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500+ REST API Interview Questions with Answers 2026
IT & Software100% OFF

500+ REST API Interview Questions with Answers 2026

Udemy Instructor
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About this course

Detailed Exam Domain CoverageThis comprehensive practice test suite is engineered to thoroughly assess and reinforce your knowledge across the core domains evaluated during technical screening rounds for engineering roles. HTTP Protocols (20%): Deconstruction of core HTTP methods (GET, POST, PUT, DELETE, PATCH), safe vs. unsafe verbs, header manipulation, and protocol specifics.

REST Architecture (18%): Core architectural constraints including statelessness, client-server separation, resource identification through structured URIs, and accurate mapping of HTTP status codes. API Design (15%): Designing predictable API endpoints, body payload formats (JSON, XML), robust error handling payload structures, versioning strategies (URI, Header, Query string), and pagination mechanics. Security and Authentication (12%): Implementation of OAuth workflows, signing and verifying JSON Web Tokens (JWT), SSL/TLS encryption mechanisms, input validation, and defensive API authentication strategies.

Advanced REST Concepts (10%): Hypermedia (HATEOAS), idempotency guarantees, rate limiting algorithms, multi-level caching strategies, and content negotiation. Comparison with Other APIs (8%): Structural architectural evaluations comparing SOAP vs REST, GraphQL vs REST, and the distinct design principles driving RESTful web services. Troubleshooting and Best Practices (7%): Practical debugging techniques, standard error handling strategies, performance optimization, structural API documentation, and testing methodologies.

Tools and Technologies (10%): Leveraging Swagger and OpenAPI specifications, working with JAX-RS ecosystems, configuring API gateways, and managing enterprise API management platforms. About the CourseNavigating modern system design and backend engineering interviews requires a deep, production-level understanding of API lifecycle operations. Landing a role as an API Developer, Full Stack Engineer, or Software Architect depends on your ability to handle real-world edge cases—like choosing between PUT and PATCH, preventing token manipulation, handling race conditions via HTTP headers, or designing optimal rate-limiting strategies.

I designed this extensive repository of 550 highly specific, original practice questions to help you master the exact scenarios technical panels evaluate. Instead of basic definitions, this test bank dives straight into architectural tradeoffs, security implications, and error states. Every question is backed by a thorough, step-by-step breakdown explaining why the correct choice stands up to architectural standards and why the alternative selections cause bugs, performance drops, or security flaws in a live environment.

Utilizing these realistic scenario-based evaluations ensures you enter your interview with the absolute confidence required to pass your technical screening rounds on your very first attempt. Sample Practice Questions PreviewReview these three production-grade sample questions to preview the depth, structure, and quality of the explanations provided throughout this entire test preparation bank. Question 1: Idempotency Realities in HTTP Method ExecutionAn engineer needs to design a set of endpoints for an e-commerce platform.

While evaluating network retry behaviors, they must guarantee that duplicate incoming client requests do not cause unexpected side effects in the system state. Which of the following accurately describes the idempotency guarantees of standard HTTP methods? A) POST and PUT are inherently idempotent, while PATCH and DELETE are strictly non-idempotent.

B) GET, PUT, and DELETE are idempotent methods, whereas POST is inherently non-idempotent. C) All standard HTTP methods are completely idempotent as long as the backend database handles transactions correctly. D) Only GET and HEAD requests are idempotent because they do not modify the server state at all.

E) PUT is completely non-idempotent because it creates a new entity representation every single time it runs. F) DELETE is non-idempotent because running it a second time against a missing resource returns a 404 instead of a 200. Correct Answer & Explanation:Correct Answer: BWhy it is correct: By HTTP specification standards, an idempotent operation can be executed multiple times without changing the final state of the server beyond the initial request.

GET is safe and idempotent as it only retrieves data. PUT replaces the target resource entirely, meaning multiple identical PUT requests result in the exact same resource state. DELETE is idempotent because once a resource is removed, subsequent delete operations leave the system in that same "removed" state, despite variations in the response code returned.

POST is explicitly non-idempotent because multiple execution instances create duplicate resources. Why alternative options are incorrect:Option A is incorrect: POST is not idempotent, and DELETE is idempotent. Option C is incorrect: The HTTP specification dictates method properties, not the database layer logic.

Option D is incorrect: GET and HEAD are safe methods, but PUT and DELETE are also strictly idempotent even though they alter state. Option E is incorrect: PUT updates or replaces the resource at a specific URI, making its final state predictable across retries. Option F is incorrect: The returned status code variation (200 OK vs 404 Not Found) does not break idempotency; what matters is that the backend server state remains identical after the first deletion.

Question 2: Designing Graceful Versioning Strategies for Enterprise ClientsA team needs to transition an active production API from version 1 to version 2 due to breaking changes in the response payload structure. The architect wants to implement a versioning approach that does not break existing client integrations, supports browser caching mechanisms out of the box, and keeps the resource URIs clean. Which strategy fits these requirements best?

A) Use URI path versioning exclusively by prefixing all endpoints with /v1/ and /v2/. B) Use custom header versioning by requiring clients to send an X-API-Version key in their requests. C) Use content negotiation via the standard Accept header to define payload schemas.

