Java Backend 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 Java Backend 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
68 Modules • 589 Deep-Dive Topics • 589 Integrated Topic Mock Tests & AI Interviews
Modules 1–4: Software Development Fundamentals, Programming Logic, Problem Solving, Complexity Awareness.
Software Development Fundamentals
Topics:; Source code; compiler; runtime; processes; memory; libraries; dependencies
- Explain the core concepts and architecture of Software Development Fundamentals.
- Apply Software Development Fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Programming Logic
Variables; conditions; loops; functions; arrays; algorithms
- Explain the core concepts and architecture of Programming Logic.
- Apply Programming Logic in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Problem Solving
Framework:; Understand → Break Down → Design → Code → Test → Improve
- Explain the core concepts and architecture of Problem Solving.
- Apply Problem Solving in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Complexity Awareness
Introduction to:; time complexity; space complexity; Big-O; Assessment; 30 questions; =====================================
- Explain the core concepts and architecture of Complexity Awareness.
- Apply Complexity Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 5–18: Java Platform, Java Program Structure, Variables, Primitive Types, Reference Types, Operators, Type Conversion, Input / Output and 6 more topics.
Java Platform
Understand:; JVM; JDK; bytecode; portability
- Explain the core concepts and architecture of Java Platform.
- Apply Java Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Java Program Structure
Core concepts, implementation patterns, engineering trade-offs and production considerations for Java Program Structure.
- Explain the core concepts and architecture of Java Program Structure.
- Apply Java Program Structure in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Variables
Core concepts, implementation patterns, engineering trade-offs and production considerations for Variables.
- 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.
Primitive Types
Core concepts, implementation patterns, engineering trade-offs and production considerations for Primitive Types.
- Explain the core concepts and architecture of Primitive Types.
- Apply Primitive Types in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reference Types
Core concepts, implementation patterns, engineering trade-offs and production considerations for Reference Types.
- Explain the core concepts and architecture of Reference Types.
- Apply Reference 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.
Type Conversion
Core concepts, implementation patterns, engineering trade-offs and production considerations for Type Conversion.
- Explain the core concepts and architecture of Type Conversion.
- Apply Type Conversion in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Input / Output
Core concepts, implementation patterns, engineering trade-offs and production considerations for Input / Output.
- Explain the core concepts and architecture of Input / Output.
- Apply Input / Output in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Conditions
if; else; switch
- 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
for; while; do-while
- 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.
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.
Methods
Core concepts, implementation patterns, engineering trade-offs and production considerations for Methods.
- Explain the core concepts and architecture of Methods.
- Apply Methods in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scope
Core concepts, implementation patterns, engineering trade-offs and production considerations for Scope.
- Explain the core concepts and architecture of Scope.
- Apply Scope in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Recursion
Coding Lab; 35 Java foundation problems; =====================================
- Explain the core concepts and architecture of Recursion.
- Apply Recursion in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 19–31: Classes, Objects, Constructors, Encapsulation, Inheritance, Polymorphism, Abstraction, Interfaces and 5 more topics.
Classes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Classes.
- 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.
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.
Constructors
Core concepts, implementation patterns, engineering trade-offs and production considerations for Constructors.
- Explain the core concepts and architecture of Constructors.
- Apply Constructors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Encapsulation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Encapsulation.
- Explain the core concepts and architecture of Encapsulation.
- Apply Encapsulation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Inheritance
Core concepts, implementation patterns, engineering trade-offs and production considerations for Inheritance.
- 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.
Polymorphism
Core concepts, implementation patterns, engineering trade-offs and production considerations for Polymorphism.
- Explain the core concepts and architecture of Polymorphism.
- Apply Polymorphism in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Abstraction
Core concepts, implementation patterns, engineering trade-offs and production considerations for Abstraction.
- Explain the core concepts and architecture of Abstraction.
- Apply Abstraction in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Interfaces
Core concepts, implementation patterns, engineering trade-offs and production considerations for Interfaces.
- 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.
Abstract Classes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Abstract Classes.
- Explain the core concepts and architecture of Abstract Classes.
- Apply Abstract Classes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Composition
Core concepts, implementation patterns, engineering trade-offs and production considerations for Composition.
- 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.
Association
Core concepts, implementation patterns, engineering trade-offs and production considerations for Association.
- Explain the core concepts and architecture of Association.
- Apply Association in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Immutability
Core concepts, implementation patterns, engineering trade-offs and production considerations for Immutability.
- Explain the core concepts and architecture of Immutability.
- Apply Immutability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SOLID Fundamentals
Cover:; Single Responsibility; Open/Closed; Liskov Substitution; Interface Segregation; Dependency Inversion; Major Lab; Banking Domain Model; Implement:; Customer; Account; SavingsAccount; CurrentAccount; Transaction; TransferService; =====================================
- Explain the core concepts and architecture of SOLID Fundamentals.
- Apply SOLID Fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 32–38: Object, Object Identity vs Equality, Immutable Objects, Records, Enums, Wrapper Classes, Autoboxing.
Object
Understand:; equals(); hashCode(); toString()
- Explain the core concepts and architecture of Object.
- Apply Object in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Object Identity vs Equality
Core concepts, implementation patterns, engineering trade-offs and production considerations for Object Identity vs Equality.
- Explain the core concepts and architecture of Object Identity vs Equality.
- Apply Object Identity vs Equality in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Immutable Objects
Core concepts, implementation patterns, engineering trade-offs and production considerations for Immutable Objects.
- Explain the core concepts and architecture of Immutable Objects.
- Apply Immutable Objects in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Records
Core concepts, implementation patterns, engineering trade-offs and production considerations for Records.
- Explain the core concepts and architecture of Records.
- Apply Records in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Enums
Core concepts, implementation patterns, engineering trade-offs and production considerations for Enums.
- Explain the core concepts and architecture of Enums.
- Apply Enums in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Wrapper Classes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Wrapper Classes.
- Explain the core concepts and architecture of Wrapper Classes.
- Apply Wrapper Classes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Autoboxing
=====================================
- Explain the core concepts and architecture of Autoboxing.
- Apply Autoboxing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 39–45: String, String Pool, String Immutability, StringBuilder, StringBuffer, Regular Expressions, Common String Interview Problems.
String
Core concepts, implementation patterns, engineering trade-offs and production considerations for String.
- Explain the core concepts and architecture of String.
- Apply String in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
String Pool
Core concepts, implementation patterns, engineering trade-offs and production considerations for String Pool.
- Explain the core concepts and architecture of String Pool.
- Apply String Pool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
String Immutability
Core concepts, implementation patterns, engineering trade-offs and production considerations for String Immutability.
- Explain the core concepts and architecture of String Immutability.
- Apply String Immutability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
StringBuilder
Core concepts, implementation patterns, engineering trade-offs and production considerations for StringBuilder.
- Explain the core concepts and architecture of StringBuilder.
- Apply StringBuilder in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
StringBuffer
Core concepts, implementation patterns, engineering trade-offs and production considerations for StringBuffer.
- Explain the core concepts and architecture of StringBuffer.
- Apply StringBuffer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Regular Expressions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Regular Expressions.
- Explain the core concepts and architecture of Regular Expressions.
- Apply Regular Expressions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Common String Interview Problems
=====================================
- Explain the core concepts and architecture of Common String Interview Problems.
- Apply Common String Interview Problems in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 46–53: Exception Hierarchy, Checked Exceptions, Runtime Exceptions, try/catch/finally, throw / throws, Custom Exceptions, Exception Translation, Error Handling Principles.
Exception Hierarchy
Core concepts, implementation patterns, engineering trade-offs and production considerations for Exception Hierarchy.
- Explain the core concepts and architecture of Exception Hierarchy.
- Apply Exception Hierarchy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Checked Exceptions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Checked Exceptions.
- Explain the core concepts and architecture of Checked Exceptions.
- Apply Checked Exceptions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Runtime Exceptions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Runtime Exceptions.
- Explain the core concepts and architecture of Runtime Exceptions.
- Apply Runtime Exceptions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
try/catch/finally
Core concepts, implementation patterns, engineering trade-offs and production considerations for try/catch/finally.
- Explain the core concepts and architecture of try/catch/finally.
- Apply try/catch/finally in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
throw / throws
Core concepts, implementation patterns, engineering trade-offs and production considerations for throw / throws.
- Explain the core concepts and architecture of throw / throws.
- Apply throw / throws in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Custom Exceptions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Custom Exceptions.
- Explain the core concepts and architecture of Custom Exceptions.
- Apply Custom Exceptions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exception Translation
Example:; Database exception; Repository-level exception; Business exception; HTTP error
- Explain the core concepts and architecture of Exception Translation.
- Apply Exception Translation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error Handling Principles
Avoid:; swallowing exceptions; logging everything repeatedly; exposing stack traces to clients; =====================================
- Explain the core concepts and architecture of Error Handling Principles.
- Apply Error Handling Principles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 54–69: Collection Architecture, ArrayList, LinkedList, HashSet, TreeSet, HashMap, LinkedHashMap, TreeMap and 8 more topics.
Collection Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for Collection Architecture.
- Explain the core concepts and architecture of Collection Architecture.
- Apply Collection Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ArrayList
Core concepts, implementation patterns, engineering trade-offs and production considerations for ArrayList.
- Explain the core concepts and architecture of ArrayList.
- Apply ArrayList in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
LinkedList
Core concepts, implementation patterns, engineering trade-offs and production considerations for LinkedList.
- Explain the core concepts and architecture of LinkedList.
- Apply LinkedList in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HashSet
Core concepts, implementation patterns, engineering trade-offs and production considerations for HashSet.
- Explain the core concepts and architecture of HashSet.
- Apply HashSet in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TreeSet
Core concepts, implementation patterns, engineering trade-offs and production considerations for TreeSet.
- Explain the core concepts and architecture of TreeSet.
- Apply TreeSet in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HashMap
Core concepts, implementation patterns, engineering trade-offs and production considerations for HashMap.
- Explain the core concepts and architecture of HashMap.
- Apply HashMap in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
LinkedHashMap
Core concepts, implementation patterns, engineering trade-offs and production considerations for LinkedHashMap.
- Explain the core concepts and architecture of LinkedHashMap.
- Apply LinkedHashMap in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TreeMap
Core concepts, implementation patterns, engineering trade-offs and production considerations for TreeMap.
- Explain the core concepts and architecture of TreeMap.
- Apply TreeMap in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queue
Core concepts, implementation patterns, engineering trade-offs and production considerations for Queue.
- 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.
PriorityQueue
Core concepts, implementation patterns, engineering trade-offs and production considerations for PriorityQueue.
- Explain the core concepts and architecture of PriorityQueue.
- Apply PriorityQueue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Deque
Core concepts, implementation patterns, engineering trade-offs and production considerations for Deque.
- Explain the core concepts and architecture of Deque.
- Apply Deque in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Iterator
Core concepts, implementation patterns, engineering trade-offs and production considerations for Iterator.
- Explain the core concepts and architecture of Iterator.
- Apply Iterator in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Comparable
Core concepts, implementation patterns, engineering trade-offs and production considerations for Comparable.
- Explain the core concepts and architecture of Comparable.
- Apply Comparable in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Comparator
Core concepts, implementation patterns, engineering trade-offs and production considerations for Comparator.
- Explain the core concepts and architecture of Comparator.
- Apply Comparator in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HashMap Internals
Cover:; hash; bucket; collision; equals/hashCode; resizing; load factor concepts
- Explain the core concepts and architecture of HashMap Internals.
- Apply HashMap Internals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Concurrent Collections
=====================================
- Explain the core concepts and architecture of Concurrent Collections.
- Apply Concurrent Collections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 70–74: Generic Classes, Generic Methods, Bounds, Wildcards, PECS Concept.
Generic Classes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Generic Classes.
- Explain the core concepts and architecture of Generic Classes.
- Apply Generic Classes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Generic Methods
Core concepts, implementation patterns, engineering trade-offs and production considerations for Generic Methods.
- Explain the core concepts and architecture of Generic Methods.
- Apply Generic Methods in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Bounds
Core concepts, implementation patterns, engineering trade-offs and production considerations for Bounds.
- Explain the core concepts and architecture of Bounds.
- Apply Bounds in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Wildcards
Core concepts, implementation patterns, engineering trade-offs and production considerations for Wildcards.
