API testing guides — test REST and GraphQL APIs, write contract tests, and automate API validation.
Security Testing
Dynamic Application Security Testing (DAST) attacks your running API to find vulnerabilities that static analysis misses: authentication bypass, BOLA/IDOR (Broken Object-Level Authorization), injection through actual HTTP requests, and security misconfigurations. This guide covers OWASP ZAP API Scan and Nuclei for REST API DAST in CI/CD pipelines. Why
Testing
Most contract testing material focuses on REST APIs. But many modern systems communicate through message queues — Kafka, RabbitMQ, SNS/SQS, or custom event buses. The same integration problems that contract testing solves for HTTP — a producer changes a message schema and consumers silently break — exist in event-driven architectures, and
Testing
Integration tests are slow, brittle, and expensive to maintain. You spin up multiple services, wire them together in a test environment, and hope that everything behaves the way it did last Tuesday. When a test fails, you spend twenty minutes figuring out whether the problem is in the consumer, the
API Testing
Checkly's API checks are HTTP monitors with assertions. You send a request, define what "passing" looks like, and Checkly runs that check from global locations on a schedule. When an assertion fails, you get alerted. Simple premise, a lot of depth in the details. This guide
Puppeteer
Puppeteer's network interception capabilities turn browser automation into an API testing tool. You can intercept requests, inspect payloads, mock responses, and validate that your frontend sends the right data to your backend — all within end-to-end test scenarios where the browser and API are exercised together. Network
Testing
Writing consumer Pact tests is the easy part. Provider verification is where teams run into real friction — database state, authentication middleware, third-party dependencies, and slow test setup all become problems at once. This post covers practical strategies for handling each of these. The Core Challenge: Provider State Every Pact
API Testing
Frontend team waiting on backend APIs to be built. Backend team waiting on the frontend to tell them if the API shape is right. Everyone blocked on everyone else. Prism breaks this cycle. Give it an OpenAPI spec and it spins up a fully functional mock server — returns realistic example
API Testing
Postman collections are useful for manual API testing. Newman — Postman's command-line runner — makes those same collections run in CI/CD. Every push triggers the full API test suite, reports go into your build artifacts, and failures block merges. This guide covers setting up Newman in CI/CD:
Testing
* Postman Monitors run your collections on a schedule without any local infrastructure * Schedules can run as often as every 5 minutes from multiple global regions * Alerts fire via email, Slack, or PagerDuty when a run fails or degrades * The Monitors dashboard shows pass rate, response time, and full request history
API Testing
Postman mock servers create a fake API endpoint that responds to requests with predefined data. They're useful for two scenarios: building frontend code before the backend API exists, and testing how your code handles specific API responses (including edge cases and errors) without needing to orchestrate the real
Testing
* Postman Flows is a visual canvas for chaining API requests without writing collection scripts * Data passes between blocks using typed connections — no pm.collectionVariables needed * Conditional (If) blocks branch the flow based on response values * Flows are shareable and runnable inside Postman — no local runtime required * Use Flows for orchestration
Testing
* Collection Runner executes all requests in a collection sequentially with pre/post scripts * Newman is the CLI equivalent — install with npm and run anywhere * Data-driven testing uses CSV or JSON files to parameterize requests * GitHub Actions and Jenkins both support Newman out of the box * newman-reporter-htmlextra produces