Performance and load testing guides — measure, benchmark, and optimize your app before it hits production.
Performance Testing
Core Web Vitals are Google's user-experience metrics that directly impact search rankings. Most teams check them manually in PageSpeed Insights—once a quarter, usually after someone notices traffic dropped. That's reactive and slow. This guide shows you how to measure LCP, CLS, and INP automatically
Python
Python profiling uses cProfile for deterministic function-level profiling, py-spy for low-overhead sampling profiling in production, and line_profiler for line-by-line analysis. This guide covers running each tool, reading pstats output, generating flame graphs, and profiling Django and FastAPI applications. Python's GIL (Global Interpreter
PWA Testing
A PWA that loads slowly or scores poorly on Core Web Vitals fails to deliver on the promise of an app-like experience. Lighthouse is the standard tool for PWA auditing, but running it manually isn't enough — you need automated performance testing in CI, regression detection, and monitoring
Puppeteer
Puppeteer has built-in access to Chrome's performance APIs, the Coverage API for unused code detection, and the DevTools Protocol for deep profiling. This makes it a capable performance testing tool — one that many teams overlook in favor of manual Lighthouse runs. This guide covers automating performance measurement
Testing Strategy
Chaos engineering is no longer a Netflix-only practice. Teams of all sizes now deliberately inject failures into their systems to discover weaknesses before users do. Two tools dominate the conversation: Chaos Monkey, the open-source originator, and Gremlin, the commercial platform that productized the concept. Choosing between them depends
Testing Strategy
Chaos engineering for stateless services is relatively forgiving. Kill a pod, another one starts. The state lives elsewhere. Stateful services are different. When you chaos-test a database, a message queue, or a distributed cache, you're working with data that can be corrupted, lost, or inconsistent. The blast
Testing Strategy
The most common reason teams never start chaos engineering: they're afraid of breaking production. The second most common reason: they start chaos engineering and actually break production. Both outcomes are avoidable. Rolling out chaos engineering safely is an engineering problem, not a bravery contest. The Prerequisite Checklist Before
Testing Strategy
Single-cloud chaos engineering is hard enough. Multi-cloud and hybrid environments add layers that make failure modes more complex, blast radius harder to control, and recovery paths less obvious. The upside: multi-cloud architectures are supposed to provide resilience through redundancy. Chaos engineering tells you whether that redundancy actually
Database Testing
PostgreSQL performance problems are rarely obvious until they're in production. A query that runs fine on 10,000 rows starts doing sequential scans on 10 million. An index that covers the happy path misses the query your new feature generates. Connection pool exhaustion looks like application errors, not
Performance Testing
Lighthouse is good at measuring page load performance. It's bad at measuring everything that happens after load: navigation between pages, complex interactions, data-heavy operations, application-specific flows. For those, Playwright with Chrome DevTools Protocol (CDP) is the right tool. This guide covers using Playwright to catch performance
Performance Testing
Synthetic monitoring tells you your site is up. Real User Monitoring (RUM) tells you what experience your actual users are having. These are different questions with different answers. A site can pass every synthetic check and still be slow for users on mobile networks in Southeast Asia, or fast in
Performance Testing
A performance budget is a constraint: "this JavaScript bundle cannot exceed 300KB." The goal isn't to have a target to aim at—it's to make building things that exceed the target impossible. A budget that can be bypassed isn't a budget; it&