- Explain the core concepts and architecture of Wildcards.
- Apply Wildcards in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PECS Concept
Producer Extends / Consumer Super.; =====================================
- Explain the core concepts and architecture of PECS Concept.
- Apply PECS Concept in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 75–81: Functional Interfaces, Lambda Expressions, Predicate, Function, Consumer, Supplier, Method References.
Functional Interfaces
Core concepts, implementation patterns, engineering trade-offs and production considerations for Functional Interfaces.
- Explain the core concepts and architecture of Functional Interfaces.
- Apply Functional Interfaces in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lambda Expressions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Lambda Expressions.
- Explain the core concepts and architecture of Lambda Expressions.
- Apply Lambda Expressions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Predicate
Core concepts, implementation patterns, engineering trade-offs and production considerations for Predicate.
- Explain the core concepts and architecture of Predicate.
- Apply Predicate in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Function
Core concepts, implementation patterns, engineering trade-offs and production considerations for Function.
- Explain the core concepts and architecture of Function.
- Apply Function in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consumer
Core concepts, implementation patterns, engineering trade-offs and production considerations for Consumer.
- 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.
Supplier
Core concepts, implementation patterns, engineering trade-offs and production considerations for Supplier.
- Explain the core concepts and architecture of Supplier.
- Apply Supplier in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Method References
=====================================
- Explain the core concepts and architecture of Method References.
- Apply Method References in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 82–91: Stream Fundamentals, map(), flatMap(), filter(), reduce(), collect(), groupingBy(), partitioningBy() and 2 more topics.
Stream Fundamentals
Core concepts, implementation patterns, engineering trade-offs and production considerations for Stream Fundamentals.
- Explain the core concepts and architecture of Stream Fundamentals.
- Apply Stream Fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
map()
Core concepts, implementation patterns, engineering trade-offs and production considerations for map().
- Explain the core concepts and architecture of map().
- Apply map() in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
flatMap()
Core concepts, implementation patterns, engineering trade-offs and production considerations for flatMap().
- Explain the core concepts and architecture of flatMap().
- Apply flatMap() in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
filter()
Core concepts, implementation patterns, engineering trade-offs and production considerations for filter().
- Explain the core concepts and architecture of filter().
- Apply filter() in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
reduce()
Core concepts, implementation patterns, engineering trade-offs and production considerations for reduce().
- Explain the core concepts and architecture of reduce().
- Apply reduce() in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
collect()
Core concepts, implementation patterns, engineering trade-offs and production considerations for collect().
- Explain the core concepts and architecture of collect().
- Apply collect() in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
groupingBy()
Core concepts, implementation patterns, engineering trade-offs and production considerations for groupingBy().
- Explain the core concepts and architecture of groupingBy().
- Apply groupingBy() in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
partitioningBy()
Core concepts, implementation patterns, engineering trade-offs and production considerations for partitioningBy().
- Explain the core concepts and architecture of partitioningBy().
- Apply partitioningBy() in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sorting
Core concepts, implementation patterns, engineering trade-offs and production considerations for Sorting.
- Explain the core concepts and architecture of Sorting.
- Apply Sorting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Parallel Streams
Understand when not to use them.; Lab; Analyze a large transaction dataset using Streams.; =====================================
- Explain the core concepts and architecture of Parallel Streams.
- Apply Parallel Streams in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 92–100: var, Records, Sealed Classes, Pattern Matching, Modern Switch, Text Blocks, Optional, Date/Time API and 1 more topics.
var
Core concepts, implementation patterns, engineering trade-offs and production considerations for var.
- Explain the core concepts and architecture of var.
- Apply var in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Records
Core concepts, implementation patterns, engineering trade-offs and production considerations for Records.
- Explain the core concepts and architecture of Records.
- Apply Records in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sealed Classes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Sealed Classes.
- Explain the core concepts and architecture of Sealed Classes.
- Apply Sealed Classes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pattern Matching
Core concepts, implementation patterns, engineering trade-offs and production considerations for Pattern Matching.
- Explain the core concepts and architecture of Pattern Matching.
- Apply Pattern Matching in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modern Switch
Core concepts, implementation patterns, engineering trade-offs and production considerations for Modern Switch.
- Explain the core concepts and architecture of Modern Switch.
- Apply Modern Switch in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Text Blocks
Core concepts, implementation patterns, engineering trade-offs and production considerations for Text Blocks.
- Explain the core concepts and architecture of Text Blocks.
- Apply Text Blocks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Optional
Core concepts, implementation patterns, engineering trade-offs and production considerations for Optional.
- Explain the core concepts and architecture of Optional.
- Apply Optional in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Date/Time API
Core concepts, implementation patterns, engineering trade-offs and production considerations for Date/Time API.
- Explain the core concepts and architecture of Date/Time API.
- Apply Date/Time API in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Virtual Threads
Use cases:; high-concurrency blocking I/O; request processing; Also explain limitations and benchmarking.; =====================================
- Explain the core concepts and architecture of Virtual Threads.
- Apply Virtual Threads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 101–118: Process vs Thread, Thread Lifecycle, Runnable, Callable, Synchronization, Race Conditions, Visibility, volatile and 10 more topics.
Process vs Thread
Core concepts, implementation patterns, engineering trade-offs and production considerations for Process vs Thread.
- Explain the core concepts and architecture of Process vs Thread.
- Apply Process vs Thread in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Thread Lifecycle
Core concepts, implementation patterns, engineering trade-offs and production considerations for Thread Lifecycle.
- Explain the core concepts and architecture of Thread Lifecycle.
- Apply Thread Lifecycle in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Runnable
Core concepts, implementation patterns, engineering trade-offs and production considerations for Runnable.
- Explain the core concepts and architecture of Runnable.
- Apply Runnable in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Callable
Core concepts, implementation patterns, engineering trade-offs and production considerations for Callable.
- Explain the core concepts and architecture of Callable.
- Apply Callable in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Synchronization
Core concepts, implementation patterns, engineering trade-offs and production considerations for Synchronization.
- Explain the core concepts and architecture of Synchronization.
- Apply Synchronization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Race Conditions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Race Conditions.
- Explain the core concepts and architecture of Race Conditions.
- Apply Race Conditions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Visibility
Core concepts, implementation patterns, engineering trade-offs and production considerations for Visibility.
- Explain the core concepts and architecture of Visibility.
- Apply Visibility in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
volatile
Core concepts, implementation patterns, engineering trade-offs and production considerations for volatile.
- Explain the core concepts and architecture of volatile.
- Apply volatile in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Locks
Core concepts, implementation patterns, engineering trade-offs and production considerations for Locks.
- 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.
Deadlocks
Core concepts, implementation patterns, engineering trade-offs and production considerations for Deadlocks.
- Explain the core concepts and architecture of Deadlocks.
- Apply Deadlocks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Atomic Classes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Atomic Classes.
- Explain the core concepts and architecture of Atomic Classes.
- Apply Atomic Classes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ExecutorService
Core concepts, implementation patterns, engineering trade-offs and production considerations for ExecutorService.
- Explain the core concepts and architecture of ExecutorService.
- Apply ExecutorService in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Thread Pools
Core concepts, implementation patterns, engineering trade-offs and production considerations for Thread Pools.
- Explain the core concepts and architecture of Thread Pools.
- Apply Thread Pools in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Future
Core concepts, implementation patterns, engineering trade-offs and production considerations for Future.
- Explain the core concepts and architecture of Future.
- Apply Future in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CompletableFuture
Core concepts, implementation patterns, engineering trade-offs and production considerations for CompletableFuture.
- Explain the core concepts and architecture of CompletableFuture.
- Apply CompletableFuture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ConcurrentHashMap
Core concepts, implementation patterns, engineering trade-offs and production considerations for ConcurrentHashMap.
- Explain the core concepts and architecture of ConcurrentHashMap.
- Apply ConcurrentHashMap in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
BlockingQueue
Core concepts, implementation patterns, engineering trade-offs and production considerations for BlockingQueue.
- Explain the core concepts and architecture of BlockingQueue.
- Apply BlockingQueue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Virtual Threads
Major Coding Project; Concurrent Order Processing Engine; Requirements:; accept orders; validate; process concurrently; record failures; avoid duplicate processing; collect execution metrics; =====================================
- Explain the core concepts and architecture of Virtual Threads.
- Apply Virtual Threads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 119–135: JVM Architecture, Class Loading, Heap, Stack, Metaspace, Object Allocation, Garbage Collection, GC Algorithms Concepts and 9 more topics.
JVM Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for JVM Architecture.
- Explain the core concepts and architecture of JVM Architecture.
- Apply JVM Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Class Loading
Core concepts, implementation patterns, engineering trade-offs and production considerations for Class Loading.
- Explain the core concepts and architecture of Class Loading.
- Apply Class Loading in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Heap
Core concepts, implementation patterns, engineering trade-offs and production considerations for Heap.
- 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.
Stack
Core concepts, implementation patterns, engineering trade-offs and production considerations for Stack.
- Explain the core concepts and architecture of Stack.
- Apply Stack in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Metaspace
Core concepts, implementation patterns, engineering trade-offs and production considerations for Metaspace.
- Explain the core concepts and architecture of Metaspace.
- Apply Metaspace in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Object Allocation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Object Allocation.
- Explain the core concepts and architecture of Object Allocation.
- Apply Object Allocation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Garbage Collection
Core concepts, implementation patterns, engineering trade-offs and production considerations for Garbage Collection.
- Explain the core concepts and architecture of Garbage Collection.
- Apply Garbage Collection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
GC Algorithms Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for GC Algorithms Concepts.
- Explain the core concepts and architecture of GC Algorithms Concepts.
- Apply GC Algorithms Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Stop-The-World Events
Core concepts, implementation patterns, engineering trade-offs and production considerations for Stop-The-World Events.
- Explain the core concepts and architecture of Stop-The-World Events.
- Apply Stop-The-World Events in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Memory Leaks
Core concepts, implementation patterns, engineering trade-offs and production considerations for Memory Leaks.
- Explain the core concepts and architecture of Memory Leaks.
- Apply Memory Leaks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
OutOfMemoryError
Core concepts, implementation patterns, engineering trade-offs and production considerations for OutOfMemoryError.
- Explain the core concepts and architecture of OutOfMemoryError.
- Apply OutOfMemoryError in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
StackOverflowError
Core concepts, implementation patterns, engineering trade-offs and production considerations for StackOverflowError.
- Explain the core concepts and architecture of StackOverflowError.
- Apply StackOverflowError in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Thread Dumps
Core concepts, implementation patterns, engineering trade-offs and production considerations for Thread Dumps.
- Explain the core concepts and architecture of Thread Dumps.
- Apply Thread Dumps in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Heap Dumps
Core concepts, implementation patterns, engineering trade-offs and production considerations for Heap Dumps.
- Explain the core concepts and architecture of Heap Dumps.
- Apply Heap Dumps in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JVM Options
Core concepts, implementation patterns, engineering trade-offs and production considerations for JVM Options.
- Explain the core concepts and architecture of JVM Options.
- Apply JVM Options in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Profiling Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Profiling Concepts.
- Explain the core concepts and architecture of Profiling Concepts.
- Apply Profiling Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JFR / diagnostic tooling awareness
=====================================
- Explain the core concepts and architecture of JFR / diagnostic tooling awareness.
- Apply JFR / diagnostic tooling awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 136–144: Maven, pom.xml, Dependency Management, Plugins, Maven Lifecycle, Profiles, Multi-Module Builds, Dependency Conflicts and 1 more topics.
Maven
Core concepts, implementation patterns, engineering trade-offs and production considerations for Maven.
- Explain the core concepts and architecture of Maven.
- Apply Maven in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
pom.xml
Core concepts, implementation patterns, engineering trade-offs and production considerations for pom.xml.
- Explain the core concepts and architecture of pom.xml.
- Apply pom.xml in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency Management
Core concepts, implementation patterns, engineering trade-offs and production considerations for Dependency Management.
- Explain the core concepts and architecture of Dependency Management.
- Apply Dependency Management in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Plugins
Core concepts, implementation patterns, engineering trade-offs and production considerations for Plugins.
- Explain the core concepts and architecture of Plugins.
- Apply Plugins in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Maven Lifecycle
Core concepts, implementation patterns, engineering trade-offs and production considerations for Maven Lifecycle.
