Send Playwright test runs to Checkly with traces, videos, screenshots, flaky test visibility, and session history, then take key tests into monitoring.

50% of Checkly CLI users are already coding agents. Learn how built-in skills, structured output, and agent guardrails make one CLI work for humans and agents alike.

CLIs are the new agent interface. Discover how Checkly turned its CLI into an agentic layer with built-in skills, structured output, and confirmation protocols for safe autonomous monitoring.

In 2025, Checkly received 12,479 applications, of which we hired 24 people. Here's an honest look at our hiring funnel, speed, and data.

Checkly's ICMP monitors ping any host or IP to measure reachability, latency, and packet loss, available on all plans and fully integrated with Monitoring as Code.

Checkly's AI agent Rocky AI is now GA. Here are five lessons from building an AI root cause analysis agent into a SaaS product: data wrangling is still the hard part, model upgrades are nearly free, multi-model is as painful as multi-cloud, codifying human expertise into prompts works, and chat isn't always the right UI for AI.

After months of being available in Beta for our app users, Rocky AI is now generally available to all users and plans. Rocky AI is Checkly’s AI agent that works around the clock, 24/7, to make sure your application’s reliability is optimal. In this first release, Rocky AI ships with the ability to run continual Analysis on test and check failures, giving your teams AI-powered root cause analysis, impact analysis, and more. Since day 1 of the AI craze, Checkly has made it easy to work with your favorite LLMs and coding agents like Claude Code, Cursor, and OpenAI, allowing you to craft and manage your monitoring right from your IDE. Now, we’re bringing that power right into the Checkly workflow with Rocky AI. Root Cause Analysis When a test or monitor fails, Rocky AI analyzes multiple vectors across your application, including logs, traces, and more to understand what exactly caused the failure; and how to best fix it. For large teams with hundreds of monitors across their apps and servi

Only 3 of 7 major AI agents request markdown via the Accept header. Learn which agents support content negotiation, why it cuts tokens by 99%, and how to make your site agent-friendly.

Introducing Checkly Agent Skills: a new “monitoring” agent skill that lets AI coding agents set up, review, and ship production-ready monitoring as code. Learn what agent skills are, what’s inside the Checkly skill (API checks, Playwright browser checks, alerts, status pages, and more), and how its token-efficient design helps agents load best practices on demand.

Learn how to write a cover letter that actually helps you get the job. Practical, concise tips from Checkly’s Director of People, Kaylie Boogaerts, on what hiring teams really want.

There are only a few companies that successfully invest in actively monitoring real user flows in production. I’ve been puzzled by the state of the art for many years, because I’m an anxious developer that always needs to know that production is “all right”. How can it be okay for all of us to wait for error logs, thrown exceptions or customer complains to learn about production issues? Shouldn’t knowing that all the systems are operational at all time be the ultimate monitoring goal? And why’s no one actively testing and monitoring core application flows in production to ensure that all customers are having a good time? The short answer: developers, QA engineers and SREs think that synthetic monitoring or “testing in production” is too hard. But is it really? We at Checkly have some news, so buckle up! Playwright has Taken over the End-to-end Testing Market The teams at Microsoft started working on the Playwright end-to-end testing framework in February 2020. If you fast forward to to

We've been running Playwright in production since the beginning. Today, we're going all in. When we first launched Browser Checks with Playwright support, we proved something critical: the most popular test automation framework since Selenium isn't just for testing—it's the foundation of modern production monitoring. But that was just the beginning. Today, we're announcing Playwright Check Suites—our bet on the future of monitoring and the most significant evolution in Checkly's history. From Browser Checks to Check Suites: Our Evolution Our Browser Checks introduced Playwright to production monitoring, but they came with constraints. We provided curated runtime dependencies, a single test spec per check, and a managed environment that worked well for many use cases. Playwright Check Suites removes every limitation. You're no longer adapting Playwright to fit our platform. You're running it exactly as you do locally—with full control over: Your entire playwright.config.ts — Every setti

Here are 10 standout examples of public status pages, with a quick breakdown of what they do well—and where there’s room for improvement.

Checkly is now available in the AWS Marketplace. See what this means if you're an AWS user.

Can AI replace Playwright CodeGen for test automation? Explore the new Playwright MCP server that lets AI control real browsers to generate end-to-end tests with proper context and code examples.