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By Stefan Judis
A Playwright Check fails at 2 am. The login flow is broken. Until today, that alert triggered a human to get up, open the Checkly dashboard, copy Rocky AI root cause analysis (RCA), and then tell an agent to get to work. There were two AI agents, one incident, and no way for them to talk to each other. The extended checkly checks and new checkly rca CLI commands close that gap. Your coding agent can now pull Rocky AI's analysis into its ongoing work, read the diagnosis, and go fix the code.
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By Vince Graics
This is a guest post by Vince Graics, Staff QA Engineer at World of Books. If you're running a Shopify storefront and want reliable synthetic monitoring, you'll hit a wall. Shopify's bot detection doesn't care that your headless browser is friendly; it sees datacenter IPs and acts accordingly. Cart API calls get hit with 429 rate limits, Cloudflare challenge pages pop up mid-check, and you're left wondering whether the bug is in your code or in the platform fighting you.
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By Pırıl Kavlak
The Checkly Playwright Reporter is an npm package that sends the results of npx playwright test to Checkly as a cloud test session, including traces, screenshots, videos, and full debugging context. Run your Playwright suite in CI or locally, and every result gets a persistent, shareable home in Checkly with AI-powered analysis, richer trace-derived views, and a direct path to production monitoring. It does not replace Playwright. It makes the output of Playwright much easier to work with.
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By Hannes Lenke
November 24th, the Opus 4.5 release turned around the entire tech industry. This was the moment when agents became capable. Capable enough to write solid staff-level code. Capable enough to reason about alerts, investigate root causes much faster than most engineers, and set up the reliability layer faster. For me, this feels like an iPhone moment on steroids; the adoption of AI is accelerating much faster than any adoption curve I’ve seen over the past few decades.
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By Stefan Judis
Half of the Checkly CLI users are already coding agents. This is not a prediction — it's what the data shows today. Since February, more and more agents have been using the CLI to manage and configure their Checkly monitoring setups. Right now, we're at 50% human and 50% agentic CLI users. And we predict that by the end of 2026, it won't be humans using the CLI; the agents will have taken over. The terminal became the primary interface for AI agents doing real work in the Checkly ecosystem.
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By Susa Tünker
When we started building Checkly's uptime monitoring suite, the goal was to give engineering teams complete visibility across every layer of their stack, from application down to network, in one place. URL, TCP, DNS, and Heartbeat monitors covered a lot of that ground. But one fundamental piece was missing: the ability to simply ping a host and know if it's reachable.
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By Dan Giordano
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.
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By Tim Nolet
Rocky AI — Checkly’s AI agent — is now Generally Available. We developed Rocky AI over the last ~6 to 8 months. This is an aeon in AI-years. During this period, we learned a ton. About AI, but mostly about how to fit them into an existing SaaS product, not just another chat widget. This is my ramble…
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By Stefan Judis
The web was built for humans, but now the agents are taking over. Humans look at a web page and see content rendered by their browser. AI agents see 180,000 tokens of nav bars, footers, and div soup — burning through their context window on junk that makes them slower and stupider. The web needs to evolve, and we as developers are driving the shift. AI agents like Claude Code, Cursor, Codex, and Gemini are how we interact with documentation, CLIs, and products today.
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By Stefan Judis
AI coding agents are excellent at writing code. Ask Claude Code, Codex, or Cursor to add a feature, and it just works. At Checkly, we were ready for the new agentic world from the start! Monitoring as Code means your entire monitoring setup lives in your repository. API Checks, Browser Checks, alert channels, status pages; everything is defined in code, managed with the Checkly CLI, and version-controlled like any other part of your stack.
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By Checkly
Rocky, Checkly's AI agent, monitors production sites and provides an analysis for every failing check. Previously, a coding agent couldn't access this analysis, leaving incidents and agents disconnected. Now, you can access all the analyses via the Checkly CLI (or API) and tell your coding agent, "Hey, I got a Checkly alert. Please investigate!" With Rocky's structured analysis delivered inline, the coding agent can start with a strong hypothesis, fix issues, and propose a PR in one session.
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By Checkly
Learn how the Checkly CLI uses a single function (`detectOperator()`) to detect whether the caller is a human, CI, or a coding agent by checking agent-set environment variables. This detection then changes how commands behave to provide the best agent experience.