- Explain the core concepts and architecture of Maven Lifecycle.
- Apply Maven Lifecycle in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Profiles
Core concepts, implementation patterns, engineering trade-offs and production considerations for Profiles.
- Explain the core concepts and architecture of Profiles.
- Apply Profiles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Multi-Module Builds
Core concepts, implementation patterns, engineering trade-offs and production considerations for Multi-Module Builds.
- Explain the core concepts and architecture of Multi-Module Builds.
- Apply Multi-Module Builds in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency Conflicts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Dependency Conflicts.
- Explain the core concepts and architecture of Dependency Conflicts.
- Apply Dependency Conflicts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Gradle Awareness
=====================================
- Explain the core concepts and architecture of Gradle Awareness.
- Apply Gradle Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 145–153: Repository, Commit, Branch, Merge, Rebase Concepts, Conflict Resolution, Pull Requests, Code Reviews and 1 more topics.
Repository
Core concepts, implementation patterns, engineering trade-offs and production considerations for Repository.
- 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.
Commit
Core concepts, implementation patterns, engineering trade-offs and production considerations for Commit.
- Explain the core concepts and architecture of Commit.
- Apply Commit in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Branch
Core concepts, implementation patterns, engineering trade-offs and production considerations for Branch.
- Explain the core concepts and architecture of Branch.
- Apply Branch in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Merge
Core concepts, implementation patterns, engineering trade-offs and production considerations for Merge.
- Explain the core concepts and architecture of Merge.
- Apply Merge in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rebase Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rebase Concepts.
- Explain the core concepts and architecture of Rebase Concepts.
- Apply Rebase Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Conflict Resolution
Core concepts, implementation patterns, engineering trade-offs and production considerations for Conflict Resolution.
- Explain the core concepts and architecture of Conflict Resolution.
- Apply Conflict Resolution in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pull Requests
Core concepts, implementation patterns, engineering trade-offs and production considerations for Pull Requests.
- Explain the core concepts and architecture of Pull Requests.
- Apply Pull Requests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Code Reviews
Core concepts, implementation patterns, engineering trade-offs and production considerations for Code Reviews.
- Explain the core concepts and architecture of Code Reviews.
- Apply Code Reviews in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Release Tags
=====================================
- Explain the core concepts and architecture of Release Tags.
- Apply Release Tags in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 154–161: Relational Model, Keys, Constraints, Normalization, Denormalization, Transactions, ACID, Isolation Levels.
Relational Model
Core concepts, implementation patterns, engineering trade-offs and production considerations for Relational Model.
- Explain the core concepts and architecture of Relational Model.
- Apply Relational Model in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Keys
Core concepts, implementation patterns, engineering trade-offs and production considerations for Keys.
- 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.
Constraints
Core concepts, implementation patterns, engineering trade-offs and production considerations for Constraints.
- 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.
Normalization
Core concepts, implementation patterns, engineering trade-offs and production considerations for Normalization.
- Explain the core concepts and architecture of Normalization.
- Apply Normalization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Denormalization
Core concepts, implementation patterns, engineering trade-offs and production considerations for Denormalization.
- Explain the core concepts and architecture of Denormalization.
- Apply Denormalization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Transactions.
- 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.
ACID
Core concepts, implementation patterns, engineering trade-offs and production considerations for ACID.
- 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 Levels
Cover:; Read Uncommitted; Read Committed; Repeatable Read; Serializable; Understand anomalies:; dirty reads; non-repeatable reads; phantom reads; =====================================
- Explain the core concepts and architecture of Isolation Levels.
- Apply Isolation Levels in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 162–173: CRUD SQL, Joins, Aggregation, Subqueries, CTEs, Window Functions, Indexes, Composite Indexes and 4 more topics.
CRUD SQL
Core concepts, implementation patterns, engineering trade-offs and production considerations for CRUD SQL.
- Explain the core concepts and architecture of CRUD SQL.
- Apply CRUD SQL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Joins
Core concepts, implementation patterns, engineering trade-offs and production considerations for Joins.
- 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.
Aggregation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Aggregation.
- Explain the core concepts and architecture of Aggregation.
- Apply Aggregation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Subqueries
Core concepts, implementation patterns, engineering trade-offs and production considerations for Subqueries.
- 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.
CTEs
Core concepts, implementation patterns, engineering trade-offs and production considerations for CTEs.
- Explain the core concepts and architecture of CTEs.
- Apply CTEs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Window Functions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Window Functions.
- 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.
Indexes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Indexes.
- 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.
Composite Indexes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Composite Indexes.
- Explain the core concepts and architecture of Composite Indexes.
- Apply Composite Indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Covering Index Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Covering Index Concepts.
- Explain the core concepts and architecture of Covering Index Concepts.
- Apply Covering Index Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Execution Plans
Core concepts, implementation patterns, engineering trade-offs and production considerations for Execution Plans.
- 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 Optimization
Core concepts, implementation patterns, engineering trade-offs and production considerations for Query Optimization.
- Explain the core concepts and architecture of Query Optimization.
- Apply Query Optimization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
Discuss:; OFFSET pagination; keyset/cursor pagination; SQL Assessment; 100 MCQs + 75 query problems; =====================================
- 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.
Modules 174–182: PostgreSQL Architecture Concepts, Schemas, Constraints, Index Types Awareness, JSON/JSONB Concepts, Transactions, Locks, Connection Management and 1 more topics.
PostgreSQL Architecture Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for PostgreSQL Architecture Concepts.
- Explain the core concepts and architecture of PostgreSQL Architecture Concepts.
- Apply PostgreSQL Architecture Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Schemas
Core concepts, implementation patterns, engineering trade-offs and production considerations for Schemas.
- 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.
Constraints
Core concepts, implementation patterns, engineering trade-offs and production considerations for Constraints.
- 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.
Index Types Awareness
Core concepts, implementation patterns, engineering trade-offs and production considerations for Index Types Awareness.
- Explain the core concepts and architecture of Index Types Awareness.
- Apply Index Types Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JSON/JSONB Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for JSON/JSONB Concepts.
- Explain the core concepts and architecture of JSON/JSONB Concepts.
- Apply JSON/JSONB Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Transactions.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Locks.
- 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.
Connection Management
Core concepts, implementation patterns, engineering trade-offs and production considerations for Connection Management.
- Explain the core concepts and architecture of Connection Management.
- Apply Connection Management in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Explain / Analyze Concepts
=====================================
- Explain the core concepts and architecture of Explain / Analyze Concepts.
- Apply Explain / Analyze Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 183–190: JDBC Architecture, Connections, PreparedStatement, ResultSet, SQL Injection Prevention, Transactions, Batch Updates, Connection Pooling.
JDBC Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for JDBC Architecture.
- Explain the core concepts and architecture of JDBC Architecture.
- Apply JDBC Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connections
Core concepts, implementation patterns, engineering trade-offs and production considerations for Connections.
- 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.
PreparedStatement
Core concepts, implementation patterns, engineering trade-offs and production considerations for PreparedStatement.
- Explain the core concepts and architecture of PreparedStatement.
- Apply PreparedStatement in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ResultSet
Core concepts, implementation patterns, engineering trade-offs and production considerations for ResultSet.
- Explain the core concepts and architecture of ResultSet.
- Apply ResultSet in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SQL Injection Prevention
Core concepts, implementation patterns, engineering trade-offs and production considerations for SQL Injection Prevention.
- Explain the core concepts and architecture of SQL Injection Prevention.
- Apply SQL Injection Prevention in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Transactions.
- 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.
Batch Updates
Core concepts, implementation patterns, engineering trade-offs and production considerations for Batch Updates.
- Explain the core concepts and architecture of Batch Updates.
- Apply Batch Updates in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection Pooling
=====================================
- 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.
Modules 191–201: HTTP, HTTPS, Request/Response, Methods, Headers, Status Codes, Content Negotiation, Caching Headers and 3 more topics.
HTTP
Core concepts, implementation patterns, engineering trade-offs and production considerations for HTTP.
- 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.
HTTPS
Core concepts, implementation patterns, engineering trade-offs and production considerations for HTTPS.
- Explain the core concepts and architecture of HTTPS.
- Apply HTTPS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Request/Response
Core concepts, implementation patterns, engineering trade-offs and production considerations for Request/Response.
- Explain the core concepts and architecture of Request/Response.
- Apply Request/Response in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Methods
Core concepts, implementation patterns, engineering trade-offs and production considerations for Methods.
- Explain the core concepts and architecture of Methods.
- Apply Methods in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Headers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Headers.
- 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.
Status Codes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Status Codes.
- 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.
Content Negotiation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Content Negotiation.
- Explain the core concepts and architecture of Content Negotiation.
- Apply Content Negotiation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Caching Headers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Caching Headers.
- Explain the core concepts and architecture of Caching Headers.
- Apply Caching Headers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cookies
Core concepts, implementation patterns, engineering trade-offs and production considerations for Cookies.
- Explain the core concepts and architecture of Cookies.
- Apply Cookies in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sessions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Sessions.
- 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.
TLS Concepts
=====================================
- Explain the core concepts and architecture of TLS Concepts.
- Apply TLS Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 202–219: REST, Resource Modeling, HTTP Semantics, Request DTO, Response DTO, Validation, Pagination, Filtering and 10 more topics.
REST
Core concepts, implementation patterns, engineering trade-offs and production considerations for REST.
- 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.
Resource Modeling
Bad:; /getEmployee; Better:; GET /employees/{id}
- Explain the core concepts and architecture of Resource Modeling.
- Apply Resource Modeling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HTTP Semantics
Core concepts, implementation patterns, engineering trade-offs and production considerations for HTTP Semantics.
- 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.
Request DTO
Core concepts, implementation patterns, engineering trade-offs and production considerations for Request DTO.
- Explain the core concepts and architecture of Request DTO.
- Apply Request DTO in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Response DTO
Core concepts, implementation patterns, engineering trade-offs and production considerations for Response DTO.
- Explain the core concepts and architecture of Response DTO.
- Apply Response DTO in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Validation.
- 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.
Pagination
Core concepts, implementation patterns, engineering trade-offs and production considerations for Pagination.
- 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.
Filtering
Core concepts, implementation patterns, engineering trade-offs and production considerations for Filtering.
- Explain the core concepts and architecture of Filtering.
- Apply Filtering in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sorting
Core concepts, implementation patterns, engineering trade-offs and production considerations for Sorting.
- Explain the core concepts and architecture of Sorting.
- Apply Sorting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Search
Core concepts, implementation patterns, engineering trade-offs and production considerations for Search.
- 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.
API Versioning
Core concepts, implementation patterns, engineering trade-offs and production considerations for API Versioning.
- 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.
Idempotency
Critical for:; payments; order creation; retries
- 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.
Idempotency Keys
Core concepts, implementation patterns, engineering trade-offs and production considerations for Idempotency Keys.
- Explain the core concepts and architecture of Idempotency Keys.
- Apply Idempotency Keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error Response Design
Core concepts, implementation patterns, engineering trade-offs and production considerations for Error Response Design.
- Explain the core concepts and architecture of Error Response Design.
- Apply Error Response Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Problem Details Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Problem Details Concepts.
- Explain the core concepts and architecture of Problem Details Concepts.
- Apply Problem Details Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API Compatibility
Core concepts, implementation patterns, engineering trade-offs and production considerations for API Compatibility.
- Explain the core concepts and architecture of API Compatibility.
- Apply API Compatibility in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
OpenAPI
Core concepts, implementation patterns, engineering trade-offs and production considerations for OpenAPI.
- 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.
Swagger
=====================================
- Explain the core concepts and architecture of Swagger.
- Apply Swagger in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 220–228: IoC, Dependency Injection, Beans, Component Scanning, Configuration, Bean Lifecycle, Profiles, Properties and 1 more topics.
IoC
Core concepts, implementation patterns, engineering trade-offs and production considerations for IoC.
- Explain the core concepts and architecture of IoC.
- Apply IoC in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency Injection
Core concepts, implementation patterns, engineering trade-offs and production considerations for Dependency Injection.
- 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.
Beans
Core concepts, implementation patterns, engineering trade-offs and production considerations for Beans.
- Explain the core concepts and architecture of Beans.
- Apply Beans in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Component Scanning
Core concepts, implementation patterns, engineering trade-offs and production considerations for Component Scanning.
