In-Depth Understanding

For a deeper dive into Spring Boot and related areas, especially for senior or more specialized roles, you’ll want to cover more advanced topics. Here’s an extended list that builds upon the basics, giving you more in-depth areas to focus on:

1. Advanced Spring Core Concepts

Bean Scopes and Proxies: In-depth understanding of bean scopes (singleton, prototype, request, session) and how Spring manages these in different contexts.
Custom Bean Post Processors: Implementing and using custom BeanPostProcessor and BeanFactoryPostProcessor.
Profile-specific Beans: Managing environment-specific beans using @Profile and @Conditional.
Annotation-based Configuration vs XML-based Configuration: How to mix and match.
Lazy Initialization: Configuring and optimizing lazy loading of beans.
Circular dependencies in Spring and how to handle them.

2. Advanced Spring Boot Customizations

Customizing Auto-Configuration: Creating custom auto-configurations with conditions (@ConditionalOnProperty, @ConditionalOnMissingBean, etc.).
Customizing Spring Boot Starters: Writing custom starter modules for Spring Boot.
Custom Health Indicators for Spring Boot Actuator: Implementing custom health checks for external services (e.g., databases, third-party APIs).
Customizing Spring Boot Error Handling: Using ErrorController, custom error pages, and error attributes.

3. Advanced Security

Custom Security Filters: Writing custom filters that extend Spring Security filters.
JWT Token Enhancements: Refresh tokens, access token expiry management, token revocation.
OAuth2 Advanced Features: Token relay, OAuth2 clients, and resource servers.
Security Context Propagation: Understanding how security context is propagated across threads in reactive and non-reactive applications.
SAML Integration: Implementing single sign-on (SSO) using SAML with Spring Security.
Role Hierarchy: Configuring and understanding complex role hierarchies.

4. Reactive Programming with Spring WebFlux

Deep Dive into Mono and Flux: Error handling, retries, and combining reactive streams.
Backpressure: How Spring WebFlux deals with backpressure and using operators like onBackpressureBuffer.
Non-blocking I/O: Understanding how reactive programming eliminates the need for blocking threads.
Reactive Database Access: Using R2DBC or reactive NoSQL support with MongoDB.
Reactive Security: Securing reactive web applications with Spring Security.

5. Advanced Data Handling with Spring Data JPA

Entity Graphs: Optimizing queries with JPA Entity Graphs to avoid N+1 select issues.
Caching Entities: Using second-level caching with Hibernate, EhCache, or Redis.
Locking Mechanisms: Optimistic and pessimistic locking strategies in Spring Data JPA.
Soft Deletes: Implementing and managing soft delete functionality with JPA and Hibernate.
Advanced Querying with Criteria API: Writing dynamic queries using the Criteria API.
Custom Repositories: Extending Spring Data JPA repositories with custom implementations.

6. Event-Driven Architecture

Spring Application Events: Using and extending Spring’s event system for decoupled communication.
Custom Events: Creating and publishing custom application events.
Transactional Events: Ensuring events are published only after the successful completion of a transaction.
Domain Events: Implementing Domain-Driven Design (DDD) with events and event sourcing.

7. Spring Batch

Spring Batch Architecture: Understanding job repository, job launcher, step, chunk-oriented processing.
Fault-tolerant Batch Jobs: Retry, skip, and rollback scenarios.
Partitioning: Running large jobs by partitioning the data.
Remote Chunking: Scaling Spring Batch using remote chunking.
Job Scheduling: Scheduling batch jobs with Spring’s Task Scheduler or Quartz.

8. Advanced Microservices

Saga Pattern: Implementing long-running transactions across multiple microservices (Orchestration vs Choreography).
Event Sourcing and CQRS: Using event sourcing and Command Query Responsibility Segregation (CQRS) for distributed data.
Distributed Locking: Handling distributed locking using Redis, Zookeeper, or Hazelcast.
Service Mesh: Understanding and integrating Istio or Linkerd for microservices traffic management.
API Gateway Patterns: Centralizing APIs through Spring Cloud Gateway and managing routing, load balancing, and security at the edge.

9. Advanced Messaging

Kafka Streams: Working with Kafka Streams for real-time data processing.
Transaction Management with Messaging: Managing transactional messaging using Kafka, RabbitMQ, or JMS.
Message Ordering and Idempotency: Ensuring message consistency and handling duplicate messages.
Message-driven Microservices: Using Spring Cloud Stream for integrating event-driven microservices.

10. Performance Tuning

Memory Management: Understanding JVM memory management (heap, stack, garbage collection) and tuning parameters.
Profiling Spring Applications: Using tools like VisualVM, JProfiler, or YourKit to analyze application performance.
Database Optimization: Using tools like Hibernate Statistics, SQL execution plans, and query tuning for performance optimization.
Load Testing: Using tools like Gatling, JMeter, or BlazeMeter to simulate high load and measure performance.

11. Distributed Systems Patterns

CAP Theorem: Understanding trade-offs between consistency, availability, and partition tolerance.
Distributed Transactions: Using XA Transactions, 2PC (Two-Phase Commit), or TCC (Try-Confirm/Cancel).
Consistency Patterns: Strong vs Eventual Consistency in distributed systems.
Circuit Breaker Design Patterns: Deep dive into Hystrix or Resilience4j to ensure resilience in distributed systems.

12. Containerization and Kubernetes

Docker Internals: Understanding containerization, multi-stage builds, networking, and storage in Docker.
Kubernetes Configurations: Helm charts, StatefulSets, and Kubernetes deployment patterns (Blue-Green, Canary).
Service Mesh in Kubernetes: Managing traffic routing, load balancing, and security with Istio/Linkerd.
Scaling Spring Boot applications: Horizontal vs vertical scaling in a cloud-native environment.

13. Serverless Architectures

AWS Lambda with Spring Cloud Function: Writing serverless functions using Spring Boot.
Event-driven serverless applications: Integrating AWS Lambda, SQS, SNS, or other cloud-native services.
Cold Start Mitigations: Techniques for reducing latency in serverless functions.

14. API Gateway Patterns

API Gateway Routing: Using Spring Cloud Gateway to route requests dynamically.
Security at the API Gateway level: Token propagation, rate limiting, throttling.
Custom Filters and Predicates: Creating custom logic at the gateway layer for microservices.

15. Advanced Error Handling

Global Error Handling: Creating a unified error response strategy across REST APIs and microservices.
Fault Tolerance: Implementing retry, timeout, and fallback mechanisms with tools like Resilience4j.
Circuit Breaker Fine Tuning: Advanced configuration of circuit breakers for microservices resilience.

Covering these advanced topics will give you deep insight into Spring Boot development, performance optimization, microservices architecture, and distributed systems, preparing you for more senior roles or specialized interviews.

In Depth Spring Boot Concepts