Microservices Interview Questions & Answers

✅ Section 1: Technical Deep Dive

1. What is microservices architecture? How is it different from monolithic architecture?

2. What are the key benefits and challenges of using microservices?

3. How do microservices communicate with each other? What are the pros and cons of synchronous vs asynchronous communication?

4. What is service discovery and how is it implemented?

5. How do you handle data consistency in microservices?

6. Explain the role of API Gateway. What are its common responsibilities?

7. How do you handle versioning of APIs in a microservices ecosystem?

8. How do you secure communication between microservices?

9. What is the role of service mesh in microservices?

10. What are sidecars, and how do they help in microservices deployments?

1. What is microservices architecture? How is it different from monolithic architecture?

Answer:Microservices architecture is an approach where an application is composed of small, loosely coupled, independently deployable services. Each service focuses on a specific business capability and communicates via lightweight protocols (typically HTTP or messaging queues).

Differences:

Monolith	Microservices
Single codebase	Multiple independent services
Tight coupling	Loose coupling
Shared DB	Independent DBs
Hard to scale selectively	Scalable per service
Single point of failure	Resilient and fault-tolerant

2. What are the key benefits and challenges of using microservices?

Benefits:

• Independent deployment

• Technology diversity

• Scalability per service

• Improved fault isolation

• Aligned with Agile/DevOps

Challenges:

• Complexity in distributed systems

• Data consistency

• Inter-service communication

• DevOps sophistication needed

• Testing and monitoring become harder

3. How do microservices communicate with each other?

Answer:

• Synchronous (HTTP/REST, gRPC): Easy to implement, but tightly coupled and prone to cascading failures.

• Asynchronous (Kafka, RabbitMQ): Decoupled, more scalable, resilient, but harder to debug and ensure delivery guarantees.

4. What is service discovery and how is it implemented?

Answer: Service discovery helps microservices locate each other dynamically. Implemented using:

• Client-side discovery (e.g., Netflix Eureka with Ribbon)

• Server-side discovery (e.g., AWS ALB, Consul)

• Service mesh (e.g., Istio + Envoy)

5. How do you handle data consistency in microservices?

Answer:

• Prefer eventual consistency

• Use Saga pattern for long-running transactions (choreography or orchestration)

• Event-driven architecture to propagate state changes

• Avoid distributed transactions if possible

6. Explain the role of API Gateway.

Answer: Acts as a single entry point for client requests. Responsibilities:

• Request routing

• Authentication/Authorization

• Rate limiting

• Logging/Monitoring

• Load balancing

Examples: Kong, NGINX, AWS API Gateway, Spring Cloud Gateway

7. How do you handle API versioning?

Answer:

• URI-based (/api/v1/resource)

• Header-based (Accept: application/vnd.api.v1+json)

• Query param-based (?version=1) Ensure backward compatibility and deprecate carefully.

8. How do you secure communication between microservices?

Answer:

• Use mTLS for service-to-service encryption

• Token-based auth (e.g., JWT, OAuth2)

• API Gateway for auth and rate-limiting

• Use service mesh (e.g., Istio) for consistent policy enforcement

9. What is the role of a service mesh?

Answer: A service mesh handles service-to-service communication transparently. It provides:

• Traffic routing

• Observability

• Security (mTLS)

• Retry, timeout, circuit breaking

Examples: Istio, Linkerd, Consul Connect

10. What are sidecars, and how do they help?

Answer: Sidecars are helper containers deployed alongside application containers (in the same pod) in Kubernetes. They provide:

• Logging

• Service discovery

• Proxies (e.g., Envoy)

• Security (auth, TLS)

✅ Section 2: Architecture & Design Questions

1. Design a microservices-based architecture for a digital banking platform.

Answer:

• Services: Accounts, Payments, Loans, Customer, Auth, Notification

• Communication: REST + Kafka (event-driven)

• DB per service (PostgreSQL, MongoDB)

• API Gateway for aggregation

• CI/CD with Jenkins + Docker + Kubernetes

• Observability: Prometheus, Grafana, ELK

• Security: OAuth2, mTLS, rate limiting

2. How to decompose a monolith into microservices?

Answer:

• Identify business domains → create bounded contexts

• Use Domain-Driven Design (DDD)

• Start with non-critical modules

• Use strangler pattern to gradually replace parts

• Ensure contracts via APIs

3. Design patterns used in microservices?

Answer:

• API Gateway

• Circuit Breaker (e.g., Resilience4j)

• Saga pattern

• CQRS (Command Query Responsibility Segregation)

• Service Registry

• Sidecar & Ambassador

4. How do you handle distributed transactions?

Answer: Avoid 2PC. Use:

• Saga pattern – local transactions + compensating actions

• Eventual consistency via events

• Orchestrator pattern if coordination needed

5. How to ensure observability?

Answer:

• Logging: Centralized via ELK or Fluentd

• Metrics: Prometheus + Grafana

• Tracing: OpenTelemetry, Jaeger, Zipkin

• Dashboards + Alerts: Grafana + Alertmanager

6. CI/CD in microservices ecosystem?

Answer:

• CI: Code → Build → Test → Package (Jenkins, GitHub Actions)

• CD: Deploy to staging/prod (ArgoCD, Spinnaker)

• Containerize each service (Docker)

• Use Kubernetes with Helm charts or Kustomize

7. Handling failures in microservices?

Answer:

• Retries with exponential backoff

• Circuit breaker

• Fallback logic

• Timeouts

• Bulkheads

• Alerting and dashboards

8. How to handle schema evolution?

Answer:

• Use backward/forward-compatible schemas

• Evolve APIs carefully (add new fields, avoid removing required ones)

• For events: use Protobuf/Avro with schema registry

• Implement consumer-first contracts (Consumer-Driven Contracts)

✅ Section 3: Scenario-Based Questions

1. Intermittent service failure in prod?

Approach:

• Check dashboards/logs/alerts

• Use distributed tracing to find root cause

• Check dependencies and external services

• Rollback recent deployments if needed

• Add circuit breaker/fallback if pattern detected

2. Service bottleneck due to high traffic?

Approach:

• Scale horizontally (add pods/instances)

• Optimize code/db queries

• Add caching (e.g., Redis)

• Use rate limiting or throttle non-critical requests

• Offload to async processing (e.g., queue)

3. Fraud detection service needing 4 service integrations?

Answer:

• Use async pub-sub model via Kafka for resilience

• Retry + circuit breakers for external calls

• Aggregate responses if needed using Saga

• Ensure observability

• Cache frequent responses (if possible)

4. Integrate GenAI-based personalization in microservices?

Answer:

• Create a separate AI inference microservice

• Use REST/gRPC to invoke GenAI APIs

• Use RAG (Retrieval Augmented Generation) for contextual responses

• Add monitoring + auto ML model retraining

• Ensure latency control (use async if needed)

5. Migrate legacy credit scoring module to microservices?

Answer:

• Use strangler pattern

• Create new credit scoring microservice in parallel

• Route a subset of traffic for A/B testing

• Ensure data sync

• Gradually increase usage, then retire monolith part