Spring Boot microservices interview prep

Explain the key differences between monolithic and microservices architectures, including benefits and challenges.

Apply Domain-Driven Design (DDD) concepts, like Bounded Context, to define service boundaries from a sample monolith.

Apply the Single Responsibility Principle (SRP) to refine and validate proposed microservice boundaries.

Explain the twelve-factor app methodology for building cloud-native applications.

Describe strategies for migrating from monoliths to microservices, including the strangler fig pattern.

Implement health check endpoints using Spring Boot Actuator for service monitoring.

Configure application properties for different environments using Spring profiles.

Implement standardized error responses across a service using global exception handlers (@ControllerAdvice).

Explain the trade-offs between synchronous and asynchronous communication patterns.

Implement declarative synchronous communication using OpenFeign, including timeout and retry configurations.

Implement asynchronous, non-blocking communication using WebClient.

Explain the role of a service registry and compare client-side vs. server-side discovery patterns.

Implement an API Gateway using Spring Cloud Gateway for routing, rate limiting, and request transformation.

Implement the Circuit Breaker pattern with a fallback mechanism using Resilience4j to prevent cascading failures.

Implement the Retry pattern with exponential backoff and jitter using Resilience4j to handle transient faults.

Implement the Bulkhead pattern using Resilience4j to isolate service dependencies and prevent resource exhaustion.

Explain the benefits and trade-offs of event-driven architecture (EDA) in microservices.

Implement event publishers and consumers for Apache Kafka using Spring Cloud Stream.

Explain the role of a schema registry and compare the trade-offs of using JSON vs. Avro for event serialization.

Implement a backward-compatible schema change for an Avro-serialized event using a schema registry.

Configure Kafka partitions and consumer groups for scalable parallel processing with message ordering guarantees.

Implement idempotent message consumers to ensure events can be processed multiple times without side effects.

Configure a Dead-Letter Topic (DLT) in Kafka for handling poison messages after exhausted retries.

Describe the differences between RabbitMQ (queues) and Kafka (logs) and when to choose one over the other.

Explain the database-per-service pattern and its data consistency challenges.

Compare choreography vs. orchestration patterns for coordinating microservices, including their trade-offs.

Design a saga flow for a distributed transaction, outlining events and compensation logic.

Implement a choreographed saga using events for the 'happy path' and compensating transactions.

Implement an orchestrated saga using a central service to manage command and compensation flows.

Explain the CQRS pattern and its use cases for optimizing read/write workloads.

Implement the command side of a CQRS system to handle state changes and the query side to expose denormalized read models.

Analyze the trade-offs of eventual consistency and describe strategies to mitigate user-experience issues.

Explain the thread-per-request model and its scalability limitations.

Identify potential race conditions in concurrent code and resolve them using thread-safe constructs (e.g., ReentrantLock, Atomic classes).

Analyze a thread dump to identify a deadlock and explain deadlock prevention strategies like lock ordering.

Explain the core principles of reactive programming, including non-blocking I/O and backpressure.

Implement non-blocking REST controllers using Spring WebFlux (Mono/Flux) for high-concurrency scenarios.

Implement the cache-aside pattern using Redis with Spring caching annotations (@Cacheable, @CacheEvict).

Describe advanced caching patterns, including write-through, write-behind, and eviction policies.

Design a multi-level caching strategy for a high-traffic, read-heavy service.

Explain the OAuth 2.0 framework, including roles (Resource Owner, Client, etc.) and common grant types.

Set up a Spring Authorization Server and register an OAuth2 client with support for the authorization_code grant type.

Secure a microservice by configuring it as a Resource Server to validate JWT access tokens.

Implement JWT token validation at the API Gateway for centralized authentication.

Compare different strategies for inter-service authentication (e.g., service-to-service JWTs, mTLS).

Describe strategies for secrets management in a microservices environment (e.g., HashiCorp Vault, cloud provider KMS).

Implement symmetric encryption for sensitive properties in a configuration repository and configure clients for decryption.

Explain the role of mutual TLS (mTLS) in securing service-to-service communication.