- Explain the core concepts and architecture of Component Scanning.
- Apply Component Scanning in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Configuration
Core concepts, implementation patterns, engineering trade-offs and production considerations for Configuration.
- Explain the core concepts and architecture of Configuration.
- Apply Configuration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Bean Lifecycle
Core concepts, implementation patterns, engineering trade-offs and production considerations for Bean Lifecycle.
- Explain the core concepts and architecture of Bean Lifecycle.
- Apply Bean Lifecycle in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Profiles
Core concepts, implementation patterns, engineering trade-offs and production considerations for Profiles.
- Explain the core concepts and architecture of Profiles.
- Apply Profiles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Properties
Core concepts, implementation patterns, engineering trade-offs and production considerations for Properties.
- Explain the core concepts and architecture of Properties.
- Apply Properties in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
=====================================
- 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.
Modules 229–241: Boot Architecture, Starters, Auto Configuration, application.properties, YAML, Configuration Properties, Profiles, External Configuration and 5 more topics.
Boot Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for Boot Architecture.
- Explain the core concepts and architecture of Boot Architecture.
- Apply Boot Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Starters
Core concepts, implementation patterns, engineering trade-offs and production considerations for Starters.
- Explain the core concepts and architecture of Starters.
- Apply Starters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Auto Configuration
Core concepts, implementation patterns, engineering trade-offs and production considerations for Auto Configuration.
- Explain the core concepts and architecture of Auto Configuration.
- Apply Auto Configuration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
application.properties
Core concepts, implementation patterns, engineering trade-offs and production considerations for application.properties.
- Explain the core concepts and architecture of application.properties.
- Apply application.properties in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
YAML
Core concepts, implementation patterns, engineering trade-offs and production considerations for YAML.
- Explain the core concepts and architecture of YAML.
- Apply YAML in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Configuration Properties
Core concepts, implementation patterns, engineering trade-offs and production considerations for Configuration Properties.
- Explain the core concepts and architecture of Configuration Properties.
- Apply Configuration Properties in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Profiles
Core concepts, implementation patterns, engineering trade-offs and production considerations for Profiles.
- Explain the core concepts and architecture of Profiles.
- Apply Profiles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
External Configuration
Core concepts, implementation patterns, engineering trade-offs and production considerations for External Configuration.
- Explain the core concepts and architecture of External Configuration.
- Apply External Configuration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Application Startup
Core concepts, implementation patterns, engineering trade-offs and production considerations for Application Startup.
- Explain the core concepts and architecture of Application Startup.
- Apply Application Startup in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Embedded Server
Core concepts, implementation patterns, engineering trade-offs and production considerations for Embedded Server.
- Explain the core concepts and architecture of Embedded Server.
- Apply Embedded Server in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logging
Core concepts, implementation patterns, engineering trade-offs and production considerations for Logging.
- 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.
Actuator
Core concepts, implementation patterns, engineering trade-offs and production considerations for Actuator.
- Explain the core concepts and architecture of Actuator.
- Apply Actuator in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Health Indicators
Spring Boot’s current documentation explicitly describes production features such as security, metrics, health checks and externalized configuration as core non-functional capabilities. ([Home][5]); =====================================
- Explain the core concepts and architecture of Health Indicators.
- Apply Health Indicators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 242–253: DispatcherServlet, Controllers, RequestMapping, PathVariable, RequestParam, RequestBody, ResponseEntity, Validation and 4 more topics.
DispatcherServlet
Core concepts, implementation patterns, engineering trade-offs and production considerations for DispatcherServlet.
- Explain the core concepts and architecture of DispatcherServlet.
- Apply DispatcherServlet in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Controllers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Controllers.
- 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.
RequestMapping
Core concepts, implementation patterns, engineering trade-offs and production considerations for RequestMapping.
- Explain the core concepts and architecture of RequestMapping.
- Apply RequestMapping in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PathVariable
Core concepts, implementation patterns, engineering trade-offs and production considerations for PathVariable.
- Explain the core concepts and architecture of PathVariable.
- Apply PathVariable in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RequestParam
Core concepts, implementation patterns, engineering trade-offs and production considerations for RequestParam.
- Explain the core concepts and architecture of RequestParam.
- Apply RequestParam in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RequestBody
Core concepts, implementation patterns, engineering trade-offs and production considerations for RequestBody.
- Explain the core concepts and architecture of RequestBody.
- Apply RequestBody in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ResponseEntity
Core concepts, implementation patterns, engineering trade-offs and production considerations for ResponseEntity.
- Explain the core concepts and architecture of ResponseEntity.
- Apply ResponseEntity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Validation.
- 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.
ExceptionHandler
Core concepts, implementation patterns, engineering trade-offs and production considerations for ExceptionHandler.
- Explain the core concepts and architecture of ExceptionHandler.
- Apply ExceptionHandler in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ControllerAdvice
Core concepts, implementation patterns, engineering trade-offs and production considerations for ControllerAdvice.
- Explain the core concepts and architecture of ControllerAdvice.
- Apply ControllerAdvice in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Filters
Core concepts, implementation patterns, engineering trade-offs and production considerations for Filters.
- Explain the core concepts and architecture of Filters.
- Apply Filters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Interceptors
=====================================
- Explain the core concepts and architecture of Interceptors.
- Apply Interceptors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Applied engineering phase: Production Api Project.
Production Api Project
=====================================; Project: Customer Management API; Features:; customer CRUD; validation; pagination; filtering; search; standardized errors; audit fields; Swagger; PostgreSQL; automated testing
- Explain the core concepts and architecture of Production Api Project.
- Apply Production Api Project in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 254–272: ORM, Entity, Persistence Context, Entity States, Repository, JPQL, Native Queries, One-to-One and 11 more topics.
ORM
Core concepts, implementation patterns, engineering trade-offs and production considerations for ORM.
- Explain the core concepts and architecture of ORM.
- Apply ORM in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Entity
Core concepts, implementation patterns, engineering trade-offs and production considerations for Entity.
- 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.
Persistence Context
Core concepts, implementation patterns, engineering trade-offs and production considerations for Persistence Context.
- Explain the core concepts and architecture of Persistence Context.
- Apply Persistence Context in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Entity States
transient; managed; detached; removed
- Explain the core concepts and architecture of Entity States.
- Apply Entity States in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Repository
Core concepts, implementation patterns, engineering trade-offs and production considerations for Repository.
- 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.
JPQL
Core concepts, implementation patterns, engineering trade-offs and production considerations for JPQL.
- Explain the core concepts and architecture of JPQL.
- Apply JPQL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Native Queries
Core concepts, implementation patterns, engineering trade-offs and production considerations for Native Queries.
- Explain the core concepts and architecture of Native Queries.
- Apply Native Queries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
One-to-One
Core concepts, implementation patterns, engineering trade-offs and production considerations for One-to-One.
- Explain the core concepts and architecture of One-to-One.
- Apply One-to-One in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
One-to-Many
Core concepts, implementation patterns, engineering trade-offs and production considerations for One-to-Many.
- Explain the core concepts and architecture of One-to-Many.
- Apply One-to-Many in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Many-to-One
Core concepts, implementation patterns, engineering trade-offs and production considerations for Many-to-One.
- Explain the core concepts and architecture of Many-to-One.
- Apply Many-to-One in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Many-to-Many
Core concepts, implementation patterns, engineering trade-offs and production considerations for Many-to-Many.
- Explain the core concepts and architecture of Many-to-Many.
- Apply Many-to-Many in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Fetch Strategies
Core concepts, implementation patterns, engineering trade-offs and production considerations for Fetch Strategies.
- Explain the core concepts and architecture of Fetch Strategies.
- Apply Fetch Strategies in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cascades
Core concepts, implementation patterns, engineering trade-offs and production considerations for Cascades.
- Explain the core concepts and architecture of Cascades.
- Apply Cascades in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Orphan Removal
Core concepts, implementation patterns, engineering trade-offs and production considerations for Orphan Removal.
- Explain the core concepts and architecture of Orphan Removal.
- Apply Orphan Removal in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
N+1 Problem
Core concepts, implementation patterns, engineering trade-offs and production considerations for N+1 Problem.
- Explain the core concepts and architecture of N+1 Problem.
- Apply N+1 Problem in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Fetch Joins
Core concepts, implementation patterns, engineering trade-offs and production considerations for Fetch Joins.
- Explain the core concepts and architecture of Fetch Joins.
- Apply Fetch Joins in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Entity Graphs Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Entity Graphs Concepts.
- Explain the core concepts and architecture of Entity Graphs Concepts.
- Apply Entity Graphs Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Batch Operations
Core concepts, implementation patterns, engineering trade-offs and production considerations for Batch Operations.
- Explain the core concepts and architecture of Batch Operations.
- Apply Batch Operations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Auditing
=====================================
- Explain the core concepts and architecture of Auditing.
- Apply Auditing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 273–282: @Transactional, Transaction Boundaries, Propagation, Isolation, Rollback, Read-Only Transactions, Optimistic Locking, Pessimistic Locking and 2 more topics.
@Transactional
Core concepts, implementation patterns, engineering trade-offs and production considerations for @Transactional.
- Explain the core concepts and architecture of @Transactional.
- Apply @Transactional in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transaction Boundaries
Core concepts, implementation patterns, engineering trade-offs and production considerations for Transaction Boundaries.
- Explain the core concepts and architecture of Transaction Boundaries.
- Apply Transaction Boundaries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Propagation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Propagation.
- Explain the core concepts and architecture of Propagation.
- Apply Propagation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Isolation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Isolation.
- 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.
Rollback
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rollback.
- 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.
Read-Only Transactions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Read-Only Transactions.
- Explain the core concepts and architecture of Read-Only Transactions.
- Apply Read-Only Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Optimistic Locking
Core concepts, implementation patterns, engineering trade-offs and production considerations for Optimistic Locking.
- Explain the core concepts and architecture of Optimistic Locking.
- Apply Optimistic Locking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pessimistic Locking
Core concepts, implementation patterns, engineering trade-offs and production considerations for Pessimistic Locking.
- Explain the core concepts and architecture of Pessimistic Locking.
- Apply Pessimistic Locking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lost Update Problem
Core concepts, implementation patterns, engineering trade-offs and production considerations for Lost Update Problem.
- Explain the core concepts and architecture of Lost Update Problem.
- Apply Lost Update Problem in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Deadlock Handling
Scenario; Two users attempt to buy the final available product.; Student designs a concurrency-safe solution.; =====================================
- Explain the core concepts and architecture of Deadlock Handling.
- Apply Deadlock Handling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 283–287: Schema Versioning, Flyway Concepts, Migration Scripts, Backward-Compatible Database Changes, Expand/Contract Pattern Concepts.
Schema Versioning
Core concepts, implementation patterns, engineering trade-offs and production considerations for Schema Versioning.
- Explain the core concepts and architecture of Schema Versioning.
- Apply Schema Versioning in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Flyway Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Flyway Concepts.
- Explain the core concepts and architecture of Flyway Concepts.
- Apply Flyway Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Migration Scripts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Migration Scripts.
- Explain the core concepts and architecture of Migration Scripts.
- Apply Migration Scripts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Backward-Compatible Database Changes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Backward-Compatible Database Changes.
- Explain the core concepts and architecture of Backward-Compatible Database Changes.
- Apply Backward-Compatible Database Changes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Expand/Contract Pattern Concepts
=====================================
- Explain the core concepts and architecture of Expand/Contract Pattern Concepts.
- Apply Expand/Contract Pattern Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 288–297: Authentication, Authorization, Security Filter Chain, Password Hashing, Roles, Authorities, Method Security, CORS and 2 more topics.
Authentication
Core concepts, implementation patterns, engineering trade-offs and production considerations for Authentication.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Authorization.
- 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.
Security Filter Chain
Core concepts, implementation patterns, engineering trade-offs and production considerations for Security Filter Chain.
- Explain the core concepts and architecture of Security Filter Chain.
- Apply Security Filter Chain in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Password Hashing
Core concepts, implementation patterns, engineering trade-offs and production considerations for Password Hashing.
- 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.
Roles
Core concepts, implementation patterns, engineering trade-offs and production considerations for Roles.
- Explain the core concepts and architecture of Roles.
- Apply Roles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authorities
Core concepts, implementation patterns, engineering trade-offs and production considerations for Authorities.
