Your Guide to the Top 10 Microservices Interview Questions (with Answers)

Microservices architecture has become the de facto standard for designing scalable, resilient, and sustainable software systems. Organizations from startups to enterprises are quickly moving away from monoliths to microservices. This transition is creating a demand for developers who understand not just the what but also the why and how of microservices.

This architectural style of designing and developing software applications involves dividing an application into various, independent services that are separate and distinct from each other, with each one developed, deployed, and maintained independently. Although there are numerous advantages of using microservices, there are a few drawbacks that need to be taken into account.

Whether you are a fresher developer looking to enter backend development or an experienced developer gearing up for a senior position, learning microservices is essential to differentiate yourself during interviews and contribute positively to contemporary software teams.

Here’s what we’re going to cover in this guide:

Top 10 Microservices interview questions and answers with a focus on experienced professionals

3 easy-to-understand questions and answers to help beginners enter microservices

Tips and best practices sprinkled throughout to give you an edge in real-world interviews

Let’s get started.

Top 10 Microservices Interview Questions and Answers

1. How do you handle communication between microservices?

Answer: There are two main ways:  synchronous (usually by HTTP REST or gRPC) and asynchronous (by messaging queues like RabbitMQ, Kafka, or AWS SNS/SQS).

• Use REST/gRPC when a real-time response is required.
• Use event-driven messaging for decoupling and fault-tolerance.

Here is a tip: In interviews, demonstrate knowledge of event sourcing and CQRS since they are gaining popularity in distributed systems.

2. What database management techniques do you employ in microservices?

Answer: Ideally, every microservice should maintain its database (Database per Service pattern) to achieve loose coupling and data encapsulation. 

For consistency, apply:

• Sagas for handling distributed transactions
• Eventual consistency as a guiding principle
• Change Data Capture (CDC) for synchronizing among services

Tools: Debezium (for CDC), Kafka (for event streaming)

3. How do you make your microservices resilient and fault-tolerant?

Fault tolerance ensures that the system remains functional at all times, enhancing user experience. It also makes things much easier for software teams. 

Answer: Resilience patterns are:

• Circuit Breaker (e.g., Netflix Hystrix, Resilience4j)
• Retry with Backoff
• Bulkheads and Rate Limiting

Example: When Service A relies on Service B, and B is not available, a Circuit Breaker avoids A getting flooded with failed calls and may resort to fallback logic.

4. How do you design and deploy microservices securely?

Answer: Important practices for microservices secure deployment are:

• OAuth2 / JWT for stateless authentication
• Mutual TLS for service-to-service encryption
• API Gateway to secure, rate-limit, and route centrally
• Secrets Management with Vault or AWS Secrets Manager

Here is a tip: Display awareness of zero trust architecture and securing internal APIs, not only external-facing ones.

5. How do you log and monitor across microservices?

Answer: To log and monitor across each microservice, follow these steps. 

• Use centralized logging: ELK Stack (Elasticsearch, Logstash, Kibana) or EFK (Fluentd)

• Use distributed tracing tools such as Jaeger or Zipkin
• Integrate with monitoring tools: Prometheus + Grafana

Here is a tip: Describe the usage of correlation IDs between services to follow end-to-end requests.

6. What are microservices’ challenges, and how do you address them?

Answer: While microservices offer flexibility and modularity, they are not free from challenges. Development teams often face many challenges that might include:

• Data consistency → Utilize event-driven architecture
• Deployment complexity → Implement CI/CD Pipelines and Kubernetes
• Service discovery → Utilize tools such as Consul, Eureka, or K8s DNS
• Versioning → Address through backward-compatible API design or versioned endpoints

7. How do you configure microservices?

Answer: Configuring microservices architecture may include managing and maintaining the settings that control the behavior of each microservice. These settings can include database connections, API keys, feature toggles, and environment-specific configurations. Here are some best practices:

• Utilize centralized config servers (e.g., Spring Cloud Config)
• Use environment-specific configurations using tools such as Kubernetes ConfigMaps and Secrets
• Make configurations immutable in production

Here is a tip: Talk about feature toggles and dynamic configuration reload mechanisms.