Set up a Spring Cloud Config Server to serve centralized configuration from a Git repository.

Implement dynamic configuration refresh using Spring Cloud Bus to update properties without a service restart.

Implement structured logging with correlation IDs for end-to-end request troubleshooting.

Implement distributed tracing using Micrometer Tracing and Zipkin to track requests across services.

Configure custom application metrics using Micrometer and expose them in Prometheus format.

Set up Prometheus to scrape metrics and write basic PromQL queries to analyze them.

Define Service Level Indicators (SLIs), Objectives (SLOs), and implement alerting rules in Prometheus.

Interpret distributed traces in Zipkin to identify and diagnose performance bottlenecks in a request flow.

Implement unit tests for a Spring Boot microservice using JUnit and Mockito to isolate component behavior.

Implement integration tests using Testcontainers to validate interactions with external dependencies like databases or message brokers.

Explain the concept of the Test Pyramid and how it applies to a microservices architecture.

Describe the purpose and benefits of consumer-driven contract testing.

Write a consumer-driven contract for a REST API using Spring Cloud Contract.

Implement a provider-side verification test based on a contract generated by Spring Cloud Contract.

Implement a mock server in consumer-side tests based on a contract to enable isolated development.

Compare the roles of integration tests and contract tests in a CI/CD pipeline.

Explain the benefits of containerization for microservices development and deployment.

Create optimized Dockerfiles for Spring Boot microservices using multi-stage builds.

Describe and apply image tagging strategies (e.g., semantic versioning, Git SHA) for production versioning.

Use Docker Compose to launch and network multiple microservices and their dependencies (e.g., database, broker) for local development.

Implement health checks in a Docker container to ensure container reliability and inform the container runtime.

Configure a Spring Boot application to correctly read environment variables and secrets passed by a container runtime.

Build and push a Docker image to a container registry (e.g., Docker Hub, ECR, GCR).

Debug a running container by accessing its shell, viewing logs, and inspecting its network.

Explain the fundamental architecture of Kubernetes, including the control plane, worker nodes, and Pods.

Implement a Kubernetes Deployment to manage application replicas and perform rolling updates for zero-downtime deployments.

Expose applications using different Kubernetes Service types (ClusterIP, NodePort, LoadBalancer).

Implement HTTP routing to services using an Ingress controller and Ingress resources.

Externalize application configuration using ConfigMaps and inject sensitive data using Secrets.

Implement liveness and readiness probes for automated container health management.

Configure resource requests and limits for containers to ensure Quality of Service (QoS).

Explain the purpose of Helm as a package manager for Kubernetes and describe the structure of a Helm chart.

Create a basic Helm chart to package and deploy a Spring Boot microservice on Kubernetes.

Manage application releases using Helm commands, including install, upgrade, and rollback.

Design a CI/CD pipeline for a microservice, including build, test, containerize, and deploy stages.

Implement a CI/CD pipeline using Jenkins or GitLab CI to automatically deploy a microservice to Kubernetes.

Implement a blue-green deployment strategy using Kubernetes service selectors.

Implement a canary release strategy for a microservice using traffic splitting (e.g., with Ingress or a service mesh).

Describe strategies for handling database schema migrations in a zero-downtime deployment context (e.g., expand/contract pattern).

Implement feature flags within a Spring Boot application to decouple feature releases from deployments.

Decompose a complex system (e.g., e-commerce platform) into microservices by applying the bounded context pattern.

Design API contracts and choose appropriate communication patterns for key inter-service interactions.

Select and justify data management strategies (e.g., CQRS, event sourcing) for different services within the system.

Explain how a service mesh (e.g., Istio) enhances observability, security (mTLS), and traffic management.

Compare the roles and trade-offs of using an API Gateway versus a service mesh.

Analyze the root cause of a simulated production incident by correlating logs, metrics, and traces.

Describe a holistic observability strategy for production, incorporating centralized logging, metrics, alerting, and tracing.

Describe common disaster recovery strategies, including multi-region deployment and data backup plans.