Checkly

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Introduction

Checkly calls itself “the active reliability layer for developers & agents”. It lets you create and manage tests, monitors, alerts and status pages in an AI-native workflow, and deploy them as code. The homepage shows a Playwright check defined in TypeScript, tested with npx checkly test and deployed with npx checkly deploy.

The core idea is monitoring as code: the same Playwright end-to-end tests your team writes for CI can run on a schedule from global locations against production, with alerts when they fail. API checks and simple uptime monitors cover lighter cases.

Checkly says it works with AI coding agents such as Claude Code, so agents can write checks and monitors, and it monitors from 20+ global locations.

In the quality loop, Checkly bridges end-to-end testing and production monitoring: run checks against preview deployments as a release gate, then keep them running against production.

Features

1. Playwright browser checks: Run real Playwright tests on a schedule.
2. API checks: Assert on HTTP responses, headers and timing.
3. Uptime monitors: Lightweight availability checks.
4. Monitoring as code: Define checks with the Checkly CLI and constructs; version them in Git.
5. Global locations: Run from many regions; private locations on higher plans.
6. Alerting: Email, Slack, webhooks, SMS and more by plan.
7. Status pages: Communicate incidents to users.
8. CI integration: Test checks against preview environments before deploying them.

Pros

1. Reuses Playwright: One skill set for tests and monitors.
2. Code-first: Reviewable, versioned monitoring.
3. Free Hobby plan: 10 uptime monitors and generous check quotas.
4. Clear pricing: Published plans and quotas.
5. Agent-friendly: Designed for AI coding agents.

Cons

1. Quota-based: Heavy browser checks consume quotas quickly.
2. SaaS: Checks run in Checkly’s infrastructure unless you use private locations.
3. Not full APM: Pair with tracing and metrics for root cause.
4. Playwright skills needed: Browser checks need test-writing skills.
5. Private locations gated: Not on the cheaper plans.

Usage and Links (Example)

From the homepage example:

import { PlaywrightCheck, Frequency } from 'checkly/constructs'

new PlaywrightCheck('checkout', {
  name: 'Checkout Flow',
  frequency: Frequency.EVERY_5M,
  locations: ['us-east-1', 'eu-west-1', 'ap-south-1'],
  code: { entrypoint: './checkout.spec.ts' },
})

npx checkly init
npx checkly test
npx checkly deploy

Tips: start with your most important user journey, run checkly test in CI against preview URLs, and route alerts to the owning team.

Resources:

• Checkly website
• Pricing
• Checkly CLI on GitHub

Pricing

From Checkly’s pricing page (monthly prices; annual billing saves up to 20%):

1. Hobby: $0 a month. 10 uptime monitors, 2-minute frequency, 1,000 browser/Playwright checks, 10,000 API checks.
2. Starter: $24 a month. 50 uptime monitors, 1-minute frequency, 3,000 browser checks, 25,000 API checks.
3. Team: $64 a month. 75 uptime monitors, 30-second frequency, 12,000 browser checks, 100,000 API checks, 21 locations, private locations.
4. Enterprise: custom.

Recommended for?

1. Teams using Playwright who want the same tests as production monitors.
2. Developers preferring monitoring as code.
3. Small teams starting on the free plan.
4. Not a fit as a replacement for APM or log analytics.

Conclusion

Checkly makes synthetic monitoring a natural extension of end-to-end testing, with code-first checks and clear pricing.

Watch browser-check quotas and pair it with tracing for root cause.