8. Describe the role of the API Gateway in microservices?

Answer: An API Gateway is a single entry point to all clients, and offers:

• Routing to suitable services
• Authentication & Authorization
• Rate limiting & Throttling
• Load balancing and Caching

Popular options: Kong, NGINX, AWS API Gateway, Istio (in service mesh)

9. How do you deploy microservices into production?

Answer: Deploying microservices into production typically involves several key steps and considerations to ensure reliability, scalability, and maintainability. You can deploy using container orchestration tools such as Kubernetes or Docker Swarm.

Best practices:

• Blue-Green or Canary Deployments
• Health checks & readiness probes
• Automated rollbacks on failure
• Observability baked into the CI/CD pipeline

10. What is a service mesh, and when do I use one?

Answer: A service mesh is an infrastructure layer that governs service-to-service communication in microservices systems. It takes care of functions such as traffic routing, security, observability, and resiliency, hiding these complexities from individual services. You employ a service mesh when you’re working with a distributed application with lots of microservices and want to handle their interactions effectively and reliably.

(e.g., Istio, Linkerd) is an infrastructure layer that manages:

• Service discovery
• Traffic management
• Security (mTLS)
• Observability (telemetry, tracing)

Use case: When you have lots of services talking to each other internally and want to have uniform governance, security, and resilience without adding additional code in every service.

Here are some Q&A for freshers:

Microservices Questions and Answers for Freshers

1. What is microservices architecture?

Answer: Microservices architecture refers to the design of software as a set of small, stand-alone, deployable services. Every service addresses one business capability, exchanges messages across the network, and can be developed and scaled separately.

2. What are the major benefits of microservices?

Answer: Microservices provide many benefits centered around key areas such as greater agility, shorter development cycles, better scalability, and more robust fault isolation. These are derived from decomposing applications into smaller independent services that can be developed, deployed, and scaled independently.

Major benefits are:

• Scalability: Scale individual services on demand
• Flexibility: Employ various tech stacks per service
• Faster deployments: Independent teams
• Resilience: One service failure doesn’t bring down the entire application

3. How do microservices contrast with monolithic architecture?

Answer: Microservices and monolithic designs are fundamentally different design methodologies for constructing software applications. Monolithic design consists of one, tightly bound codebase, whereas microservices decompose applications into smaller, independent, and loosely coupled services. This difference results in drastic differences in development, deployment, scaling, and fault tolerance.

Aspect	Monolith	Microservices
Deployment	Single unit	Individual services
Scaling	Whole app	Per service
Development	Tightly coupled	Loosely coupled
Technology choice	Uniform	Polyglot possible

Tip for Freshers: Understand the progression from monolith → SOA → microservices.

Bonus Tips for Interview Success

Use real-world experience when answering questions, even small-scale microservices projects or side projects.

Trade-offs: When not to use Microservices

Microservices aren’t a silver bullet. You should know when not to use them. Here is the complete list of reasons when you should not use Microservices Architectures: 

Here are the Anti-Patterns of Microservices:

Don’t do Distributed Monolith

Ensure that you break your services down correctly and adhere to the decoupling principle, such as using bounded context and business capabilities principles.

Don’t implement microservices without DevOps or cloud services

Microservices adopt the distributed cloud-native patterns. And you can only reap the benefits of microservices by adhering to the following cloud-native principles:

Some of them are:

• CI/CD pipeline with DevOps automations
• Correct deployment and monitoring tools
• Managed cloud services to back your infrastructure
• Follow Key enabling technologies and tools such as Containers, Docker, and Kubernetes.
• Broken dependencies with the following async communications using Messaging and event streaming services.

