How we added a cache to our Prometheus requests, without significantly increasing cache usage.

I recently talked to a customer of Checkly and he shared some thoughts about Monitoring as Code. Let’s call him Karl in this article. Karl and I talked about why Monitoring as Code (MaC) is becoming essential for teams operating at scale. As the Head of Platform Engineering at a major e-commerce company processing millions of transactions daily, his experience shows how MaC solves a lot of the messy challenges that come with traditional synthetic monitoring setups. The Problem: No Ownership, No Visibility With hundreds of microservices, dozens of development teams, and critical customer journeys that need constant monitoring, Karl's observability needs are complex and demanding. Before implementing MaC, his company struggled with traditional synthetic monitoring approaches that weren't scaling with their business needs. Traditional monitoring tools often rely on shared consoles and UIs where tests are created and managed. At first, that seems fine, but it creates some big problems: Who

Around 2022 that we needed to consider another hosting solution, and decided to move from Heroku to AWS as our hosting provider. We thought it would be interesting to share some of our thoughts and learnings from this process, so we decided to write a blog post about our experiences.

Discover how LinkedIn improved infrastructure monitoring with Checkly, preventing bugs from reaching users and enhancing service reliability.

Learn how GitHub Copilot generates Playwright tests, from detailed prompts to AI-driven coding, to streamline end-to-end test automation.

Compare Prometheus Blackbox Exporter and Kuberhealthy for Kubernetes monitoring. Discover cost, scope, and performance differences to ensure uptime.

Explore ChatGPT and Playwright Codegen for generating end-to-end tests. Discover strengths, limitations, and insights into AI-powered test generation.

Learn 5 essential Playwright CLI features like "--last-failed" and "--only-changed" to rerun failed tests & optimize end-to-end testing workflows.

Learn how to parameterize Playwright projects using fixtures and page object models for cleaner, maintainable code, and enhanced test efficiency.

Learn how to attach screenshots directly to Playwright test reports, centralizing all files in one place for an integrated view of test results.

Discover how to use Playwright and Checkly to detect broken links in your web applications by evaluating URL status codes in end-to-end tests.

Learn how a TCPDump uncovered a bug in Node.js IPv6 handling, highlighting limitations and lessons from Checkly’s Coralogix integration in monitoring services.

In this post, we’ll explore how Playwright can be used to test a GraphQL API (but don’t worry if you’re using REST; Playwright can handle any HTTP-based API). Let's dive into an example using the countries.trevorblades.com GraphQL API.

Streamline Playwright tests with TypeScript decorators. Learn how to efficiently structure test steps and enhance your Playwright test reports.

Discover essential software deployment best practices tailored for modern engineering teams. Learn how to streamline your deployment processes, enhance efficiency, and ensure successful rollouts with these expert strategies.