Java Backend Engineer Interview

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Java Core (20 points)

Understanding of OOP principles: Encapsulation, Inheritance, Polymorphism, Abstraction.
Generics in Java: Use of type parameters, bounded types, and wildcard generics.
Multithreading in Java: Creating threads, thread lifecycle, and inter-thread communication.
JVM memory management: Heap, Stack, PermGen/Survivor spaces, garbage collection algorithms.
Exception handling: Checked and unchecked exceptions, try-catch blocks, finally, and multi-catch.
Serialization in Java: Serializable interface, custom serialization with writeObject and readObject.
Java Collections Framework: List, Set, Map, Queue interfaces and their implementations.
Lambda expressions and functional interfaces: Using predicates, consumers, suppliers, and functions.
Stream API: Intermediate and terminal operations, parallel streams, and stream pipelining.
Reflection API: Accessing classes, methods, and fields at runtime, annotation processing.
Java IO vs NIO: Differences in file handling, channel-based I/O, and non-blocking I/O.
Java Date and Time API: Working with LocalDate, LocalDateTime, and Duration.
Java Networking: Socket programming, URL connections, and HTTP clients.
Java Security: Cryptography, digital signatures, and secure coding practices.
Java Modules: Understanding of JPMS (Java Platform Module System) and modularity.
Java Enumerations: Use of enums, ordinal values, and custom methods in enums.
Java Annotations: Built-in annotations, custom annotations, and annotation processing.
Java Concurrency Utilities: CountDownLatch, CyclicBarrier, Semaphore, and Exchanger.
Java Memory Leaks: Causes, detection, and prevention strategies.
Java Performance Tuning: JVM options, profiling tools, and memory optimization techniques.

Spring Ecosystem (20 points)

Spring IoC container: Dependency injection, bean lifecycle, and scope.
Spring Boot auto-configuration: How Spring Boot automatically configures beans.
Spring Data JPA: Repository patterns, CRUD operations, and query methods.
Spring Security: Authentication, authorization, and securing REST APIs.
Spring MVC: Controller methods, request mapping, and view resolution.
Spring Cloud: Service discovery with Eureka, load balancing with Ribbon.
Spring AOP: Aspect Oriented Programming, cross-cutting concerns, and advice types.
Spring Boot Actuator: Monitoring endpoints, health checks, and metrics collection.
Spring Profiles: Environment-specific configurations and profile activation.
Spring Boot Starter Dependencies: Use of starters to simplify dependency management.
Spring Integration: Integrating different systems, messaging, and adapters.
Spring Batch: Batch processing, job scheduling, and step implementations.
Spring Cache: Caching strategies, annotations, and cache managers.
Spring WebFlux: Reactive programming, non-blocking I/O, and WebFlux frameworks.
Spring Cloud Config: Centralized configuration management for microservices.
Spring Cloud Gateway: API gateway patterns, routing, and filtering.
Spring Boot Testing: Using @SpringBootTest, MockMvc, and TestRestClient.
Spring Data REST: Exposing repositories as RESTful services.
Spring Cloud Stream: Integration with message brokers like RabbitMQ and Kafka.
Spring Cloud Sleuth: Distributed tracing and logging in microservices.

Microservices Architecture (20 points)

Service Discovery: How Eureka, Consul, and Zookeeper work.
API Gateway: Patterns, routing, and security in API gateways.
Circuit Breaker: Implementing resilience with Hystrix, Resilience4j.
Event-Driven Architecture: Event sourcing, message brokers, and event handlers.
RESTful API Design: HATEOAS, stateless design, and REST constraints.
GraphQL: Implementing GraphQL APIs, schema definitions, and resolvers.
Microservices Communication: Synchronous vs asynchronous communication.
Saga Pattern: Managing distributed transactions across services.
Health Checks: Implementing liveness and readiness probes.
Contract First Development: Using Swagger for API contracts.
API Versioning: Strategies for versioning RESTful APIs.
Rate Limiting: Implementing rate limits to prevent abuse.
Circuit Breaker Patterns: Implementing fallbacks and retries.
Microservices Deployment: Using Docker, Kubernetes, and cloud platforms.
Service Mesh: Understanding Istio, Linkerd, and their benefits.
Event Collaboration: Saga vs Choreography patterns.
Microservices Security: OAuth2, JWT, and API gateways.
Monitoring and Tracing: Tools like Prometheus, Grafana, and Jaeger.
Microservices Testing: Integration testing, contract testing, and end-to-end testing.
Database per Service: Data management and consistency in microservices.