- Explain the core concepts and architecture of Authorities.
- Apply Authorities in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Method Security
Core concepts, implementation patterns, engineering trade-offs and production considerations for Method Security.
- Explain the core concepts and architecture of Method Security.
- Apply Method Security in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CORS
Core concepts, implementation patterns, engineering trade-offs and production considerations for CORS.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for CSRF.
- 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.
Session Security
=====================================
- Explain the core concepts and architecture of Session Security.
- Apply Session Security in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 298–304: JWT, Access Tokens, Refresh Tokens, Token Expiry, Key Rotation Concepts, Revocation Strategies, Secure Token Validation.
JWT
Understand:; Header; payload; signature
- 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.
Access Tokens
Core concepts, implementation patterns, engineering trade-offs and production considerations for Access Tokens.
- Explain the core concepts and architecture of Access Tokens.
- Apply Access Tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Refresh Tokens
Core concepts, implementation patterns, engineering trade-offs and production considerations for Refresh Tokens.
- Explain the core concepts and architecture of Refresh Tokens.
- Apply Refresh Tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token Expiry
Core concepts, implementation patterns, engineering trade-offs and production considerations for Token Expiry.
- Explain the core concepts and architecture of Token Expiry.
- Apply Token Expiry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Key Rotation Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Key Rotation Concepts.
- Explain the core concepts and architecture of Key Rotation Concepts.
- Apply Key Rotation Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Revocation Strategies
Core concepts, implementation patterns, engineering trade-offs and production considerations for Revocation Strategies.
- Explain the core concepts and architecture of Revocation Strategies.
- Apply Revocation Strategies in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secure Token Validation
=====================================
- Explain the core concepts and architecture of Secure Token Validation.
- Apply Secure Token Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 305–314: OAuth 2.0, OpenID Connect, Resource Server, OAuth2 Client, Authorization Server Concepts, Authorization Code, PKCE, Client Credentials and 2 more topics.
OAuth 2.0
Core concepts, implementation patterns, engineering trade-offs and production considerations for OAuth 2.0.
- Explain the core concepts and architecture of OAuth 2.0.
- Apply OAuth 2.0 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
OpenID Connect
Core concepts, implementation patterns, engineering trade-offs and production considerations for OpenID Connect.
- Explain the core concepts and architecture of OpenID Connect.
- Apply OpenID Connect in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Resource Server
Core concepts, implementation patterns, engineering trade-offs and production considerations for Resource Server.
- Explain the core concepts and architecture of Resource Server.
- Apply Resource Server in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
OAuth2 Client
Core concepts, implementation patterns, engineering trade-offs and production considerations for OAuth2 Client.
- Explain the core concepts and architecture of OAuth2 Client.
- Apply OAuth2 Client in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authorization Server Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Authorization Server Concepts.
- Explain the core concepts and architecture of Authorization Server Concepts.
- Apply Authorization Server Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authorization Code
Core concepts, implementation patterns, engineering trade-offs and production considerations for Authorization Code.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for PKCE.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Client Credentials.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Scopes.
- 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.
JWT vs Opaque Tokens
Spring Security 7.1.1 currently supports OAuth2 Resource Server, OAuth2 Client and Authorization Server scenarios, including both JWT and opaque bearer-token validation. ([Home][6]); =====================================
- Explain the core concepts and architecture of JWT vs Opaque Tokens.
- Apply JWT vs Opaque Tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 315–323: OWASP API Risks, Input Validation, Output Validation, Rate Limiting, Brute-Force Protection, Secrets, Secure Headers, Audit Logging and 1 more topics.
OWASP API Risks
Teach:; Broken object-level authorization; broken authentication; excessive data exposure concepts; resource exhaustion; injection; security misconfiguration
- Explain the core concepts and architecture of OWASP API Risks.
- Apply OWASP API Risks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Input Validation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Input Validation.
- Explain the core concepts and architecture of Input Validation.
- Apply Input Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Output Validation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Output Validation.
- 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.
Rate Limiting
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rate Limiting.
- 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.
Brute-Force Protection
Core concepts, implementation patterns, engineering trade-offs and production considerations for Brute-Force Protection.
- 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.
Secrets
Core concepts, implementation patterns, engineering trade-offs and production considerations for Secrets.
- 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.
Secure Headers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Secure Headers.
- Explain the core concepts and architecture of Secure Headers.
- Apply Secure Headers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Audit Logging
Core concepts, implementation patterns, engineering trade-offs and production considerations for Audit Logging.
- Explain the core concepts and architecture of Audit Logging.
- Apply Audit Logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sensitive Data Handling
=====================================
- Explain the core concepts and architecture of Sensitive Data Handling.
- Apply Sensitive Data Handling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 324–337: Testing Strategy, Unit Tests, JUnit, Assertions, Mockito, Mocking, Controller Testing, MockMvc and 6 more topics.
Testing Strategy
Core concepts, implementation patterns, engineering trade-offs and production considerations for Testing Strategy.
- Explain the core concepts and architecture of Testing Strategy.
- Apply Testing Strategy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unit Tests
Core concepts, implementation patterns, engineering trade-offs and production considerations for Unit Tests.
- Explain the core concepts and architecture of Unit Tests.
- Apply Unit Tests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JUnit
Core concepts, implementation patterns, engineering trade-offs and production considerations for JUnit.
- Explain the core concepts and architecture of JUnit.
- Apply JUnit in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Assertions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Assertions.
- Explain the core concepts and architecture of Assertions.
- Apply Assertions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mockito
Core concepts, implementation patterns, engineering trade-offs and production considerations for Mockito.
- Explain the core concepts and architecture of Mockito.
- Apply Mockito in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mocking
Core concepts, implementation patterns, engineering trade-offs and production considerations for Mocking.
- 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.
Controller Testing
Core concepts, implementation patterns, engineering trade-offs and production considerations for Controller Testing.
- Explain the core concepts and architecture of Controller Testing.
- Apply Controller Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
MockMvc
Core concepts, implementation patterns, engineering trade-offs and production considerations for MockMvc.
- Explain the core concepts and architecture of MockMvc.
- Apply MockMvc in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Repository Testing
Core concepts, implementation patterns, engineering trade-offs and production considerations for Repository Testing.
- Explain the core concepts and architecture of Repository Testing.
- Apply Repository Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Integration Testing
Core concepts, implementation patterns, engineering trade-offs and production considerations for Integration Testing.
- Explain the core concepts and architecture of Integration Testing.
- Apply Integration Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Test Database Strategy
Core concepts, implementation patterns, engineering trade-offs and production considerations for Test Database Strategy.
- Explain the core concepts and architecture of Test Database Strategy.
- Apply Test Database Strategy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Testcontainers Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Testcontainers Concepts.
- Explain the core concepts and architecture of Testcontainers Concepts.
- Apply Testcontainers Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API Contract Testing Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for API Contract Testing Concepts.
- Explain the core concepts and architecture of API Contract Testing Concepts.
- Apply API Contract Testing Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mutation Testing Awareness
=====================================
- Explain the core concepts and architecture of Mutation Testing Awareness.
- Apply Mutation Testing Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Applied engineering phase: Test Design.
Test Design
=====================================; Teach students not to maximize coverage blindly.; Test:; Happy Path; Validation; Authentication; Authorization; Database Failure; Downstream Failure; Concurrency; Boundary Conditions
- Explain the core concepts and architecture of Test Design.
- Apply Test Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 338–344: Layered Architecture, Modular Monolith, Hexagonal Architecture, Clean Architecture Concepts, Ports and Adapters, Domain Services, Repository Pattern.
Layered Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for Layered Architecture.
- Explain the core concepts and architecture of Layered Architecture.
- Apply Layered Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modular Monolith
Core concepts, implementation patterns, engineering trade-offs and production considerations for Modular Monolith.
- 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.
Hexagonal Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for Hexagonal Architecture.
- Explain the core concepts and architecture of Hexagonal Architecture.
- Apply Hexagonal Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Clean Architecture Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Clean Architecture Concepts.
- Explain the core concepts and architecture of Clean Architecture Concepts.
- Apply Clean Architecture Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Ports and Adapters
Core concepts, implementation patterns, engineering trade-offs and production considerations for Ports and Adapters.
- Explain the core concepts and architecture of Ports and Adapters.
- Apply Ports and Adapters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Domain Services
Core concepts, implementation patterns, engineering trade-offs and production considerations for Domain Services.
- Explain the core concepts and architecture of Domain Services.
- Apply Domain Services in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Repository Pattern
=====================================
- Explain the core concepts and architecture of Repository Pattern.
- Apply Repository Pattern in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 345–352: Domain, Bounded Context, Entity, Value Object, Aggregate, Aggregate Root, Domain Events, Anti-Corruption Layer Concepts.
Domain
Core concepts, implementation patterns, engineering trade-offs and production considerations for Domain.
- Explain the core concepts and architecture of Domain.
- Apply Domain in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Bounded Context
Core concepts, implementation patterns, engineering trade-offs and production considerations for Bounded Context.
- 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.
Entity
Core concepts, implementation patterns, engineering trade-offs and production considerations for Entity.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Value Object.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Aggregate.
- 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.
Aggregate Root
Core concepts, implementation patterns, engineering trade-offs and production considerations for Aggregate Root.
- Explain the core concepts and architecture of Aggregate Root.
- Apply Aggregate Root in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Domain Events
Core concepts, implementation patterns, engineering trade-offs and production considerations for Domain Events.
- Explain the core concepts and architecture of Domain Events.
- Apply Domain Events in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Anti-Corruption Layer Concepts
=====================================
- Explain the core concepts and architecture of Anti-Corruption Layer Concepts.
- Apply Anti-Corruption Layer Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 353–360: Microservice Architecture, Why Microservices?, When NOT to Use Microservices, Service Boundaries, Database Per Service, Loose Coupling, Independent Deployment, Distributed System Complexity.
Microservice Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for Microservice Architecture.
- Explain the core concepts and architecture of Microservice Architecture.
- Apply Microservice Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Why Microservices?
Core concepts, implementation patterns, engineering trade-offs and production considerations for Why Microservices?.
- Explain the core concepts and architecture of Why Microservices?.
- Apply Why Microservices? in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
When NOT to Use Microservices
Critical topic.
- Explain the core concepts and architecture of When NOT to Use Microservices.
- Apply When NOT to Use Microservices in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Service Boundaries
Core concepts, implementation patterns, engineering trade-offs and production considerations for Service Boundaries.
- 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.
Database Per Service
Core concepts, implementation patterns, engineering trade-offs and production considerations for Database Per Service.
- Explain the core concepts and architecture of Database Per Service.
- Apply Database Per Service in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Loose Coupling
Core concepts, implementation patterns, engineering trade-offs and production considerations for Loose Coupling.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Independent Deployment.
- 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.
Distributed System Complexity
Current backend hiring continues to explicitly combine Spring microservices with scalability, resilience, API contract integrity, Kafka and container tooling. ([LinkedIn][2]); =====================================
- Explain the core concepts and architecture of Distributed System Complexity.
- Apply Distributed System Complexity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 361–367: Synchronous REST, HTTP Clients, RestClient, WebClient Awareness, gRPC Awareness, Asynchronous Communication, Choosing Sync vs Async.
Synchronous REST
Core concepts, implementation patterns, engineering trade-offs and production considerations for Synchronous REST.
- Explain the core concepts and architecture of Synchronous REST.
- Apply Synchronous REST in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HTTP Clients
Core concepts, implementation patterns, engineering trade-offs and production considerations for HTTP Clients.
- Explain the core concepts and architecture of HTTP Clients.
- Apply HTTP Clients in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RestClient
Core concepts, implementation patterns, engineering trade-offs and production considerations for RestClient.
- Explain the core concepts and architecture of RestClient.
- Apply RestClient in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
WebClient Awareness
Core concepts, implementation patterns, engineering trade-offs and production considerations for WebClient Awareness.
- Explain the core concepts and architecture of WebClient Awareness.
- Apply WebClient Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
gRPC Awareness
Core concepts, implementation patterns, engineering trade-offs and production considerations for gRPC Awareness.
- 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.
Asynchronous Communication
Core concepts, implementation patterns, engineering trade-offs and production considerations for Asynchronous Communication.
- Explain the core concepts and architecture of Asynchronous Communication.
- Apply Asynchronous Communication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Choosing Sync vs Async
=====================================
- Explain the core concepts and architecture of Choosing Sync vs Async.
