1. Microservices Architecture 🏗️
- Definition: A software architecture style where applications are composed of small, independent services that communicate over a network.
- Advantages: Scalability, flexibility, independent deployment, resilience, and better fault isolation.
- Challenges: Complexity in management, network latency, distributed data management, and need for strong DevOps practices.
2. Service Discovery 🔍
- Definition: A mechanism to dynamically discover and connect services in a microservices architecture.
- Tools: Eureka (Netflix), Consul (HashiCorp), Zookeeper (Apache).
- Patterns: Client-side discovery, Server-side discovery.
3. API Gateway 🚪
- Definition: An entry point for client requests, routing them to the appropriate services.
- Responsibilities: Request routing, composition, and protocol translation.
- Tools: Kong, NGINX, Zuul (Netflix).
4. Communication Patterns 💬
- Synchronous Communication: Direct service-to-service communication, typically via HTTP/REST or gRPC.
- Asynchronous Communication: Communication via messaging systems like RabbitMQ, Kafka, or AWS SQS.
- Pattern: Request-Response, Event-driven, Publish-Subscribe.
5. Data Management in Microservices 🗄️
- Database per Service: Each service manages its own database schema, promoting data autonomy.
- Challenges: Maintaining data consistency across services, distributed transactions.
- Solutions: Eventual consistency, Saga Pattern, CQRS (Command Query Responsibility Segregation).
6. Circuit Breaker Pattern 🔄
- Definition: A design pattern used to detect failures and encapsulate the logic of preventing a failure from constantly recurring.
- Tools: Hystrix (Netflix), Resilience4j.
- Usage: To prevent cascading failures and improve fault tolerance.
7. Service Resilience & Fault Tolerance 🛡️
- Techniques: Retry logic, timeout settings, fallback methods.
- Patterns: Bulkhead Pattern, Retry Pattern, Timeout Pattern.
- Tools: Hystrix, Resilience4j.
8. API Versioning 📅
- Definition: Managing changes in APIs without breaking existing client implementations.
- Techniques: URI versioning, query parameter versioning, custom headers.
- Strategy: Deprecate old versions and maintain backward compatibility.
9. Monitoring & Logging 🖥️
- Importance: Critical for understanding the behavior and performance of microservices.
- Tools: Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), Zipkin (Distributed tracing).
- Best Practices: Centralized logging, distributed tracing, metrics collection.
10. Security in Microservices 🔐
- Techniques: OAuth2, JWT (JSON Web Tokens) for authentication and authorization.
- Challenges: Securing inter-service communication, managing secrets.
- Tools: Spring Security, Keycloak, Vault (HashiCorp).
11. Containerization & Orchestration 📦
- Containers: Microservices are often deployed in containers for consistency across environments.
- Tools: Docker, Podman.
- Orchestration: Kubernetes for automating deployment, scaling, and operations of containers.
12. Continuous Integration/Continuous Deployment (CI/CD) 🚀
- Importance: Automates the process of testing, building, and deploying microservices.
- Tools: Jenkins, GitLab CI, CircleCI.
- Best Practices: Automated testing, blue-green deployments, canary releases.
13. Event-Driven Microservices 🔔
- Definition: Microservices that communicate through events, allowing loose coupling and scalability.
- Tools: Kafka, RabbitMQ, AWS SNS/SQS.
- Patterns: Event sourcing, CQRS.
14. Domain-Driven Design (DDD) in Microservices 📚
- Definition: An approach to software development that focuses on modeling the business domain.
- Concepts: Bounded Contexts, Aggregates, Entities, Value Objects.
- Usage: Helps in defining service boundaries in a microservices architecture.
15. Testing Strategies 🧪
- Types of Tests: Unit testing, integration testing, contract testing, end-to-end testing.
- Tools: JUnit, TestNG, Postman, WireMock (for mocking services).
- Best Practices: Automation, CI/CD integration, use of test doubles.
Final Tips
- Understand the Basics: Know the core principles of microservices.
- Hands-on Practice: Work with tools like Docker, Kubernetes, and Spring Boot.
- Stay Updated: Microservices evolve quickly; keep up with the latest trends and best practices.
Good luck with your interview!
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