Testing
Locust is a Python-based load testing tool that lets you define user behavior as plain Python code. If your team writes Python, Locust is the most natural load testing choice — no XML, no proprietary scripting language, just standard Python classes. What Is Locust? Locust is an open-source load testing framework
Testing
Both k6 and Locust are excellent modern load testing tools that replaced JMeter for many teams. The choice between them often comes down to one question: does your team write JavaScript or Python? But there are real differences beyond scripting language. Side-by-Side Comparison Feature k6 Locust Language JavaScript (ES6+) Python
Testing
Hypothesis is Python's most powerful property-based testing library. It generates test inputs automatically, shrinks failures to minimal examples, and remembers past failures across test runs. If you write Python and care about test quality, Hypothesis is worth learning. Installation pip install hypothesis Copy Hypothesis integrates with pytest, unittest,
Testing
JMeter has been the go-to load testing tool for over two decades. k6 emerged as a modern alternative that trades JMeter's GUI and feature breadth for developer-friendliness and simplicity. Which one should you use? This comparison cuts through the noise. Quick Comparison Feature k6 JMeter Scripting JavaScript (ES6+
Testing
Load testing tells you how your application behaves under pressure — before real users find out the hard way. k6 is a modern, developer-friendly load testing tool that has quickly become one of the most popular choices for performance testing. This guide walks you through everything you need to get started.
Testing
fast-check is the leading property-based testing library for JavaScript and TypeScript. It generates test inputs automatically, shrinks failures, and integrates with Jest, Vitest, and Mocha with zero configuration changes. If you write JavaScript and want to find bugs that hand-written tests miss, fast-check is the tool. Installation npm install --save-dev
Testing
k6's scenarios system gives you fine-grained control over how load is applied to your system. Instead of a single thread count and duration, you can model realistic traffic patterns — gradual ramp-ups, sudden spikes, sustained soak tests — with different executors for each shape. What Are k6 Scenarios? Scenarios define
Testing
Integration tests fail for predictable reasons: shared mutable state, timing assumptions, over-mocking, wrong scope, and ordering dependencies. Most integration test suites that "work most of the time" are failing for these reasons. This guide identifies the most common anti-patterns and shows how to fix them. Key Takeaways Shared
Testing
Service meshes (Istio, Linkerd) add traffic management, observability, and security at the infrastructure layer. Testing mesh behavior requires testing at a different level than application code — you're testing retry policies, circuit breakers, mTLS, and traffic routing rules, not business logic. This guide covers the test patterns specific to
Testing
TestContainers runs real Docker containers (PostgreSQL, Redis, Kafka, Elasticsearch, etc.) inside your integration tests. Each test gets a clean, isolated instance with no shared state. This eliminates the "works on my machine but fails in CI" problem that plagues integration tests using shared test databases or in-memory substitutes.
Testing
WireMock is an HTTP mock server that lets you stub external API responses and verify that your code makes the expected calls. It's the right tool when your integration tests need a real HTTP server to call (not a mock object) without depending on an actual external service.
Testing
Testing Kafka producers and consumers requires handling asynchrony — you publish a message and the consumer processes it on its own schedule. Embedded Kafka (for unit-like tests) and TestContainers Kafka (for integration tests) solve the "real Kafka without real infrastructure" problem. Consumer group offset management, idempotency, and retry logic