Most recently asked Java Backend Microservice interview Questions for Preparing Cognizant Java Backend Microservice interview. You must know real-world distributed systems, internal API communication, fault tolerance, cloud-native deployment, and production-grade Spring Boot patterns.

In this guide, I cover the 8 most repeatedly asked and high-impact Cognizant Java Microservices Interview Questions. These questions are specifically targeted at experienced developers (3–10 years) and reflect what Cognizant asks in system design + backend round.

1. How Does Internal Service-to-Service Communication Work in Microservices, and How Do You Configure It Effectively?

When moving from monolithic architecture to microservices, the biggest shift is how services communicate. Internal calls that once happened in memory now travel over the network — bringing flexibility but also failures, latency, and security challenges.

Microservices communicate in two ways:

A. Synchronous Communication (Request-Response)

Technologies: REST (JSON), gRPC
Examples:

• Service A → Service B (REST over HTTP)
• High-throughput internal RPC (gRPC)

Pros: Simple, immediate response
Cons: Tightly coupled, cascading failures, timeout issues

B. Asynchronous Communication (Event-Based)

Technologies: Kafka, RabbitMQ
Patterns: Publish/Subscribe, Event Sourcing

Pros: Loose coupling, high resilience, better throughput
Cons: Harder debugging, eventual consistency challenges

End-to-End Flow of Synchronous Call:

1. Client hits the API Gateway → Auth, rate limiting
2. Gateway routes request to target service
3. Service receives the request → New trace span created
4. Service may call another service via REST/gRPC
5. Uses service discovery (Eureka/K8s DNS)
6. Outbound request sent with propagated headers
7. mTLS/JWT secured internal communication
8. Fault tolerance applied → retry, timeout, circuit breaker
9. Downstream responds
10. Response returned to client
11. Full tracing/logging captured (OpenTelemetry/ELK)

How to Configure Synchronous Communication Effectively

1. Service Discovery (Avoid Hardcoding IPs)

• Netflix Eureka
• Consul
• Kubernetes DNS
• API Gateway internal routing

2. Load-Balanced HTTP Client (Spring Cloud LoadBalancer)

@Bean
@LoadBalanced
public WebClient.Builder webClientBuilder() {
    return WebClient.builder();
}

3. Strict Timeouts Are Mandatory

webClientBuilder.build()
    .get()
    .uri(url)
    .retrieve()
    .bodyToMono(String.class)
    .timeout(Duration.ofSeconds(2));

4. Apply Resilience4j Patterns:

• Circuit Breaker
• Retry
• Bulkhead
• Rate Limiter
• Timeouts

5. Zero-Trust Security Model

• mTLS between services
• Short-lived OAuth2 machine tokens
• DO NOT forward user JWT directly

6. Propagate Context

• X-Request-ID
• traceparent (OpenTelemetry)
• Authorization token (if needed)

7. Observability

Use:

• OpenTelemetry + Jaeger/Zipkin → tracing
• Prometheus + Grafana → metrics
• ELK/OpenSearch → logs

Monitor:

• p95/p99 latency
• error rate
• circuit breaker state
• retry count

2. How Is Eureka Used as a Service Registry? How Do Applications Register and Consume Services?

Eureka is a service registry used to dynamically register and discover microservices.

Eureka Workflow (Simple Version):

1. Billing Service starts
2. Billing registers itself with Eureka
3. Eureka stores its details (IP, port, status)
4. Billing needs Order Service → it calls http://order-service/...
5. Spring Cloud LoadBalancer asks Eureka for healthy instances
6. Eureka returns instance list
7. Load balancer picks one instance
8. Billing sends request
9. Eureka removes unhealthy instances automatically

Eureka in One Simple Analogy

Item	Meaning
Eureka Server	Phonebook
Service	Person listing number
Discovery	Looking up someone

Benefits of Eureka

• No hardcoded URLs
• Auto-registration
• Auto-deregistration of unhealthy services
• Built-in load balancing
• Works well with Spring Cloud

3. What Is Fault Tolerance in Distributed Systems and How Is It Implemented?

In microservices, failure is normal.

A downstream service will eventually:

• timeout
• crash
• overload
• return errors
• respond slowly

Fault tolerance ensures the system stays functional even when parts fail.

Resilience4j Is the Standard Tool

It provides these reliability patterns:

• Retry
• Circuit Breaker
• Bulkhead
• Timeout
• Fallback
• Rate Limiter

Simple Summary

Fault tolerance prevents cascading failures using:

• timeouts
• retries
• circuit breakers
• isolation
• fallbacks

This keeps your system stable, predictable, and recoverable.