D) Duplicate the entire server infrastructure to run the new API version on a separate subdomain. E) Avoid explicit versioning by writing complex conditional statements inside a single unified endpoint controller code block. F) Implement query string versioning by appending a version parameter onto the end of every URL string.

Correct Answer & Explanation:Correct Answer: CWhy it is correct: Content negotiation versioning leverages the standard Accept header (e. g. , Accept: application/vnd.

company. v2+json). This keeps the resource URI completely clean and consistent, which aligns with true REST principles.

It also supports standard HTTP caching engines by utilizing the Vary: Accept response header to distinguish cached schemas cleanly. Why alternative options are incorrect:Option A is incorrect: URI path versioning alters the URL, meaning the exact same conceptual resource has two different identifiers, which violates REST principles and complicates long-term caching strategies. Option B is incorrect: Custom headers hide version details from the URL, but they break standard proxy caching because most downstream internet proxies do not cache separate variants based on custom headers.

Option D is incorrect: Splitting entire infrastructure environments creates massive operational overhead and does not resolve individual application-layer caching rules. Option E is incorrect: Omitting versioning rules and relying on internal conditional blocks degrades code maintainability and causes severe technical debt. Option F is incorrect: Query string versioning compromises clean URI patterns and frequently conflicts with custom query filtering or sorting arrays.

Question 3: Handling Token Validation Faults inside an API Gateway LayerAn API Gateway intercepts an incoming request containing an expired JSON Web Token (JWT) in the Authorization header. The gateway layer must halt processing immediately to prevent the request from hitting downstream microservices. According to REST architectural design principles, what is the most appropriate HTTP response payload response?

A) Return a status code of 400 Bad Request along with a plain text string describing the token expiration. B) Return a status code of 401 Unauthorized accompanied by a WWW-Authenticate challenge header detailing the error. C) Return a status code of 403 Forbidden because the user identity inside the expired token payload is recognized.

D) Return a status code of 500 Internal Server Error because validation failed inside the core gateway system logic. E) Return a status code of 404 Not Found to obscure the security architecture layout from potential malicious actors. F) Return a status code of 200 OK with a custom internal error code parameter embedded inside the JSON body.

Correct Answer & Explanation:Correct Answer: BWhy it is correct: A 401 Unauthorized response is specifically intended for scenarios where authentication is missing, invalid, or has expired. The HTTP specification also states that a 401 response should include a WWW-Authenticate header to instruct the client on how to properly authenticate or refresh their tokens. Why alternative options are incorrect:Option A is incorrect: 400 Bad Request indicates malformed request syntax, not a failure of valid credentials.

Option C is incorrect: 403 Forbidden means the server understands who the user is, but the authenticated user explicitly lacks authorization rights for that specific resource. Option D is incorrect: 500 Internal Server Error implies a server-side bug or system crash, whereas token expiration is an expected validation outcome. Option E is incorrect: Using 404 to hide endpoints complicates client debugging and degrades the predictability of the API interface.

Option F is incorrect: Returning a 200 OK for an authentication failure violates the core mapping rules of HTTP status codes and breaks client-side interceptor logic. What to ExpectWelcome to the Interview Questions Tests to help you prepare for your REST API Interview Questions Practice Test. You can retake the exams as many times as you wantThis is a huge original question bankYou get support from instructors if you have questionsEach question has a detailed explanationMobile-compatible with the Udemy appI hope that by now you're convinced!