Databases and Caching (20 points)

SQL Joins: Inner, outer, left, right, and cross joins.
ACID Properties: Atomicity, Consistency, Isolation, Durability in transactions.
NoSQL Databases: Document stores, key-value stores, and graph databases.
Redis Caching: In-memory data store, data structures, and persistence options.
Memcached vs Redis: Comparing caching solutions.
Database Sharding: Horizontal partitioning and load balancing.
ORM Frameworks: Hibernate, MyBatis, and JPA specifications.
JDBC Connection Pooling: DataSource implementations and connection lifecycle.
Full-Text Search: Implementing search in databases like Elasticsearch.
Time-Series Databases: InfluxDB, OpenTSDB for time-based data.
Transaction Isolation Levels: Read uncommitted, read committed, repeatable read, serializable.
Indexing Strategies: B-tree, hash indexes, and composite indexes.
Database Replication: Master-slave, master-master setups.
Database Backup and Recovery: Strategies for data protection.
Database Profiling: Tools like SQL Profiler, slow query logs.
NoSQL Consistency Models: Eventual consistency, CAP theorem.
Database Migrations: Using Flyway, Liquibase for schema changes.
Caching Strategies: Cache-aside, read-through, write-through patterns.
Cache Invalidation: Managing cache expiration and invalidation.
Database Connection Pooling: HikariCP, Tomcat JDBC pool configurations.

Concurrency and Multithreading (20 points)

Thread Lifecycle: New, runnable, running, blocked, waiting, terminated.
Synchronization Mechanisms: Locks, synchronized blocks, and intrinsic locks.
Reentrant Locks: Benefits over synchronized blocks, fairness, and timeouts.
Executor Framework: ThreadPoolExecutor, ExecutorService, and thread pool configurations.
Callable vs Runnable: Differences and use cases.
Java Memory Model: Visibility, happens-before relationships, and memory consistency.
Volatile Keyword: Ensuring visibility of variable changes across threads.
Deadlock Prevention: Avoiding and detecting deadlocks.
Asynchronous Programming: Using CompletableFuture for non-blocking operations.
ScheduledExecutorService: Scheduling tasks with fixed rates and delays.
Thread Pools: Fixed, cached, and scheduled thread pools.
Lock Striping: Reducing lock contention with striped locks.
Read-Write Locks: Allowing multiple readers or a single writer.
Wait and Notify Mechanisms: Inter-thread communication using wait/notify.
Thread Interruption: Handling interrupts and designing interruptible tasks.
Thread-Safe Classes: Implementing thread-safe singleton patterns.
Concurrency Utilities: CountDownLatch, CyclicBarrier, Semaphore.
Java 8+ Concurrency Features: Parallel streams, fork-join framework.
Multicore Programming: Challenges and solutions for parallel processing.
Thread Dumps and Analysis: Identifying issues with thread dumps.

Web Servers and Load Balancing (20 points)

Apache Tomcat Configuration: Setting up connectors, context.xml, and server.xml.
Nginx as Reverse Proxy: Configuring proxy_pass, upstream servers, and load balancing.
HAProxy for High Availability: Setting up failover and session persistence.
Web Server Security: SSL/TLS configurations, security headers, and firewall rules.
Load Balancing Algorithms: Round Robin, Least Connections, IP Hash.
Server-Side Caching: Using Varnish, Redis, or in-memory caches.
Monitoring Tools: Using Prometheus, Grafana, and New Relic for server monitoring.
Logging in Production: Centralized logging with ELK stack or Graylog.
Horizontal vs Vertical Scaling: Understanding trade-offs and use cases.
Web Server Performance Tuning: Adjusting worker threads, connection timeouts, and buffers.
Reverse Proxy Caching: Configuring cache headers and expiration.
Web Server Load Testing: Tools like Apache JMeter, Gatling for performance testing.
SSL Offloading: Handling SSL/TLS termination at the load balancer.
Web Server Hardening: Security best practices and vulnerability assessments.
Dynamic vs Static Content Serving: Optimizing server configurations.
Web Server Clustering: Setting up clusters for high availability.
Web Server Authentication: Implementing basic, digest, and OAuth authentication.
Web Server Logging Formats: Common log formats and parsing tools.
Web Server Resource Limits: Configuring limits on connections, requests, and bandwidth.
Web Server Backup and Recovery: Strategies for disaster recovery.

CI/CD and DevOps (20 points)

Jenkins Pipeline as Code: Writing Jenkinsfiles for CI/CD pipelines.
Docker Containerization: Dockerfile creation, multi-stage builds, and container orchestration.
Kubernetes Orchestration: Deployments, services, pods, and scaling strategies.
GitOps Principles: Using Git for infrastructure and configuration management.
Maven and Gradle Build Tools: Dependency management, plugins, and build lifecycle.
Unit and Integration Testing: Writing tests with JUnit, Mockito, and TestNG.
Code Coverage Tools: Using Jacoco for measuring code coverage.
Static Code Analysis: Tools like SonarQube for code quality checks.
Infrastructure as Code (IaC): Using Terraform, CloudFormation for infrastructure provisioning.
Blue/Green Deployments: Minimizing downtime during deployments.
Canary Deployments: Gradual rollout of new features.
Automated Testing in CI Pipelines: Integrating tests with build stages.
Environment Management: Using Ansible, Chef, or Puppet for configuration management.
CI/CD Best Practices: Continuous integration, continuous deployment, and continuous delivery.
Rollback Strategies: Implementing automated rollbacks on deployment failures.
Security Scanning: Incorporating security checks like SAST, DAST in pipelines.
CI/CD Pipelines for Microservices: Managing pipelines for multiple services.
Monitoring CI/CD Pipelines: Alerting on pipeline failures and performance issues.
DevOps Tools Ecosystem: Understanding tools like Docker, Kubernetes, Jenkins, Ansible.
CI/CD for Cloud-Native Applications: Deploying applications on cloud platforms.