When having limited team sizes, small Teams

If you do not have a team size that can manage the microservice workloads, this would only lead to a delay in delivery. For a small team, a microservice architecture can be difficult to justify, since the team is needed just to deal with the deployment and management of the microservices themselves.

Launching Brand new products or with startups

If you are building a new startup or a completely new product that needs deep change when you build and keep iterating your product, then you should not begin with microservices.

10 Actionable Best Practices for Software Assurance Excellence in 2025

 Quality assurance is a comprehensive, proactive approach that safeguards digital products against errors while elevating security, functionality, and performance. QA specialists work across every stage of development—from requirements gathering to deployment—helping teams deliver flawless applications that meet user and business expectations.

Key Elements of a Strong QA Process

QA processes begin with clear standard definitions, robust planning, and thorough documentation. By establishing benchmarks and leveraging tools like JIRA for tracking, teams maintain transparency, outline responsibilities, and enforce accountability for every step in the testing lifecycle.

10 Best Practices for Software QA

1. Develop a Strategy for Every Product

Each product merits a tailored, business-focused testing strategy. This includes setting goals, identifying risks, mapping the testing process—from ticket preparation to release management—and ensuring collaboration on test automation, integration tests, and documentation.

2. Leverage Artificial Intelligence in Testing

Integrating AI into QA streamlines scenario generation, automated data creation, debugging, coding, documentation, and code explanation. With AI, teams can rapidly boost efficiency and accuracy—yet human expertise remains essential for decision-making and continuous learning.

3. Maintain Rigorous Security Protocols

QA specialists must proactively identify vulnerabilities in user flows, onboarding, and APIs while enforcing secure access controls. Using automated and manual tests, static analysis tools, infrastructure scans, and robust compliance measures ensures user data and privacy remain protected.

4. Prioritize Early Performance Testing

Performance must be thoroughly validated from the earliest development stages. Automated tools like k6 facilitate real-time server and client-side assessments, identifying bottlenecks quickly and promoting scalability and speed.

5. Commit to Accessibility Standards

Accessibility is both a legal requirement and ethical imperative. By employing automated testing tools alongside manual inspections—such as for WCAG and EN 301 549 compliance—QA ensures inclusive software for all users, with early design phase attention and developer training.

6. Optimize User Experience (UX)

QA teams examine user flows, authentication processes, mobile optimization, and front-end performance to guarantee intuitive navigation and robust functionality that keeps users engaged, especially as mobile commerce continues to grow.

7. Introduce Test Automation Early

Automation should complement manual testing from the start, supporting efficient regression checks and extending coverage. Teams collaboratively select tools, distribute responsibilities, and regularly sync on results for consistent quality.

8. Adopt Shift-Left Testing Strategies

Testing earlier in the development cycle allows defects to be identified before deployment. QA engineers collaborate closely with developers on code branches and prototypes, providing fast and actionable feedback for refined solutions.

9. Foster Ownership and Team Proactivity

QA roles extend beyond technical testing. Engineers share responsibility for spotting risks, shaping solutions, and driving constructive collaboration—ensuring continuous improvement and alignment with business goals.

10. Invest in Continuous Education & Growth

As technology evolves, QA professionals must regularly update their skills in emerging tools, frameworks, and communication practices. Developing both technical and soft skills—like meeting management and feedback—is key to long-term effectiveness.

Practical QA Tips for 2025

Tip	Overview
Develop a testing strategy	Build product-specific plans covering goals, process, risks, and collaboration.
Use AI	Deploy AI tools for test creation, debugging, and documentation.
Focus on security	Apply robust API tests, access controls, scans, and compliance checks.
Make test performance early	Test early with automation to catch issues and optimize speed.
Focus on accessibility	Ensure compliance with accessibility standards by combining manual and automated testing.
Prioritize user experience	Test flows, authentication, mobile, and front-end performance for premium UX.
Implement test automation	Start automation early, support manual efforts, and separate responsibilities across teams.
Adopt shift-left testing	Test solutions prior to deployment, providing timely feedback and early defect detection.
Be proactive	Take ownership, work collaboratively, and communicate risks and solutions.
Educate yourself	Continuously update technical and personal skill sets.