4. What Are Lambda Expressions in Java and How Do They Work?

Lambda expressions were introduced in Java 8 to simplify functional-style programming.

Definition

A lambda expression is a short block of code that can be passed around as a function.

Works Only With Functional Interfaces

Interfaces with one abstract method:

• Runnable
• Callable
• Predicate
• Consumer
• Function
• Comparator

Example

Function<Integer, Integer> square = x -> x * x;
System.out.println(square.apply(5));

Top Java 8 Stream API Coding Interview Questions and Answers (With Code) 2026

5. What Are Stored Procedures? Why Are They Used? Where Do They Fit in Application Design?

A stored procedure is a precompiled SQL program stored inside the database.

Why Stored Procedures Are Used

• Performance improvement
• Security (no raw SQL from app)
• Reusability
• Reduced network traffic
• Handle complex multi-step business logic

Where They Fit in Modern Architecture

• Banking/Finance systems
• Bulk updates
• Batch jobs
• Data-intensive operations
• Complex joins/aggregations

Java Example (Calling Stored Procedure)

SimpleJdbcCall call = new SimpleJdbcCall(jdbcTemplate)
        .withProcedureName("GetOrdersByCustomer");

Map<String, Object> params = Map.of("customerId", 101);

Map<String, Object> result = call.execute(params);

6. How to Secure APIs in Spring Boot (JWT, OAuth2, Filters, Role-Based Access)

API security should be multilayered:

JWT Structure

• Header: algorithm, type
• Payload: user details & claims
• Signature: prevents tampering

JWT Workflow

1. User logs in
2. Auth Manager validates credentials
3. Server issues JWT
4. Client stores token
5. Client sends token in every request
6. Resource server validates JWT
7. Authorization (roles/scopes)
8. Token expiry + refresh token

Best Practices

• Use short-lived tokens
• Validate signature on every request
• Store secrets in Vault/KMS
• Never expose internal service tokens to clients
• Implement security filters for logging & rate limiting

7. Describe Your End-to-End Microservices Architecture and Responsibilities

A typical Cognizant-ready answer:

High-Level Architecture

• API Gateway at the edge
• Microservices (Orders, Billing, Catalog, Auth)
• Event streaming via Kafka
• Service discovery (Eureka/Kubernetes DNS)
• DB-per-service pattern
• CI/CD automated pipelines
• Kubernetes/Istio for orchestration and service mesh
• Distributed tracing using OpenTelemetry
• Centralized configuration (Vault/ConfigMaps)

Your Core Responsibilities

• Designing REST/gRPC APIs
• Implementing internal service calls (WebClient/Feign)
• Ensuring resiliency (Resilience4j, retries, CB)
• Implementing Kafka producers/consumers
• Writing unit, integration & contract tests
• Deploying via Jenkins/GitHub Actions → Kubernetes
• Monitoring dashboards and production debugging
• Handling secrets (Vault/ConfigMaps)
• Improving performance, caching, DB tuning

8. How Do You Deploy a Microservice? (CI/CD, Containerization, Orchestration, Config)

Deployment is a multi-stage pipeline.

1. Containerization

Package Spring Boot service as an immutable Docker image.

2. CI/CD Pipeline

CI tasks:

• Unit/Integration tests
• Static code analysis (PMD/SpotBugs)
• Container vulnerability scan
• SBOM generation
• Versioning (Git SHA tags)

CD deployment strategies:

• Rolling updates
• Canary releases
• Blue-Green deployments

3. Orchestration (Kubernetes)

Required components:

• Deployment
• Service
• Ingress
• Autoscaler
• Network policies

4. Configuration Management

Externalize configs using:

• ConfigMaps
• Secrets
• Vault
• Spring Cloud Config

5. Safe Rollouts & Rollbacks

Ensure:

• readiness/liveness probes
• health checks
• observability hooks
• versioned releases

6. Production Essentials

• Prometheus + Grafana dashboards
• Centralized logs
• Alerts, SLOs, on-call readiness
• Resource quotas & limits
• Secure network boundaries

Conclusion

These 8 Cognizant Java Microservices interview questions cover the real core of backend engineering:

• internal communication
• resiliency
• cloud-native deployment
• distributed systems
• security
• architecture
• major Java fundamentals

Mastering these will give you clarity, confidence, and differentiation in Cognizant’s System Design + Java Backend interview rounds.