- Apply Choosing Sync vs Async in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 368–376: Timeout, Retry, Exponential Backoff, Jitter, Circuit Breaker, Bulkhead, Rate Limiter, Resilience4j and 1 more topics.
Timeout
Core concepts, implementation patterns, engineering trade-offs and production considerations for Timeout.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Retry.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Exponential Backoff.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Jitter.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Circuit Breaker.
- Explain the core concepts and architecture of Circuit Breaker.
- Apply Circuit Breaker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Bulkhead
Core concepts, implementation patterns, engineering trade-offs and production considerations for Bulkhead.
- Explain the core concepts and architecture of Bulkhead.
- Apply Bulkhead in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate Limiter
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rate Limiter.
- Explain the core concepts and architecture of Rate Limiter.
- Apply Rate Limiter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Resilience4j
Core concepts, implementation patterns, engineering trade-offs and production considerations for Resilience4j.
- Explain the core concepts and architecture of Resilience4j.
- Apply Resilience4j in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Fallback
Critical Rule; Do not retry every operation blindly.; =====================================
- Explain the core concepts and architecture of Fallback.
- Apply Fallback in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 377–381: Duplicate Requests, Idempotent Consumers, Idempotency Keys, Duplicate Event Detection, Retry-Safe Business Logic.
Duplicate Requests
Core concepts, implementation patterns, engineering trade-offs and production considerations for Duplicate Requests.
- Explain the core concepts and architecture of Duplicate Requests.
- Apply Duplicate Requests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotent Consumers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Idempotent Consumers.
- 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.
Idempotency Keys
Core concepts, implementation patterns, engineering trade-offs and production considerations for Idempotency Keys.
- Explain the core concepts and architecture of Idempotency Keys.
- Apply Idempotency Keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Duplicate Event Detection
Core concepts, implementation patterns, engineering trade-offs and production considerations for Duplicate Event Detection.
- Explain the core concepts and architecture of Duplicate Event Detection.
- Apply Duplicate Event Detection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry-Safe Business Logic
Lab; Implement:; POST /payments; with an idempotency key.; =====================================
- Explain the core concepts and architecture of Retry-Safe Business Logic.
- Apply Retry-Safe Business Logic in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 382–389: Distributed Transaction Problem, Two-Phase Commit Concepts, Saga, Choreography, Orchestration, Compensation, Transactional Outbox, Inbox Pattern Concepts.
Distributed Transaction Problem
Core concepts, implementation patterns, engineering trade-offs and production considerations for Distributed Transaction Problem.
- Explain the core concepts and architecture of Distributed Transaction Problem.
- Apply Distributed Transaction Problem in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Two-Phase Commit Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Two-Phase Commit Concepts.
- Explain the core concepts and architecture of Two-Phase Commit Concepts.
- Apply Two-Phase Commit Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Saga
Core concepts, implementation patterns, engineering trade-offs and production considerations for Saga.
- 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.
Choreography
Core concepts, implementation patterns, engineering trade-offs and production considerations for Choreography.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Orchestration.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Compensation.
- 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.
Transactional Outbox
Core concepts, implementation patterns, engineering trade-offs and production considerations for Transactional Outbox.
- 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.
Inbox Pattern Concepts
=====================================
- Explain the core concepts and architecture of Inbox Pattern Concepts.
- Apply Inbox Pattern Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 390–408: Event-Driven Systems, Kafka Architecture, Brokers, Topics, Partitions, Producers, Consumers, Consumer Groups and 11 more topics.
Event-Driven Systems
Core concepts, implementation patterns, engineering trade-offs and production considerations for Event-Driven Systems.
- Explain the core concepts and architecture of Event-Driven Systems.
- Apply Event-Driven Systems in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Kafka Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for Kafka Architecture.
- Explain the core concepts and architecture of Kafka Architecture.
- Apply Kafka Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Brokers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Brokers.
- Explain the core concepts and architecture of Brokers.
- Apply Brokers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Topics
Core concepts, implementation patterns, engineering trade-offs and production considerations for Topics.
- Explain the core concepts and architecture of Topics.
- Apply Topics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Partitions
Core concepts, implementation patterns, engineering trade-offs and production considerations for Partitions.
- 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.
Producers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Producers.
- Explain the core concepts and architecture of Producers.
- Apply Producers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consumers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Consumers.
- Explain the core concepts and architecture of Consumers.
- Apply Consumers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consumer Groups
Core concepts, implementation patterns, engineering trade-offs and production considerations for Consumer Groups.
- Explain the core concepts and architecture of Consumer Groups.
- Apply Consumer Groups in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Offsets
Core concepts, implementation patterns, engineering trade-offs and production considerations for Offsets.
- Explain the core concepts and architecture of Offsets.
- Apply Offsets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Keys
Core concepts, implementation patterns, engineering trade-offs and production considerations for Keys.
- 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.
Ordering
Core concepts, implementation patterns, engineering trade-offs and production considerations for Ordering.
- Explain the core concepts and architecture of Ordering.
- Apply Ordering in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Replication
Core concepts, implementation patterns, engineering trade-offs and production considerations for Replication.
- Explain the core concepts and architecture of Replication.
- Apply Replication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Delivery Semantics
Core concepts, implementation patterns, engineering trade-offs and production considerations for Delivery Semantics.
- Explain the core concepts and architecture of Delivery Semantics.
- Apply Delivery Semantics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Serialization
Core concepts, implementation patterns, engineering trade-offs and production considerations for Serialization.
- Explain the core concepts and architecture of Serialization.
- Apply Serialization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Schema Evolution
Core concepts, implementation patterns, engineering trade-offs and production considerations for Schema Evolution.
- Explain the core concepts and architecture of Schema Evolution.
- Apply Schema Evolution in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry Topics
Core concepts, implementation patterns, engineering trade-offs and production considerations for Retry Topics.
- Explain the core concepts and architecture of Retry Topics.
- Apply Retry Topics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dead-Letter Topics
Core concepts, implementation patterns, engineering trade-offs and production considerations for Dead-Letter Topics.
- 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.
Consumer Lag
Core concepts, implementation patterns, engineering trade-offs and production considerations for Consumer Lag.
- Explain the core concepts and architecture of Consumer Lag.
- Apply Consumer Lag in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotent Consumer
Kafka Major Project; Event-Driven Order Platform; Order Service; order-created; Kafka; Inventory Service; Payment Service; Notification Service; =====================================
- Explain the core concepts and architecture of Idempotent Consumer.
- Apply Idempotent Consumer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 409–418: Caching Fundamentals, Cache-Aside, Write-Through Concepts, TTL, Cache Eviction, Cache Invalidation, Cache Stampede, Distributed Locks Concepts and 2 more topics.
Caching Fundamentals
Core concepts, implementation patterns, engineering trade-offs and production considerations for Caching Fundamentals.
- Explain the core concepts and architecture of Caching Fundamentals.
- Apply Caching Fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache-Aside
Core concepts, implementation patterns, engineering trade-offs and production considerations for Cache-Aside.
- 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.
Write-Through Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Write-Through Concepts.
- Explain the core concepts and architecture of Write-Through Concepts.
- Apply Write-Through Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TTL
Core concepts, implementation patterns, engineering trade-offs and production considerations for TTL.
- 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.
Cache Eviction
Core concepts, implementation patterns, engineering trade-offs and production considerations for Cache Eviction.
- Explain the core concepts and architecture of Cache Eviction.
- Apply Cache Eviction in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache Invalidation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Cache Invalidation.
- 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.
Cache Stampede
Core concepts, implementation patterns, engineering trade-offs and production considerations for Cache Stampede.
- 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.
Distributed Locks Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Distributed Locks Concepts.
- Explain the core concepts and architecture of Distributed Locks Concepts.
- Apply Distributed Locks Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate Limiting
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rate Limiting.
- 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.
Session Storage Concepts
=====================================
- Explain the core concepts and architecture of Session Storage Concepts.
- Apply Session Storage Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 419–425: Gateway Pattern, Routing, Authentication, Rate Limiting, Header Manipulation, Correlation IDs, Spring Cloud Gateway Concepts.
Gateway Pattern
Core concepts, implementation patterns, engineering trade-offs and production considerations for Gateway Pattern.
- Explain the core concepts and architecture of Gateway Pattern.
- Apply Gateway Pattern in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Routing
Core concepts, implementation patterns, engineering trade-offs and production considerations for Routing.
- 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.
Authentication
Core concepts, implementation patterns, engineering trade-offs and production considerations for Authentication.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rate Limiting.
- 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.
Header Manipulation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Header Manipulation.
- Explain the core concepts and architecture of Header Manipulation.
- Apply Header Manipulation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Correlation IDs
Core concepts, implementation patterns, engineering trade-offs and production considerations for Correlation IDs.
- 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.
Spring Cloud Gateway Concepts
=====================================
- Explain the core concepts and architecture of Spring Cloud Gateway Concepts.
- Apply Spring Cloud Gateway Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 426–430: Central Configuration, Service Discovery Concepts, Kubernetes DNS / Service Discovery, Environment-Based Configuration, Secret Management.
Central Configuration
Core concepts, implementation patterns, engineering trade-offs and production considerations for Central Configuration.
- Explain the core concepts and architecture of Central Configuration.
- Apply Central Configuration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Service Discovery Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Service Discovery Concepts.
- Explain the core concepts and architecture of Service Discovery Concepts.
- Apply Service Discovery Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Kubernetes DNS / Service Discovery
Core concepts, implementation patterns, engineering trade-offs and production considerations for Kubernetes DNS / Service Discovery.
- Explain the core concepts and architecture of Kubernetes DNS / Service Discovery.
- Apply Kubernetes DNS / Service Discovery in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environment-Based Configuration
Core concepts, implementation patterns, engineering trade-offs and production considerations for Environment-Based Configuration.
- Explain the core concepts and architecture of Environment-Based Configuration.
- Apply Environment-Based Configuration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secret Management
Avoid teaching legacy Netflix-stack components as mandatory architecture.; =====================================
- Explain the core concepts and architecture of Secret Management.
- Apply Secret Management in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 431–436: Scheduled Jobs, Asynchronous Jobs, Job States, Retry, Idempotency, Distributed Scheduler Concepts.
Scheduled Jobs
Core concepts, implementation patterns, engineering trade-offs and production considerations for Scheduled Jobs.
- 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.
Asynchronous Jobs
Core concepts, implementation patterns, engineering trade-offs and production considerations for Asynchronous Jobs.
- Explain the core concepts and architecture of Asynchronous Jobs.
- Apply Asynchronous Jobs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Job States
Example:; QUEUED; RUNNING; COMPLETED; FAILED
- Explain the core concepts and architecture of Job States.
- Apply Job States in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry
Core concepts, implementation patterns, engineering trade-offs and production considerations for Retry.
- 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.
Idempotency
Core concepts, implementation patterns, engineering trade-offs and production considerations for Idempotency.
- 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.
Distributed Scheduler Concepts
=====================================
- Explain the core concepts and architecture of Distributed Scheduler Concepts.
- Apply Distributed Scheduler Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 437–440: WebSockets, Server-Sent Events, Notifications, Streaming API Concepts.
WebSockets
Core concepts, implementation patterns, engineering trade-offs and production considerations for WebSockets.
- Explain the core concepts and architecture of WebSockets.
- Apply WebSockets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Server-Sent Events
Core concepts, implementation patterns, engineering trade-offs and production considerations for Server-Sent Events.
- Explain the core concepts and architecture of Server-Sent Events.
- Apply Server-Sent Events in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notifications
Core concepts, implementation patterns, engineering trade-offs and production considerations for Notifications.
- 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.
Streaming API Concepts
=====================================
- Explain the core concepts and architecture of Streaming API Concepts.
- Apply Streaming API Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 441–447: Logging Levels, Structured Logging, JSON Logs, Request IDs, Correlation IDs, MDC Concepts, Sensitive Data Redaction.
Logging Levels
Core concepts, implementation patterns, engineering trade-offs and production considerations for Logging Levels.
- Explain the core concepts and architecture of Logging Levels.
- Apply Logging Levels in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Structured Logging
Core concepts, implementation patterns, engineering trade-offs and production considerations for Structured Logging.
- Explain the core concepts and architecture of Structured Logging.