Conclusion: Building Reliable Software with Modern QA

Embracing these industry-backed QA Practices—automation, AI, security, accessibility, shift-left collaboration, and ongoing education—empowers teams to deliver digital products that excel in reliability and performance in 2025.

Vulnerability Testing for gRPC APIs: What Every Tester Should Know

As an API developer/tester, you need to ensure your API endpoints are secure and protected from vulnerabilities. Failing to properly test API security can have serious consequences – like data breaches, unauthorized access, and service disruptions.

This blog post will provide you with practical guidance on best practices for testing the security of API endpoints, including a step-by-step technical example of how to test gRPC endpoints. It outlines the types of security testing that should be performed and the different types of security vulnerabilities that can be found in API endpoints and provides tips for remediation. By following the guidance in this article, you can build a robust security testing plan for your API endpoints.

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OWASP API Security Checklist: The Types of Tests to Perform

To ensure the security of your API endpoints, you should perform several types of testing, as recommended in the OWASP API Security Checklist. By performing these types of tests regularly, you can gain assurance that your API endpoints are secure and address any vulnerabilities that are identified to protect your APIs and your consumers.

• Penetration testing examines API endpoints for vulnerabilities that could allow unauthorized access or control. This includes testing for injection flaws, broken authentication, sensitive data exposure, XML external entities (XXE), broken access control, security misconfigurations, and insufficient logging and monitoring.
• Fuzz testing, or fuzzing, submits invalid, unexpected, or random data to API endpoints to uncover potential crashes, hangs, or other issues. This can detect memory corruption, denial-of-service, and other security risks.
• Static application security testing (SAST) analyzes API endpoint source code for vulnerabilities. This is useful for finding injection flaws, broken authentication, sensitive data exposure, XXE, and other issues early in the development lifecycle.
• Dynamic application security testing (DAST) tests API endpoints by sending HTTP requests and analyzing the responses. This can uncover issues like injection, broken authentication, access control problems, and security misconfigurations.
• Abuse case testing considers how API endpoints could potentially be misused and abused. The goal is to identify ways that the API could be used for malicious purposes so that appropriate controls and protections can be put in place.

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Common API Vulnerabilities and How to Test for Them

To ensure the security of your API endpoints, you must test for common vulnerabilities. Some of the major issues to check for include:

• SQL injection: This occurs when malicious SQL statements are inserted into API calls. Test for this by entering ' or 1=1;-- into API parameters to see if the database returns an error or additional data.
• Cross-site scripting (XSS): This allows attackers to execute malicious JavaScript in a victim's browser. Try entering into API parameters to check for reflected XSS.
• Broken authentication: This allows unauthorized access to API data and functionality. Test by attempting to access API endpoints with invalid or missing authentication credentials to verify that users are properly authenticated.
• Sensitive data exposure: This occurs when API responses contain personally identifiable information (PII) or other sensitive data. Review API responses to ensure no sensitive data is returned.
• Broken access control: This allows unauthorized access to API resources. Test by attempting to access API endpoints with different user roles or permissions to verify proper access control is in place.

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Testing gRPC Endpoints: A Technical Example

Integration Testing gRPC Endpoints in Python 

To ensure your gRPC API endpoints are secure, you should perform integration testing. This involves sending requests to your API and analyzing the responses to identify any vulnerabilities.

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Step 1 

First, use a tool like Postman, Insomnia, or BloomRPC to send requests to your gRPC server. Test all endpoints and methods in your API.

• Set up a gRPC channel and stub to connect to the server.
• Call the appropriate gRPC methods on the stub to send requests and receive responses.

