REST APIs are a staple of modern software development. Whether you're fetching data, updating resources, developing cloud-based apps, or integrating third-party services, REST APIs can make your life easier. However, working with them isn't always smooth.
Developers often encounter errors that can be tricky to diagnose and fix, especially when they originate from an external service. This guide goes over some of the most common REST API errors, what causes them, and how to troubleshoot them with confidence.
REST API troubleshooting overview
REST API troubleshooting requires taking a systematic approach to identify, diagnose, and resolve problems. There are various aspects of the API lifecycle that should be examined, including:
Request analysis: Inspecting the HTTP request method (GET, POST, PUT, DELETE), headers, query parameters, and payload to align them with the API's specifications.
Response evaluation: Analyzing the HTTP status codes, response headers, and body to identify errors or anomalies.
Network diagnostics: Checking for connectivity issues, latency, or timeouts that may affect API performance.
Packet analysis: Capturing and inspecting network traffic to detect anomalies, dropped packets, or unexpected responses.
Authentication and authorization: Verifying that API keys, tokens, or credentials are valid and correctly configured.
Server-side logs: Reviewing server logs for errors, exceptions, or performance bottlenecks.
Rate limiting and throttling: Ensuring the API is not exceeding usage limits imposed by the server.
Third-party dependencies: Investigating issues related to external services or APIs that your application relies on.
Database performance: Checking database connections, query execution times, and data integrity to check whether the API is retrieving and storing data correctly.
The importance of prompt troubleshooting
When issues occur in your REST API, fixing them quickly is very important. Troubleshooting delays can lead to cascading problems that impact user experience, business operations, and even revenue. Let’s look at some reasons why prompt troubleshooting of REST API issues is critical:
API outages or errors can bring entire systems to a halt, especially in microservices architectures where multiple services depend on each other. Quick troubleshooting minimizes disruption and prevents costly downtime.
Some API errors, especially those related to database operations, can cause incomplete transactions or data corruption. Acting fast helps prevent irreversible data integrity issues.
Modern users demand seamless digital experiences. Slow responses, failed transactions, or broken features can drive them away. Quick resolution of API issues prevents frustration and loss of confidence in your service.
API failures can expose vulnerabilities, such as unauthorized data access or unintentional information leaks. Prompt troubleshooting helps detect and fix security gaps before attackers exploit them.
Certain errors can lead to high resource consumption, such as excessive database queries or infinite loops. Quick troubleshooting helps restore normal operations before the impact spreads.
Many businesses have contractual agreements that guarantee a certain level of API uptime and performance. Prompt troubleshooting keeps you compliant and avoids penalties or damaged partnerships.
Tools for REST API troubleshooting
During a troubleshooting session, having the right tools at your disposal can make all the difference. Let’s explore some handy options:
Postman
Postman is a widely used API testing tool with a user-friendly interface that lets you send requests and analyze responses. Here’s some ways it can help in troubleshooting:
Allows users to send GET, POST, PUT, DELETE, and other API requests with customizable parameters, headers, and payloads.
Provides detailed response analysis, including status codes, headers, and body content.
Allows developers to create test suites to validate API responses over time.
Features a built-in console that logs API requests, which helps trace authentication failures, missing parameters, and response errors.
cURL
cURL is a command-line tool used to make API requests and test endpoints. It’s lightweight, fast, and ideal for quick debugging without the need for a UI. Use it to:
Verify connectivity issues by invoking API endpoints directly from the terminal.
Debug access-related issues through different authentication methods like API keys, OAuth, and basic authentication.
Test different content types (JSON, XML, form-data) to ensure proper API request handling.
Write scripts that automate repetitive API calls for performance testing.
Swagger UI
Swagger UI is an open-source tool that visualizes RESTful APIs and lets developers interact with them. Here are some of its key features:
Automatically generates interactive API documentation from OpenAPI specifications.
Allows users to send requests directly from the UI. They can modify parameters, headers, and payloads to test API behavior.
Displays API responses in a structured format, including the status codes, headers, and body content.
Supports various authentication methods like API keys, OAuth, and bearer tokens.
Fiddler
Fiddler is a powerful HTTP proxy tool that captures and analyzes API traffic. It is useful for debugging issues related to API performance, security, and response handling. Its features include:
Capturing all HTTP/HTTPS requests and responses, allowing developers to analyze request headers, payloads, and authentication tokens.
Helping to diagnose slow API responses by measuring response times and identifying delays.
Allowing developers to tweak parameters, headers, or body content to simulate different scenarios.
Supporting encryption analysis to detect SSL/TLS certificate issues that may affect API security.