- Apply Structured Logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JSON Logs
Core concepts, implementation patterns, engineering trade-offs and production considerations for JSON Logs.
- Explain the core concepts and architecture of JSON Logs.
- Apply JSON Logs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Request IDs
Core concepts, implementation patterns, engineering trade-offs and production considerations for Request IDs.
- Explain the core concepts and architecture of Request IDs.
- Apply Request IDs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Correlation IDs
Core concepts, implementation patterns, engineering trade-offs and production considerations for Correlation IDs.
- 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.
MDC Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for MDC Concepts.
- Explain the core concepts and architecture of MDC Concepts.
- Apply MDC Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sensitive Data Redaction
Never log:; passwords; private keys; tokens; secrets; unnecessary PII; =====================================
- Explain the core concepts and architecture of Sensitive Data Redaction.
- Apply Sensitive Data Redaction in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 448–452: Operational Metrics, Spring Boot Actuator, Micrometer Concepts, Prometheus Concepts, Grafana Concepts.
Operational Metrics
Monitor:; request rate; error rate; latency; saturation
- Explain the core concepts and architecture of Operational Metrics.
- Apply Operational Metrics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Spring Boot Actuator
Core concepts, implementation patterns, engineering trade-offs and production considerations for Spring Boot Actuator.
- Explain the core concepts and architecture of Spring Boot Actuator.
- Apply Spring Boot Actuator in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Micrometer Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Micrometer Concepts.
- Explain the core concepts and architecture of Micrometer Concepts.
- Apply Micrometer Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Prometheus Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Prometheus Concepts.
- Explain the core concepts and architecture of Prometheus Concepts.
- Apply Prometheus Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Grafana Concepts
=====================================
- Explain the core concepts and architecture of Grafana Concepts.
- Apply Grafana Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 453–456: Trace, Span, Context Propagation, OpenTelemetry.
Trace
Core concepts, implementation patterns, engineering trade-offs and production considerations for Trace.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Span.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Context Propagation.
- 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.
OpenTelemetry
Trace example:; Client; Gateway; Order Service; Inventory Service; PostgreSQL; Kafka; =====================================
- Explain the core concepts and architecture of OpenTelemetry.
- Apply OpenTelemetry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 457–464: Performance Methodology, Latency Percentiles, Throughput, CPU Bottlenecks, Memory Bottlenecks, Thread Pool Bottlenecks, Database Bottlenecks, Network Bottlenecks.
Performance Methodology
Measure before optimizing.
- Explain the core concepts and architecture of Performance Methodology.
- Apply Performance Methodology in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Latency Percentiles
Teach:; P50; P95; P99
- Explain the core concepts and architecture of Latency Percentiles.
- Apply Latency Percentiles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Throughput
Core concepts, implementation patterns, engineering trade-offs and production considerations for Throughput.
- Explain the core concepts and architecture of Throughput.
- Apply Throughput in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CPU Bottlenecks
Core concepts, implementation patterns, engineering trade-offs and production considerations for CPU Bottlenecks.
- Explain the core concepts and architecture of CPU Bottlenecks.
- Apply CPU Bottlenecks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Memory Bottlenecks
Core concepts, implementation patterns, engineering trade-offs and production considerations for Memory Bottlenecks.
- Explain the core concepts and architecture of Memory Bottlenecks.
- Apply Memory Bottlenecks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Thread Pool Bottlenecks
Core concepts, implementation patterns, engineering trade-offs and production considerations for Thread Pool Bottlenecks.
- Explain the core concepts and architecture of Thread Pool Bottlenecks.
- Apply Thread Pool Bottlenecks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Database Bottlenecks
Core concepts, implementation patterns, engineering trade-offs and production considerations for Database Bottlenecks.
- Explain the core concepts and architecture of Database Bottlenecks.
- Apply Database Bottlenecks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Network Bottlenecks
=====================================
- Explain the core concepts and architecture of Network Bottlenecks.
- Apply Network Bottlenecks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 465–473: Slow Queries, Indexes, Query Plans, N+1, Batch Inserts, Connection Pooling, Pool Exhaustion, Read Replicas Concepts and 1 more topics.
Slow Queries
Core concepts, implementation patterns, engineering trade-offs and production considerations for Slow Queries.
- 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.
Indexes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Indexes.
- 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.
Query Plans
Core concepts, implementation patterns, engineering trade-offs and production considerations for Query Plans.
- Explain the core concepts and architecture of Query Plans.
- Apply Query Plans in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
N+1
Core concepts, implementation patterns, engineering trade-offs and production considerations for N+1.
- Explain the core concepts and architecture of N+1.
- Apply N+1 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Batch Inserts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Batch Inserts.
- Explain the core concepts and architecture of Batch Inserts.
- Apply Batch Inserts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection Pooling
Core concepts, implementation patterns, engineering trade-offs and production considerations for Connection Pooling.
- 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.
Pool Exhaustion
Core concepts, implementation patterns, engineering trade-offs and production considerations for Pool Exhaustion.
- Explain the core concepts and architecture of Pool Exhaustion.
- Apply Pool Exhaustion in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Read Replicas Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Read Replicas Concepts.
- Explain the core concepts and architecture of Read Replicas Concepts.
- Apply Read Replicas Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Partitioning Concepts
=====================================
- Explain the core concepts and architecture of Partitioning Concepts.
- Apply Partitioning Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 474–479: Heap Analysis, GC Analysis, Thread Dump Analysis, CPU Profiling, Memory Leak Investigation, Connection Leak Investigation.
Heap Analysis
Core concepts, implementation patterns, engineering trade-offs and production considerations for Heap Analysis.
- Explain the core concepts and architecture of Heap Analysis.
- Apply Heap Analysis in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
GC Analysis
Core concepts, implementation patterns, engineering trade-offs and production considerations for GC Analysis.
- Explain the core concepts and architecture of GC Analysis.
- Apply GC Analysis in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Thread Dump Analysis
Core concepts, implementation patterns, engineering trade-offs and production considerations for Thread Dump Analysis.
- Explain the core concepts and architecture of Thread Dump Analysis.
- Apply Thread Dump Analysis in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CPU Profiling
Core concepts, implementation patterns, engineering trade-offs and production considerations for CPU Profiling.
- 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.
Memory Leak Investigation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Memory Leak Investigation.
- Explain the core concepts and architecture of Memory Leak Investigation.
- Apply Memory Leak Investigation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection Leak Investigation
=====================================
- Explain the core concepts and architecture of Connection Leak Investigation.
- Apply Connection Leak Investigation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 480–485: Performance Test Design, Load, Stress, Spike, Soak Testing, JMeter/k6 Concepts.
Performance Test Design
Core concepts, implementation patterns, engineering trade-offs and production considerations for Performance Test Design.
- Explain the core concepts and architecture of Performance Test Design.
- Apply Performance Test Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Load
Core concepts, implementation patterns, engineering trade-offs and production considerations for Load.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Stress.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Spike.
- 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 Testing
Core concepts, implementation patterns, engineering trade-offs and production considerations for Soak Testing.
- Explain the core concepts and architecture of Soak Testing.
- Apply Soak Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JMeter/k6 Concepts
=====================================
- Explain the core concepts and architecture of JMeter/k6 Concepts.
- Apply JMeter/k6 Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 486–494: Containers, Images, Dockerfile, Multi-Stage Builds, Ports, Environment Variables, Volumes, Networks and 1 more topics.
Containers
Core concepts, implementation patterns, engineering trade-offs and production considerations for Containers.
- Explain the core concepts and architecture of Containers.
- Apply Containers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Images
Core concepts, implementation patterns, engineering trade-offs and production considerations for Images.
- Explain the core concepts and architecture of Images.
- Apply Images in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dockerfile
Core concepts, implementation patterns, engineering trade-offs and production considerations for Dockerfile.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Multi-Stage Builds.
- 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.
Ports
Core concepts, implementation patterns, engineering trade-offs and production considerations for Ports.
- 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.
Environment Variables
Core concepts, implementation patterns, engineering trade-offs and production considerations for Environment Variables.
- 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.
Volumes
Core concepts, implementation patterns, engineering trade-offs and production considerations for Volumes.
- 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.
Networks
Core concepts, implementation patterns, engineering trade-offs and production considerations for Networks.
- 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.
Docker Compose
Local environment:; Java service; PostgreSQL; Kafka; Redis; =====================================
- 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.
Modules 495–508: Kubernetes Architecture, Pods, Deployments, Services, ConfigMaps, Secrets, Readiness Probe, Liveness Probe and 6 more topics.
Kubernetes Architecture
Core concepts, implementation patterns, engineering trade-offs and production considerations for Kubernetes Architecture.
- Explain the core concepts and architecture of Kubernetes Architecture.
- Apply Kubernetes Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pods
Core concepts, implementation patterns, engineering trade-offs and production considerations for Pods.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Deployments.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Services.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for ConfigMaps.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Secrets.
- 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.
Readiness Probe
Core concepts, implementation patterns, engineering trade-offs and production considerations for Readiness Probe.
- Explain the core concepts and architecture of Readiness Probe.
- Apply Readiness Probe in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Liveness Probe
Core concepts, implementation patterns, engineering trade-offs and production considerations for Liveness Probe.
- Explain the core concepts and architecture of Liveness Probe.
- Apply Liveness Probe in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Startup Probe
Core concepts, implementation patterns, engineering trade-offs and production considerations for Startup Probe.
- Explain the core concepts and architecture of Startup Probe.
- Apply Startup Probe in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Requests/Limits
Core concepts, implementation patterns, engineering trade-offs and production considerations for Requests/Limits.
- Explain the core concepts and architecture of Requests/Limits.
- Apply Requests/Limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Autoscaling Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Autoscaling Concepts.
- 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.
Ingress Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Ingress Concepts.
- Explain the core concepts and architecture of Ingress Concepts.
- Apply Ingress Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rolling Updates
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rolling Updates.
- Explain the core concepts and architecture of Rolling Updates.
- Apply Rolling Updates in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rollbacks
=====================================
- Explain the core concepts and architecture of Rollbacks.
- Apply Rollbacks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 509–521: Cloud Fundamentals, IAM, Networking, EC2, S3, RDS, Load Balancer, Auto Scaling and 5 more topics.
Cloud Fundamentals
Core concepts, implementation patterns, engineering trade-offs and production considerations for Cloud Fundamentals.
- Explain the core concepts and architecture of Cloud Fundamentals.
- Apply Cloud Fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
IAM
Core concepts, implementation patterns, engineering trade-offs and production considerations for IAM.
- Explain the core concepts and architecture of IAM.
- Apply IAM in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Networking
Core concepts, implementation patterns, engineering trade-offs and production considerations for Networking.
- Explain the core concepts and architecture of Networking.
- Apply Networking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
EC2
Core concepts, implementation patterns, engineering trade-offs and production considerations for EC2.
- Explain the core concepts and architecture of EC2.
- Apply EC2 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
S3
Core concepts, implementation patterns, engineering trade-offs and production considerations for S3.
- 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.
RDS
Core concepts, implementation patterns, engineering trade-offs and production considerations for RDS.
- 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.
Load Balancer
Core concepts, implementation patterns, engineering trade-offs and production considerations for Load Balancer.
- Explain the core concepts and architecture of Load Balancer.
- Apply Load Balancer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Auto Scaling
Core concepts, implementation patterns, engineering trade-offs and production considerations for Auto Scaling.
- Explain the core concepts and architecture of Auto Scaling.
- Apply Auto Scaling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CloudWatch
Core concepts, implementation patterns, engineering trade-offs and production considerations for CloudWatch.
- Explain the core concepts and architecture of CloudWatch.
- Apply CloudWatch in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secrets Management Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Secrets Management Concepts.
- Explain the core concepts and architecture of Secrets Management Concepts.
- Apply Secrets Management Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Container Deployment Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Container Deployment Concepts.
- Explain the core concepts and architecture of Container Deployment Concepts.
- Apply Container Deployment Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Managed Kubernetes Awareness
Core concepts, implementation patterns, engineering trade-offs and production considerations for Managed Kubernetes Awareness.
- Explain the core concepts and architecture of Managed Kubernetes Awareness.
- Apply Managed Kubernetes Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
High Availability
=====================================
- Explain the core concepts and architecture of High Availability.
- Apply High Availability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 522–528: CI, CD, GitHub Actions, Jenkins Concepts, Artifact Repositories, Rollback, Deployment Approvals.