Design Patterns and Best Practices (20 points)

Singleton Pattern: Implementing thread-safe singletons.
Factory Pattern: Creating objects without specifying the exact class.
Strategy Pattern: Encapsulating algorithms and switching between them.
SOLID Principles: Understanding and applying Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, Dependency Inversion.
Dependency Injection: Reducing coupling and increasing code maintainability.
Event Sourcing Pattern: Storing events to reconstruct application state.
CQRS Architecture: Separating command and query responsibilities.
Designing for Scalability: Using horizontal scaling, sharding, and load balancing.
Code Refactoring Techniques: Extracting methods, renaming variables, and simplifying conditionals.
Clean Code Practices: Writing readable, maintainable, and self-documenting code.
Test-Driven Development (TDD): Writing tests before implementation.
Code Versioning: Using Git branching strategies like GitFlow, Trunk-Based Development.
Designing for Maintainability: Using modular design, separation of concerns.
Anti-Patterns to Avoid: God classes, spaghetti code, and tight coupling.
Designing for Security: Implementing least privilege, defense in depth.
Designing for Performance: Optimizing algorithms, reducing I/O operations.
Designing for Reliability: Implementing redundancy, fault tolerance, and error handling.
Designing for Extensibility: Using plugins, extensions, and open APIs.
Designing for Usability: Ensuring APIs are intuitive and well-documented.
Designing for Testability: Writing code that is easy to test and mock.

Security (20 points)

OAuth2 and JWT: Implementing token-based authentication.
Role-Based Access Control (RBAC): Assigning roles and permissions to users.
Security Headers: Implementing Content Security Policy, X-Frame-Options.
SQL Injection Prevention: Using prepared statements and parameterized queries.
Cross-Site Scripting (XSS) Protection: Sanitizing inputs and outputs.
Encryption and Decryption: Using AES, RSA for data protection.
Secure Coding Practices: Avoiding common vulnerabilities like buffer overflows.
Implementing Audit Trails: Logging user actions and system events.
Handling Sensitive Data: Storing passwords securely with hashing algorithms.
Compliance with Regulations: GDPR, PCI-DSS, and data protection laws.
Implementing Two-Factor Authentication (2FA): Adding an extra layer of security.
Security Testing: Penetration testing, vulnerability assessments.
Secure Communication Protocols: Implementing SSL/TLS for data encryption.
Secure Session Management: Managing session tokens and timeouts.
Implementing Web Application Firewalls (WAF): Protecting against common attacks.
Security Monitoring and Alerting: Using tools like SIEM for threat detection.
Security Best Practices in Microservices: Securing service-to-service communication.
Implementing CAPTCHA for Bot Protection: Preventing automated attacks.
Security in CI/CD Pipelines: Scanning for vulnerabilities during builds.
Implementing Security by Design: Incorporating security from the start of the development process.

Performance Tuning and Optimization (20 points)

Profiling Java Applications: Using tools like JProfiler, VisualVM for performance analysis.
Garbage Collection Tuning: Adjusting GC parameters for performance.
Database Query Optimization: Indexing, query rewriting, and using explain plans.
Caching Strategies: Using distributed caches, cache invalidation mechanisms.
Load Testing and Stress Testing: Identifying performance bottlenecks.
Optimizing RESTful APIs: Reducing response times, minimizing data transfer.
Reducing Network Latency: Using CDNs, optimizing API calls.
Connection Pool Sizing: Determining optimal pool sizes for databases and connections.
Monitoring and Alerting Setups: Using Prometheus, Grafana for real-time monitoring.
Identifying and Resolving Bottlenecks: Profiling CPU, memory, and I/O usage.
Optimizing Java Heap Settings: Setting appropriate heap sizes for different environments.
Reducing Garbage Collection Pauses: Using G1GC, ZGC for low-latency applications.
Optimizing Disk I/O: Using SSDs, RAID configurations, and file system optimizations.
Caching vs Storing: Deciding when to cache data versus storing it in a database.
Optimizing Logging: Reducing logging overhead and managing log volumes.
Optimizing Concurrent Access: Using locks efficiently and minimizing contention.
Profiling Memory Usage: Identifying memory leaks and optimizing object allocations.
Optimizing Thread Pool Sizes: Balancing between too few and too many threads.
Optimizing Data Structures: Choosing the right data structures for specific use cases.
Performance Metrics and KPIs: Defining and tracking key performance indicators for applications.

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