Wireshark
Wireshark is a network packet analyzer that provides deep visibility into API traffic. It helps diagnose low-level network issues that affect API performance. Engineers use it to:
Capture and inspect network packets to detect anomalies such as packet loss, high latency, or unexpected timeouts.
Analyze API communication at the transport layer (TCP/UDP).
Filter traffic by API endpoints, IP addresses, or protocols to isolate problem areas.
Detect security vulnerabilities, such as API calls made over unencrypted channels.
JSONLint
JSONLint is a simple yet effective tool for validating and formatting JSON responses. Since REST APIs often return data in JSON format, it’s important to ensure proper JSON structure. Here’s how JSONLint can help:
Checks for syntax errors in JSON responses to prevent issues caused by malformed data.
Formats unstructured JSON responses into a readable format.
Highlights missing brackets, commas, or incorrect nesting in JSON objects and arrays.
Helps validate API responses before they are sent to clients.
Site24x7
Site24x7 offers a comprehensive REST API monitoring solution that can be used to track API health, uptime, and performance in real time. With its features, you can:
Keep an eye on all the critical REST API metrics.
Receive real-time alerts via email, SMS, or integrations like Slack, Microsoft Teams, and PagerDuty when API failures occur.
Track protected API endpoints with supported authentication methods like Basic/NTLM, OAuth 2.0, and Client Certificates.
Test API availability and response times from over 130 locations worldwide to detect regional issues and optimize performance.
REST API issue troubleshooting guide
Next, let’s explore the most common REST API issues and troubleshooting steps for each.
Application errors
These errors occur due to incorrect API requests, malformed data, or backend processing failures.
400 bad request errors
A 400 Bad Request happens when the API rejects a request due to incorrect formatting or missing parameters.
Symptoms:
API returns a 400 status code.
Response body includes messages like "Invalid request format" or "Missing required fields".
Troubleshooting:
API endpoints, headers, and parameter names are often case-sensitive. Double-check that you are using the exact casing as specified in the API documentation.
Use tools like JSONLint to catch any formatting errors.
Verify that all mandatory parameters are in the request.
Look for detailed error messages in the API logs.
If you are sending a complex request payload, try simplifying it by sending only the essential parameters to see if the error persists.
500 internal server error
A 500 error indicates something went wrong on the server side.
Symptoms:
API responds with a 500 status code.
Server logs show unhandled exceptions.
Troubleshooting:
Check the API logs and then the application code to identify the specific errors causing failures.
500 errors are frequently caused by issues with the underlying database. Verify that your API can successfully connect to the database server.
If your API relies on other external APIs or services, a failure in one of these dependencies could lead to a 500 error in your API. Check the status and health of these external services.
Ensure that your API is running in the correct environment with the expected configuration settings. Incorrect environment variables, missing configuration files, or misconfigured settings can lead to runtime errors.
Platform issues
These issues arise due to deployment problems, incorrect configurations, or version mismatches.
API version mismatch
Clients using outdated API versions may get errors or unexpected behavior.
Symptoms:
Requests fail with 404 or 500 errors.
API documentation doesn’t match observed responses.
Troubleshooting:
Ensure that the client application is explicitly requesting the intended API version in the request URL (e.g., /api/v2/resources) or through a custom header (e.g., X-API-Version: 2).
Compare the API version being used by the client with the version documented as the latest.
If you have access to the server-side logs, look for information about the API version being accessed for each request.
If the client application uses an API library or SDK, verify that the library is updated to the desired API version.
Incorrect API deployment
A faulty deployment may lead to configuration mismatches or broken endpoints.
Symptoms:
Endpoints return unexpected responses.
API works in staging but fails in production.
Troubleshooting:
Ensure that the exact intended version of your API code was deployed to the target environment (e.g., production). Check commit hashes, build numbers, or deployment logs to confirm.
Carefully review all configuration files in the deployed environment. Look for discrepancies in database connection strings, API keys for external services, and environment-specific variables.
Verify that all necessary dependencies and libraries are correctly installed and at the expected versions in the deployed environment.
Examine the deployment process logs for any errors, warnings, or unusual activity that may indicate a problem during the deployment itself.
Networking problems
Connectivity problems can make APIs unavailable or slow.
API timeouts
API requests are timing out.
Symptoms:
Client receives a 408 Request Timeout.
Requests fail intermittently.
Troubleshooting:
Increase the timeout duration on both the client and server sides.
Long processing times on the server are a primary cause of timeouts. Analyze your API's backend logic and identify any slow-performing operations.