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By Checkly
Building Agent-Friendly CLIs: Why Your AI Agent Already Loves the Checkly CLI Stefan explains why products, docs, and CLIs must be AI-ready as coding agents rapidly become primary users of the Checkly CLI. He outlines key CLI features for agent workflows: Stefan demos how an agent initializes project-tailored Checkly setup from scratch without any human intervention and also shows how agents can entirely automate the incident life cylce from resolution to status page communication.
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By Checkly
Most agent skills are static — frozen documentation snapshots that go stale the moment APIs change or flags get deprecated. Checkly does it differently. Our SKILL.md is just 100 lines of CLI pointers. No baked-in docs. Your coding agent learns what it needs, when it needs it, straight from the Checkly CLI.
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By Checkly
Playwright is too hard, too slow, and too flaky — right? In this webinar, Stefan busts six common end-to-end testing myths and shows how to reuse your Playwright tests as production monitors with Checkly. He covers codegen, trace viewer, UI mode, flakiness root causes (and fixes), and a quick look at Playwright MCP for AI-assisted test generation.
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By Checkly
50% of Checkly's CLI users are already coding agents. We predict that agents will become dominant by the end of 2026. This video demonstrates an agentic workflow where an alert reports a broken Shopify store login flow, and Claude Code, using the installed Checkly Skill and the Checkly CLI, pulls monitoring results, identifies a Playwright test failure, investigates the codebase, finds and fixes a bug, and then updates a Checkly status page by creating an incident.
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By Checkly
Tangling DNS, TCP handshake failures, packet loss: your network has blind spots that application-level dashboards miss. In this session, Daniel Paulus (VP Engineering, Checkly) sets up DNS, TCP, and ICMP monitors from scratch and deploys them as code using the Checkly CLI. You'll see how to import checks from the UI to a code project, use coding agents to build monitors, and debug network failures with Rocky AI, trace routes, and packet captures.
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By Checkly
Checkly introduces ICMP monitoring to complement its existing uptime and synthetic monitoring (URL/HTTP, TCP, DNS, and heartbeat checks) for systems without HTTP endpoints, such as database hosts, VPN gateways, and load balancers.
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By Checkly
How does one of the world's leading AI companies keep its infrastructure reliable while shipping new models constantly? In this webinar, Devon Mizelle, Senior SRE at Mistral AI, shares the real story. Devon walks through how Mistral built an automated system that generates synthetic checks for every model the moment it goes live—no manual configuration, no forgotten monitors, no inconsistent alerting. Using monitoring as code, his team eliminated the toil of maintaining hundreds of checks across a rapidly evolving model ecosystem.
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By Checkly
We've been running Playwright in production for years. Today, we, at Checkly, are going all in with Playwright Check Suites. Playwright Check Suites is our latest step towards uniting testing and monitoring into a single workflow. It's our biggest advancement yet! Here's why this matters: We're not adapting Playwright anymore. We're running it natively in production with full `playwright.config` support, complete custom dependency control, and support for every tag, spec, or configuration.
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Downtime caused by API performance has serious business impact. Use Checkly's deep but easy to use API monitoring solution to check your mobile, webapp or IoT API for performance, uptime and correctness.
Checkly is the easiest way to monitor your API's and Browser click flows from a single dashboard. Use a powerful assertions engine to check all your (mobile) API's for timeliness and correctness. Use javascript to check your most crucial browser transactions. Built specifically for developers and ops teams.
We run your checks from multiple global data centers and alert you when things go south with SMS, Pagerduty etc. Add team mates, call checks from your CI/CD pipeline and publish a status page under a custom domain. We also do SSL expiry checks!
Features at a glance:
- No more broken APIs: Make sure your API is always responds quickly and with the correct payload. Get started quickly with our Swagger or cURL importer and super easy API monitor creator.
- No more broken shopping carts: Monitor and validate your most crucial site transactions like logins, shopping carts and onboarding flows. Take screenshots to get instant insights into what's working and what's not.
- Alerting without limits: Keep your team up to date with a generous helping of SMS messages and unlimited email, Pagerduty, Slack and web hook notifications. Control exactly how, when and how often you get alerted. Of course, "double-checking" is enabled by default to never get false positives.
- Insights without limits: Doing a root cause without complete and accurate data is insane. But too much detail can also be distracting. That's why next to calculating aggregates to keep an overview, Checkly stores each and every raw result for you and your team to dive into.
A better way to monitor your APIs and site click flows.