SECURITY: Prompt injection awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Prompt injection awareness.
- Apply Prompt injection awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unauthorized retrieval
AI SECURITY: Unauthorized retrieval. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Unauthorized retrieval.
- Apply Unauthorized retrieval in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API keys
AI SECURITY: API keys. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of API keys.
- Apply API keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Quotas
AI SECURITY: Quotas. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Quotas.
- Apply Quotas in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Output validation
AI SECURITY: Output validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Output validation.
- Apply Output validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cost limits
AI SECURITY: Cost limits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security, reliability and production considerations.
- Explain the core concepts and architecture of Cost limits.
- Apply Cost limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
26 Hands-On Production Capstones & Microservices
Build, deploy, and showcase real-world enterprise architectures on GitHub to prove your production engineering readiness:
Enterprise E-Commerce Microservices & Event-Driven Streaming Platform
Architected with Spring Boot 3.3, Apache Kafka event streams, Redis distributed caching, React 19 UI, and PostgreSQL. Features distributed ACID transaction sagas, payment webhook handling, dynamic inventory locking, and Dockerized Kubernetes deployment.
High-Throughput Banking & Core Transaction Engine
Concurrent multithreaded financial transaction ledger with ACID compliance, optimistic row locking, idempotent payment endpoints, and audit logging.
Real-Time Logistics & Fleet Tracking Service
Bi-directional live vehicle telemetry dashboard processing 10,000+ geo-coordinate events/sec with live map rendering and ETA calculations.
Multi-Tenant SaaS Subscription & Webhook Gateway
Multi-tenant automated billing engine with webhook signature verification, dynamic token bucket rate-limiting, and tenant data isolation schemas.
Distributed URL Shortener & Analytics System (Bitly Scale)
Low-latency URL redirection engine with distributed ID generation (Snowflake), sub-5ms Redis caching, and real-time click analytics.
Automated Cloud DevOps CI/CD Pipeline on AWS
Production containerization pipeline with automated testing, sonar code quality gates, container image vulnerability scanning, and zero-downtime rolling deploys.
AI-Powered Code Reviewer & Assessment Engine
Automated coding interview evaluator that parses Java AST trees, detects algorithmic time complexity, and simulates 1-on-1 voice technical interview feedback.
MockAttempt Academy vs. Traditional Bootcamps & Self-Study
Transparent side-by-side comparison of daily schedule, duration, curriculum, and placement support:
| Feature & Deliverables | MockAttempt Fast-Track Track | Expensive Bootcamps | Self-Study / YouTube |
|---|---|---|---|
| Live Weekend Schedule | Sat & Sun (4 Hours / Day) | 1 - 1.5 Hours / Day | Self-Paced / Inconsistent |
| Duration to Placement Readiness | 4 Months (16 Weeks Weekend) | 6 - 9 Months | 12+ Months (Uncertain) |
| Candidate Placement Guarantee | Unlimited Drives until Placed (or Full Refund) | Limited to 3-6 Months only | None (Apply blindly) |
| Topic Mock Tests & AI Interviews | Integrated for Every Topic (580+ Rounds) | End of Course Only | None |
| Tuition Fee | ₹49,999 ₹98,999 | ₹1,20,000 - ₹2,50,000 | Free (No Mentorship/Jobs) |
Institutional Course Assurances & 100% Placement Policy
100% Job Placement Guarantee
Our placement team arranges unlimited corporate interview drives across 1,050+ hiring partners until you receive an official offer letter. If unplaced, 100% of your tuition fee is refunded.
1-on-1 Expert Faculty Mentorship
Every cohort is taught live by seasoned lead architects from Tier-1 product companies with daily live coding and supervised code reviews.
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