Investigate potential network issues between the client and the server. High latency, packet loss, or network congestion can cause delays that lead to timeouts.
If your API relies on calls to other external services, ensure that there’s no communication breakage with these services.
DNS resolution failure
Clients may be unable to reach the API due to DNS problems.
Symptoms:
Requests return a "DNS resolution failed" error.
Users in certain locations cannot access the API.
Troubleshooting:
Ensure that domain records are correctly configured.
Use online DNS lookup tools to check the DNS records (A, CNAME, etc.) for your API's domain name from various locations around the world.
If you have recently made any changes, wait for the DNS propagation to complete.
Flush the local DNS cache. Sometimes, a simple cache reset fixes issues.
Security problems
Authentication and authorization failures can expose vulnerabilities or block users from accessing the API.
Authentication failures
Users may be unable to log in or get unauthorized errors.
Symptoms:
API returns 401 Unauthorized or 403 Forbidden.
Tokens expire too quickly.
Troubleshooting:
Ensure that the user is providing the correct username, password, API key, or authentication token. Double-check for typos, case sensitivity, and any leading or trailing spaces in the credentials.
If using token-based authentication (like JWT or OAuth 2.0), ensure that the token being used is valid and has not expired.
If tokens expire too quickly, review the token's expiration settings on the server-side.
Check the authentication server logs for any errors or failures related to the user's login attempt or token validation.
API key misuse
Attackers may exploit leaked or stolen API keys.
Symptoms:
Unexpected traffic spikes from unknown sources.
Unauthorized transactions or data access.
Troubleshooting:
If you suspect an API key has been compromised, the first and most critical step is to immediately revoke that key. This will prevent further unauthorized access.
Review your API access logs to identify the source of the unexpected traffic or unauthorized activity.
If feasible, restrict the usage of your API keys to specific IP addresses or ranges that are known and trusted.
Implement a policy of regularly rotating your API keys. This limits the window of opportunity for misuse if a key is ever compromised.
Dependency failures
APIs that rely on external services may fail if those services go down.
Third-party API downtime
External services may experience outages, which affect API functionality.
Symptoms:
Requests fail intermittently.
Logs show third-party API errors.
Troubleshooting:
Check the external service’s status page to confirm if the issue lies with them.
Check the third-party API provider's social media channels (like Twitter) and developer forums for any announcements or discussions about potential outages.
Within your API, implement health checks that periodically try to connect to or access the third-party API. This allows you to automatically detect when the dependency is down and trigger alerts.
Scalability challenges
APIs may struggle under heavy traffic or inefficient code.
API fails under high traffic
An API may stop responding when too many users access it simultaneously.
Symptoms:
Increased error rates during peak usage.
Server resource consumption spikes.
Troubleshooting:
Implement rate limiting to prevent excessive requests from overloading the system.
Implement load balancing to distribute incoming requests evenly across multiple server instances.
Use message queues (like RabbitMQ or Kafka) to handle write operations or long-running tasks asynchronously.
Ensure that your database is optimized for high concurrency using techniques like connection pooling, read replicas for offloading read traffic, and database-level caching.
If nothing else works, add more servers or use cloud auto-scaling.
How to prevent REST API issues (best practices)
To avoid several of the aforementioned issues, here are some best practices to follow:
Design your API to return meaningful error messages and appropriate HTTP status codes (e.g., 400 for client errors, 500 for server errors). This helps developers quickly identify and resolve issues.
Always version your APIs (e.g., /v1/resource) to avoid breaking changes for existing clients when updating or modifying endpoints.
Enforce strict validation on request payloads, query parameters, and headers to prevent malformed or malicious data from causing errors.
Continuously monitor API performance and log all requests and responses. Use tools like Site24x7 to track metrics such as response times, error rates, and throughput.
Use HTTPS to encrypt data in transit, implement authentication (e.g., OAuth 2.0, API keys), and enforce authorization checks to protect sensitive resources.
Use caching (e.g., HTTP caching headers or a CDN) to reduce server load and improve response times for frequently requested data.
Provide clear, up-to-date documentation that includes endpoint details, request/response examples, and error codes. Tools like Swagger can help automate this process.
Set reasonable timeout limits for API requests and implement retry mechanisms with exponential backoff to handle transient failures.
Design your API to support idempotent operations (e.g., PUT, DELETE) to ensure that repeated requests have the same effect as a single request.
Conclusion
REST APIs are a great way to build feature-rich applications, fast. However, when issues arise, they can lead to downtime, performance bottlenecks, or security risks if not handled properly. We hope that the insights shared in this guide will be helpful the next time you have to troubleshoot an API issue.