CI
Pipeline:; Commit; Compile; Unit Tests; Integration Tests; Security Scan; Package; Container Build
- Explain the core concepts and architecture of CI.
- Apply CI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CD
Image; Development; Test; Staging; Production
- Explain the core concepts and architecture of CD.
- Apply CD in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
GitHub Actions
Core concepts, implementation patterns, engineering trade-offs and production considerations for GitHub Actions.
- 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.
Jenkins Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Jenkins Concepts.
- Explain the core concepts and architecture of Jenkins Concepts.
- Apply Jenkins Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Artifact Repositories
Core concepts, implementation patterns, engineering trade-offs and production considerations for Artifact Repositories.
- Explain the core concepts and architecture of Artifact Repositories.
- Apply Artifact Repositories in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rollback
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rollback.
- 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.
Deployment Approvals
=====================================
- Explain the core concepts and architecture of Deployment Approvals.
- Apply Deployment Approvals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 529–532: Rolling, Blue/Green, Canary, Feature Flags Concepts.
Rolling
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rolling.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Blue/Green.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Canary.
- 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.
Feature Flags Concepts
=====================================
- Explain the core concepts and architecture of Feature Flags Concepts.
- Apply Feature Flags Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 533–539: Dependency Vulnerabilities, Secret Rotation, TLS Certificates, Audit Trails, Least Privilege, Service Identity, Supply-Chain Awareness.
Dependency Vulnerabilities
Core concepts, implementation patterns, engineering trade-offs and production considerations for Dependency Vulnerabilities.
- 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.
Secret Rotation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Secret Rotation.
- Explain the core concepts and architecture of Secret Rotation.
- Apply Secret Rotation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TLS Certificates
Core concepts, implementation patterns, engineering trade-offs and production considerations for TLS Certificates.
- Explain the core concepts and architecture of TLS Certificates.
- Apply TLS Certificates in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Audit Trails
Core concepts, implementation patterns, engineering trade-offs and production considerations for Audit Trails.
- Explain the core concepts and architecture of Audit Trails.
- Apply Audit Trails in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Least Privilege
Core concepts, implementation patterns, engineering trade-offs and production considerations for Least Privilege.
- Explain the core concepts and architecture of Least Privilege.
- Apply Least Privilege in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Service Identity
Core concepts, implementation patterns, engineering trade-offs and production considerations for Service Identity.
- Explain the core concepts and architecture of Service Identity.
- Apply Service Identity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Supply-Chain Awareness
=====================================
- Explain the core concepts and architecture of Supply-Chain Awareness.
- Apply Supply-Chain Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 540–549: Factory, Builder, Strategy, Adapter, Decorator, Observer, Template Method, Chain of Responsibility and 2 more topics.
Factory
Core concepts, implementation patterns, engineering trade-offs and production considerations for Factory.
- 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.
Builder
Core concepts, implementation patterns, engineering trade-offs and production considerations for Builder.
- Explain the core concepts and architecture of Builder.
- Apply Builder in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Strategy
Core concepts, implementation patterns, engineering trade-offs and production considerations for Strategy.
- 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
Core concepts, implementation patterns, engineering trade-offs and production considerations for Adapter.
- 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.
Decorator
Core concepts, implementation patterns, engineering trade-offs and production considerations for Decorator.
- Explain the core concepts and architecture of Decorator.
- Apply Decorator in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Observer
Core concepts, implementation patterns, engineering trade-offs and production considerations for Observer.
- 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.
Template Method
Core concepts, implementation patterns, engineering trade-offs and production considerations for Template Method.
- Explain the core concepts and architecture of Template Method.
- Apply Template Method in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Chain of Responsibility
Core concepts, implementation patterns, engineering trade-offs and production considerations for Chain of Responsibility.
- Explain the core concepts and architecture of Chain of Responsibility.
- Apply Chain of Responsibility in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Facade
Core concepts, implementation patterns, engineering trade-offs and production considerations for Facade.
- 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.
Repository
=====================================
- 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.
Applied engineering phase: Low-Level Design.
Low-Level Design
=====================================; Teach:; requirements; use cases; entities; interfaces; SOLID; extensibility; concurrency concerns; LLD Problems; Parking Lot; Library Management; Elevator; Movie Booking; Food Delivery; ATM; Payment Gateway; Notification System; Rate Limiter; Task Scheduler
- 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.
Modules 550–569: Requirements, Capacity Estimation, API Design, Database Selection, SQL vs NoSQL, Caching, Load Balancing, Horizontal Scaling and 12 more topics.
Requirements
Core concepts, implementation patterns, engineering trade-offs and production considerations for Requirements.
- Explain the core concepts and architecture of Requirements.
- Apply Requirements in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Capacity Estimation
Core concepts, implementation patterns, engineering trade-offs and production considerations for Capacity Estimation.
- Explain the core concepts and architecture of Capacity Estimation.
- Apply Capacity Estimation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API Design
Core concepts, implementation patterns, engineering trade-offs and production considerations for API Design.
- Explain the core concepts and architecture of API Design.
- Apply API Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Database Selection
Core concepts, implementation patterns, engineering trade-offs and production considerations for Database Selection.
- Explain the core concepts and architecture of Database Selection.
- Apply Database Selection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SQL vs NoSQL
Core concepts, implementation patterns, engineering trade-offs and production considerations for SQL vs NoSQL.
- 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.
Caching
Core concepts, implementation patterns, engineering trade-offs and production considerations for Caching.
- 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.
Load Balancing
Core concepts, implementation patterns, engineering trade-offs and production considerations for Load Balancing.
- Explain the core concepts and architecture of Load Balancing.
- Apply Load Balancing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Horizontal Scaling
Core concepts, implementation patterns, engineering trade-offs and production considerations for Horizontal Scaling.
- Explain the core concepts and architecture of Horizontal Scaling.
- Apply Horizontal Scaling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Replication
Core concepts, implementation patterns, engineering trade-offs and production considerations for Replication.
- Explain the core concepts and architecture of Replication.
- Apply Replication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Partitioning
Core concepts, implementation patterns, engineering trade-offs and production considerations for Partitioning.
- Explain the core concepts and architecture of Partitioning.
- Apply Partitioning in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Message Queues
Core concepts, implementation patterns, engineering trade-offs and production considerations for Message Queues.
- Explain the core concepts and architecture of Message Queues.
- Apply Message Queues in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Event Streaming
Core concepts, implementation patterns, engineering trade-offs and production considerations for Event Streaming.
- Explain the core concepts and architecture of Event Streaming.
- Apply Event Streaming in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CDN Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for CDN Concepts.
- Explain the core concepts and architecture of CDN Concepts.
- Apply CDN Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Object Storage
Core concepts, implementation patterns, engineering trade-offs and production considerations for Object Storage.
- Explain the core concepts and architecture of Object Storage.
- Apply Object Storage in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate Limiting
Core concepts, implementation patterns, engineering trade-offs and production considerations for Rate Limiting.
- 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.
Consistency
Core concepts, implementation patterns, engineering trade-offs and production considerations for Consistency.
- Explain the core concepts and architecture of Consistency.
- Apply Consistency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Availability
Core concepts, implementation patterns, engineering trade-offs and production considerations for Availability.
- Explain the core concepts and architecture of Availability.
- Apply Availability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CAP Theorem
Core concepts, implementation patterns, engineering trade-offs and production considerations for CAP Theorem.
- Explain the core concepts and architecture of CAP Theorem.
- Apply CAP Theorem in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Eventual Consistency
Core concepts, implementation patterns, engineering trade-offs and production considerations for Eventual Consistency.
- Explain the core concepts and architecture of Eventual Consistency.
- Apply Eventual Consistency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Backpressure Concepts
=====================================
- Explain the core concepts and architecture of Backpressure Concepts.
- Apply Backpressure Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Applied engineering phase: System Design Cases.
System Design Cases
=====================================; Students design:; URL Shortener; Payment Service; Notification Service; Order Management System; Ticket Booking System; Rate Limiter; File Upload Service; Authentication Service; Audit Logging System; Messaging Platform; E-Commerce Backend
- Explain the core concepts and architecture of System Design Cases.
- Apply System Design Cases in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Applied engineering phase: Production Troubleshooting.
Production Troubleshooting
=====================================; This should be one of the strongest modules.; Scenario 1; Application won't start.; Investigate:; configuration; dependency; database; secret; port; memory; Scenario 2; API latency rises from 100ms to 5 seconds.; downstream dependency; connection pool; threads; JVM; network; Scenario 3; CPU usage = 100%.; hot loops; thread contention; serialization; excessive GC; Scenario 4; Heap keeps increasing.; object retention; caches; listeners; thread locals; static references; Scenario 5; Database connections exhausted.; leaked connections; long transactions; slow queries; pool configuration; Scenario 6; Kafka consumer lag grows.; processing speed; partitions; downstream DB; errors; rebalances; Scenario 7; Users occasionally receive duplicate orders.; retries; idempotency; transaction boundaries; duplicate events; Scenario 8; New deployment causes 30% errors.; Decision:; rollback; analyze; remediate; redeploy
- Explain the core concepts and architecture of Production Troubleshooting.
- Apply Production Troubleshooting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 570–577: Reactive Principles, Backpressure, Reactor Concepts, Mono, Flux, Spring WebFlux, Blocking vs Non-Blocking, When Reactive Architecture Makes Sense.
Reactive Principles
Core concepts, implementation patterns, engineering trade-offs and production considerations for Reactive Principles.
- Explain the core concepts and architecture of Reactive Principles.
- Apply Reactive Principles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Backpressure
Core concepts, implementation patterns, engineering trade-offs and production considerations for Backpressure.
- Explain the core concepts and architecture of Backpressure.
- Apply Backpressure in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reactor Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Reactor Concepts.
- Explain the core concepts and architecture of Reactor Concepts.
- Apply Reactor Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mono
Core concepts, implementation patterns, engineering trade-offs and production considerations for Mono.
- Explain the core concepts and architecture of Mono.
- Apply Mono in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Flux
Core concepts, implementation patterns, engineering trade-offs and production considerations for Flux.
- Explain the core concepts and architecture of Flux.
- Apply Flux in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Spring WebFlux
Core concepts, implementation patterns, engineering trade-offs and production considerations for Spring WebFlux.
- Explain the core concepts and architecture of Spring WebFlux.
- Apply Spring WebFlux in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Blocking vs Non-Blocking
Core concepts, implementation patterns, engineering trade-offs and production considerations for Blocking vs Non-Blocking.
- Explain the core concepts and architecture of Blocking vs Non-Blocking.
- Apply Blocking vs Non-Blocking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
When Reactive Architecture Makes Sense
=====================================
- Explain the core concepts and architecture of When Reactive Architecture Makes Sense.
- Apply When Reactive Architecture Makes Sense in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Applied engineering phase: Graalvm / Native Image Awareness.
Graalvm / Native Image Awareness
=====================================; Current Spring Boot 4.1.1 supports native-image workflows using GraalVM 25+. ([Home][7]); Topics:; JVM deployment vs native binary; startup time; memory footprint; build complexity; compatibility considerations
- Explain the core concepts and architecture of Graalvm / Native Image Awareness.
- Apply Graalvm / Native Image Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules 578–583: LLM API Integration, Structured Output, Tool Calling Concepts, Embeddings Concepts, RAG Concepts, Spring AI Awareness.
LLM API Integration
Core concepts, implementation patterns, engineering trade-offs and production considerations for LLM API Integration.
- Explain the core concepts and architecture of LLM API Integration.
- Apply LLM API Integration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Structured Output
Core concepts, implementation patterns, engineering trade-offs and production considerations for Structured Output.
- 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 Calling Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Tool Calling Concepts.
- Explain the core concepts and architecture of Tool Calling Concepts.
- Apply Tool Calling Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Embeddings Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for Embeddings Concepts.
- Explain the core concepts and architecture of Embeddings Concepts.
- Apply Embeddings Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RAG Concepts
Core concepts, implementation patterns, engineering trade-offs and production considerations for RAG Concepts.
- Explain the core concepts and architecture of RAG Concepts.
- Apply RAG Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Spring AI Awareness
Mini Project; Java AI Support Knowledge API; =====================================
- Explain the core concepts and architecture of Spring AI Awareness.
- Apply Spring AI Awareness 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.
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| 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) |
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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.
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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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