What is Checkly?

Checkly is a synthetic monitoring platform built around a single conviction: monitoring configuration should live in your Git repository, not in a SaaS dashboard. Founded in 2018 and backed by Accel, CRV, and Balderton Capital — which led a $20M Series B in 2024 — Checkly pioneered the "Monitoring as Code" category with a TypeScript-native CLI that lets teams write, test, and deploy checks through standard CI/CD pipelines. The platform runs Playwright browser scripts and HTTP API checks on a schedule, executing 32.5 million checks daily for over 1,000 customers including Vercel, 1Password, and Autodesk. In early 2026, Checkly added Rocky, an AI agent that automatically triages failures, analyzes packet captures and traceroutes, and surfaces root causes without manual investigation.

Key Takeaways

• Monitoring configurations live in Git and deploy through CI/CD — the same workflow as application code.
• Native Playwright support lets teams reuse existing test scripts as production monitors, eliminating duplicate codebases.
• Free Hobby tier includes 10,000 API check runs and 1,500 browser check runs per month.
• The 30-second request timeout is a hard ceiling — teams with 60-second load balancer timeouts will see false positives.
• Checkly is hired as part of broader DevOps/SRE stacks, not as a standalone skill.

What Makes Checkly Different

Checkly's defining insight is that testing and monitoring are the same thing run at different times. Most teams maintain two separate codebases: Playwright tests that run in CI before deployment, and click-configured checks in some monitoring dashboard after deployment. These drift apart. Checkly collapses both into one: the Checkly CLI lets you define checks in TypeScript files that sit next to your application code, run against staging in your PR pipeline, and then deploy as scheduled production monitors on merge. Playwright Check Suites extend this further — your full Playwright test suite becomes a production monitor. The practical result is that monitoring stays in sync with the application because it's developed and reviewed alongside it.

Key Features

Playwright Browser Checks run full user journey scripts against production on a schedule — Checkly is one of the few platforms with native, first-class Playwright support rather than a proprietary scripting language. API Monitoring validates HTTP endpoints with chainable requests, variable passing between steps, and assertions on status, headers, body, and latency. Private Locations let you deploy the Checkly agent inside your own network to monitor internal services, staging environments, or geo-restricted endpoints that aren't publicly accessible. Multi-region execution runs each check from multiple global locations simultaneously, surfacing latency differences and region-specific failures. Rocky AI Agent (2026) performs automatic failure triage including traceroute and packet capture analysis, error classification, and user impact assessment.

Checkly vs Datadog Synthetic Monitoring

The core tradeoff is focus versus breadth. Datadog bundles synthetics into a full observability platform covering APM, logs, metrics, and infrastructure — if you already run Datadog, adding synthetic checks is one dashboard. But Datadog doesn't support native Playwright scripts, check configurations live in its UI rather than your repo, and modular pricing means synthetic check costs add to an already substantial bill. Checkly does one thing: run scripted checks from code. It's significantly cheaper as a standalone synthetics solution, supports Playwright natively, and integrates with whatever observability backend you prefer via OpenTelemetry. The recommended pattern for cost-conscious teams is Checkly for synthetics paired with Grafana Cloud or Sentry for metrics and error tracking — rather than paying Datadog for every layer.

Pricing and Plans

Checkly's free Hobby plan covers 10,000 API check runs and 1,500 browser check runs monthly — enough for personal projects and small applications. Paid usage-based pricing starts at roughly $0.80 per 10,000 API check runs; browser checks cost more due to the compute overhead of running full Chromium instances. Team and Enterprise tiers add SSO, extended data retention, private location support, and dedicated SLAs. Enterprise pricing is negotiated. The cost model can surprise teams who run high-frequency Playwright suites across multiple regions — a check running every five minutes from five locations generates 2,160 browser check runs per day. Auditing check frequency and consolidating low-priority checks to less frequent intervals is standard practice before budget reviews.

Production Gotchas

Three issues surface repeatedly in production use. First: the 30-second request timeout is absolute. Teams with 60-second load balancer or upstream service timeouts will see Checkly report failures that aren't application failures — and there's no configuration option to extend it. Second: retry logic always runs on a different region than the original check attempt. For applications that render different content by geography, a geo-fenced check that fails in us-east-1 may pass when Checkly retries from eu-west-1, masking the real regional failure. Third: alert fan-out without aggregation — when a shared upstream dependency fails, every check that depends on it fires its own alert independently. Teams hitting this problem typically build a Checkly alert group but still see on-call noise until alert routing is tuned. The 2026 Rocky AI agent helps classify cascading failures, but doesn't suppress duplicate alerts at the routing layer.

Checkly in the Fractional Talent Context

Checkly expertise shows up in fractional SRE and DevOps engineering roles rather than dedicated monitoring specialist positions. Companies typically hire for it as part of a broader "reliability engineering foundation" engagement: setting up Monitoring as Code alongside GitHub Actions CI/CD, Terraform infrastructure definitions, and an observability stack. The pattern at growth-stage SaaS companies is to bring in a fractional DevOps engineer for a 3-6 month engagement to build out the monitoring foundation, then hand it to internal engineers who can maintain it using the existing Git workflow. Checkly's alignment with developer tooling (TypeScript, Git, CLI) means a senior full-stack engineer can own it — you don't need a dedicated ops hire. We see increasing demand for Checkly alongside Playwright in fractional engineering briefs as shift-left monitoring moves from DevOps blogs to standard practice.

The Bottom Line

Checkly occupies a specific, defensible position: the monitoring tool that developers actually want to maintain. By treating monitoring configuration as code rather than dashboard state, it eliminates the drift that makes most monitoring setups stale within months of being configured. With $32.25M in total funding, 1,000+ enterprise customers, and an AI triage layer added in early 2026, the platform is maturing from niche DevOps tool to standard component of modern release pipelines. For companies hiring through Pangea, Checkly experience signals a DevOps or SRE engineer who thinks in terms of reliability systems — not just alert dashboards.