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During processing, the bot discovers that the invoice total value is a negative number, which violates the company's internal accounting policies. How should this scenario be classified and handled within an enterprise queue framework?A) Classify it as a System Exception, terminate the entire bot execution run immediately, and restart the target server node.B) Mark the individual item as Successful but log an internal warning message to skip further processing blocks.C) Classify it as a Business Exception, mark the queue item status as a business rule failure with a descriptive reason, and smoothly pick up the next available queue item.D) Re-queue the exact item up to 3 times to see if the underlying accounting rule changes automatically on subsequent attempts.E) Throw an unhandled generic application fault to trigger an automated Orchestrator infrastructure rollback.F) Pause the queue processing thread indefinitely and send a real-time email notification loop to the database administrator.Correct Answer & Explanation:Correct Answer: CWhy it is correct: A Business Exception occurs when data violates explicit business logic rules or validation checks, despite the applications themselves functioning perfectly. 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As memory fills up, the volatile keys are aggressively cleared out to free space for the incoming non-expiring data, causing the cache hit rate for expiring items to drop significantly while the non-TTL data continues to grow.Why alternative options are incorrect:Option B is incorrect: Volatile-lru cannot touch or evict keys that lack a TTL; it does not prioritize non-volatile keys for removal.Option C is incorrect: Redis does not execute dynamic structural datatype conversions during memory mitigation cycles.Option D is incorrect: Global evaluation across all keys irrespective of expiration describes the allkeys-lru policy, not volatile-lru.Option E is incorrect: Low precision samples reduce calculation accuracy but do not fundamentally reverse the data category targeting rules of the chosen policy.Option F is incorrect: OS page swapping slows down system performance and increases latency, but it does not alter the logical execution paths of the Redis eviction subroutines.Question 2: Distributed Locking Failures with Redlock and Network PartitioningAn infrastructure engineer implements the Redlock algorithm across a distributed layout of five independent Redis nodes to manage global execution locks. During a rolling network partition, Node 1 and Node 2 are isolated from the rest of the cluster. A client successfully acquires a lock by writing to Node 3, Node 4, and Node 5. While the transaction is open, Node 3 crashes before its asynchronous AOF log updates sync to disk. Upon instant reboot, Node 3 rejoins the cluster, and a second client attempts to claim the same resource lock. What occurs within this architecture?A) The secondary client cannot claim the lock because Node 4 and Node 5 maintain the existing lock signatures across the network balance.B) Node 3 allows the secondary client to write the lock key because its pre-crash state was not physically flushed to disk, potentially creating a dual-lock race condition if the secondary client also wins Node 1 and Node 2.C) The master cluster coordinator automatically invalidates all client write tokens across every node if any single node experiences an unexpected power recycling event.D) Redlock uses internal raft-based consensus parameters that completely freeze writes across Node 4 and Node 5 during single-node reboots.E) Node 3 rejects the new client connection until its local system timestamp advances past the original global lock TTL window.F) The primary client's session instantly drops because Redis triggers a structural roll-back on all surviving target instances.Correct Answer & Explanation:Correct Answer: BWhy it is correct: Because Redis replication and standard AOF processing use asynchronous flushing patterns to maintain performance, a crash-reboot cycle can cause a node to lose its record of a recently granted lock. When Node 3 returns with an empty state, it will happily accept a lock request from Client 2. If Client 2 also secures votes from the partitioned Node 1 and Node 2, both clients will believe they possess exclusive access, breaking the core mutual exclusion promise of the distributed lock.Why alternative options are incorrect:Option A is incorrect: While Node 4 and Node 5 will reject Client 2, Client 2 only needs a majority (3 out of 5 nodes) to win the lock. If it wins Node 1, Node 2, and the wiped Node 3, the lock is granted.Option C is incorrect: Independent nodes running the Redlock model do not maintain a master cluster coordinator layer to manage cross-node atomic rollbacks.Option D is incorrect: Redlock does not employ a unified consensus state-machine engine like Raft; it relies entirely on independent single-instance operations.Option E is incorrect: Redis does not natively delay processing or inspect historical lock lifetimes upon startup unless delayed restarts are manually coded into the infrastructure layer.Option F is incorrect: Client sessions do not receive automated rollback alerts from surviving instances when a parallel target node fails.Question 3: Time Complexity and Cardinality Scaling using HyperLogLogA metrics tracking application uses Redis HyperLogLog structures to estimate unique visitor counts for high-traffic telemetry points. The system administrator runs the PFADD command to insert millions of unique values daily into a single key location. Developers raise concerns regarding performance scaling as the unique visitor volume grows from millions to billions of items. What is the execution behavior of this metric collector?A) Memory usage tracks linearly with data density, consuming significant RAM resources once unique entries surpass a set threshold.B) The time complexity of PFADD scales linearly at an order of magnitude of O(N), which can block the primary execution thread as the data pool expands.C) The operation scales with a fixed memory footprint of roughly twelve kilobytes, and each single execution maintains a predictable time complexity of O(1).D) Redis converts the underlying structure into a dense Sorted Set matrix if individual entry hashes cause internal estimation collisions.E) The precision accuracy of the cardinality count scales downward to zero percent error as total records scale into the billions.F) The PFADD operation requires an active companion background process to regularly compute bit index distribution tables.Correct Answer & Explanation:Correct Answer: CWhy it is correct: HyperLogLog is a probabilistic data structure that estimates the cardinality of unique items using a fixed maximum memory allocation of twelve kilobytes. Because it hashes incoming elements to flip specific tracking bits in an array rather than storing the actual values, the execution time remains constant at O(1) per element, making it highly scalable for massive datasets without adding resource overhead.Why alternative options are incorrect:Option A is incorrect: HyperLogLog memory usage is capped at 12KB; it does not grow linearly with data size.Option B is incorrect: The time complexity is constant at O(1); an O(N) linear time scale would stall processing and defeat the purpose of using a probabilistic layout.Option D is incorrect: HyperLogLog does not transition into a Sorted Set format; its internal memory representation stays structured as a strict register array.Option E is incorrect: The statistical standard error rate remains constant at approximately zero point eighty-one percent; it does not hit zero error.Option F is incorrect: All calculations happen instantly and inline within the single thread; no auxiliary background threads are needed to reconstruct the register maps.What to ExpectWelcome to the Interview Questions Tests to help you prepare for your Redis Interview Questions Practice Test.You can retake the exams as many times as you wantThis is a huge original question bankYou get support from instructors if you have questionsEach question has a detailed explanationMobile-compatible with the Udemy appI hope that by now you're convinced! And there are a lot more questions inside the course.

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