#import the relevant modules 

import grpc

import your_service_pb2 as your_service

import your_service_pb2_grpc as your_service_grpc

def test_integration():

    # Test all endpoints and methods in your API.

    channel = grpc.insecure_channel('your_grpc_endpoint_address:port')

    stub = your_service_grpc.YourServiceStub(channel)

    test_endpoint_1(stub)

    test_endpoint_2(stub)

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Step 2 

Next, analyze the responses for information disclosure. Make sure that no sensitive data is returned in error messages or stack traces.

• In the test_endpoint_1 function, send a request to Endpoint 1.
• Handle any exceptions that occur during the request and analyze the error message or status code for potential information disclosure.

def test_endpoint_1(stub):

  

    try:

        request = your_service.Endpoint1Request(param1='value1', param2='value2')

        response = stub.Endpoint1Method(request)

        print("Endpoint 1 response:", response)

    except grpc.RpcError as e:

        print("Error occurred in Endpoint 1:", e.details())

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Step 3

Then, test for broken authentication by sending requests without authentication credentials. The API should return a “401 Unauthorized” status code.

• In the test_endpoint_2 function, send a request to Endpoint 2 without providing authentication credentials.

Catch any grpc.RpcError exceptions that occur and check the error code to ensure that it is “401 Unauthorized.”

def test_endpoint_2(stub):

    ```

Test for broken authentication.

    Send requests without authentication credentials.

    The API should return a 401 Unauthorized status code.

```

    try:

        request = your_service.Endpoint2Request(param1='value1', param2='value2')

        response = stub.Endpoint2Method(request)

        print("Endpoint 2 response:", response)

    except grpc.RpcError as e:

        print("Error occurred in Endpoint 2:", e.code())

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Step 4

Finally, execute the tests. Call the test methods you have defined in your script to execute the integration tests:

if __name__ == '__main__': 

test_integration()

It is important to note that gRPC API endpoint testing has many variations depending on the programming language and technologies you are using. For the example given above, there are many extension possibilities. 

For instance, you can further expand the code and add more test methods for other steps such as testing access control, handling malformed requests, checking TLS encryption, and reviewing API documentation for any discrepancies with the actual implementation.

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Ongoing API Endpoint Security Testing Best Practices

To ensure that API endpoints remain secure over time, ongoing security testing is essential. Schedule regular vulnerability scans and penetration tests to identify any weaknesses that could be exploited.

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Conduct Regular Vulnerability Scans

Run automated vulnerability scans on API endpoints at least monthly. Scan for issues like:

• SQL injection
• Cross-site scripting
• Broken authentication
• Sensitive data exposure

Remediate any critical or high-severity findings immediately. Develop a plan to address medium- and low-severity issues within 30-90 days.

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Perform Penetration Tests

Have an independent third party conduct penetration tests on API endpoints every 6-12 months. Penetration tests go deeper than vulnerability scans to simulate real-world attacks. Testers will attempt to access sensitive data or take control of the API. Address any issues found to strengthen endpoint security.

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Monitor for Anomalous Behavior

Continuously monitor API endpoints for abnormal behavior that could indicate compromise or abuse. Look for things like:

• Sudden spikes in traffic
• Requests from unknown or suspicious IP addresses
• Invalid requests or requests attempting to access unauthorized resources

Investigate anything unusual immediately to determine if remediation is needed. Monitoring is key to quickly detecting and responding to security events.

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Review Access Controls

Review API endpoint access controls regularly to ensure that only authorized users and applications can access data and resources. Remove any unused, outdated, or unnecessary permissions to limit exposure. Access controls are a critical line of defense, so keeping them up-to-date is important for security.

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Conclusion

In conclusion, testing the security of API endpoints should be an ongoing process to protect systems and data. By following best practices for identifying vulnerabilities through various types of security testing, you can remediate issues and strengthen endpoint security over time. 

While the examples above focused on gRPC endpoints, the overall guidelines apply to any API. Regularly testing API endpoints is key to avoiding breaches and ensuring the integrity of your infrastructure. Make security testing a priority and keep your endpoints protected.