Playwright Monitoring
Your Playwright tests are already monitors
The exact @playwright/test spec that runs green in CI can run every minute from 20+ regions as a production monitor. Same file, two jobs. No rewrite, no recorder, no second suite to maintain.
Runs standard Playwright at the latest version. No credit card required.
proves the code shipped
proves users can still buy
Trusted by engineering teams that run Playwright in production
“We've saved a lot of time by using Playwright with Checkly.”
It only took me a few minutes to get a login check working and determine if we could log in and validate that the CDN was up.
Not another synthetic tool. The same Playwright.
Most monitoring tools ask you to rebuild your flows in their recorder or their DSL. Checkly runs the tests you already wrote, and turns them into the coverage CI never gave you.
Real Playwright, unchanged
Checkly runs standard @playwright/test at the latest version, from your own playwright.config.ts. No proprietary recorder, no vendor DSL, no fork that lags months behind the framework you already use.
CI green is not production reliable
A passing pipeline proves the build shipped. It says nothing about whether a user in Sydney can check out right now. The same spec, run continuously from real regions, is what closes that gap.
One suite, versioned in git
Your monitors are PlaywrightCheck constructs in the same repo, reviewed in pull requests and deployed from CI. No second test suite to maintain, no dashboard settings drifting out of sync.
Real Playwright, unchanged
Checkly runs standard @playwright/test at the latest version, from your own playwright.config.ts. No proprietary recorder, no vendor DSL, no fork that lags months behind the framework you already use.
CI green is not production reliable
A passing pipeline proves the build shipped. It says nothing about whether a user in Sydney can check out right now. The same spec, run continuously from real regions, is what closes that gap.
One suite, versioned in git
Your monitors are PlaywrightCheck constructs in the same repo, reviewed in pull requests and deployed from CI. No second test suite to maintain, no dashboard settings drifting out of sync.
Promote the specs you already have
The PlaywrightCheck construct points at your playwright.config.ts and turns the specs you tag into scheduled monitors. Your tests stay in your repo, unchanged, running on the same Playwright you use locally.
Reuse an existing suite instead of writing ping and string checks- Tag which specs graduate to production, leave the rest in CI
- Set regions and frequency in code, reviewed in pull requests
- Plain constructs your AI agents can read, write, and maintain
Run from where your users are
CI runs your suite once, from one machine, in one location. Checkly runs the same spec every minute from 20+ regions around the world, so you catch the failure a user in Mumbai or Sydney hits before they tell you about it.
- 20+ public locations, or private locations inside your network
- Schedules as tight as every minute, per check
- Cross-region retries absorb transient blips before alerting
- A real pass or fail from every region, not a synthetic average
When it fails, you get the why
A red run in CI hands you a stack trace and leaves the rest to you. A failed monitor captures the full Playwright trace, screenshots, network calls, and console logs, then Rocky AI reads them and tells you what broke and where.
- Full Playwright traces and screenshots stored with every run
- Rocky AI root-cause analysis, not just a red X
- Network and console evidence captured automatically
- Verified alerts to Slack, PagerDuty, SMS, phone, and 18+ channels
The Buy now button never became clickable. The payments API returned 503 from ap-southeast-2, so the cart never advanced to confirmation. Users in that region could not complete a purchase.
- •
Step timed out on getByRole('button', { name: 'Buy now' }) after 10000ms.
trace - •
POST /api/payments returned 503 Service Unavailable, 4 consecutive runs.
network
You could run Playwright on a cron. Until you can't.
A scheduled CI job runs the tests. Everything that makes those runs trustworthy in production, you build and maintain yourself. Here is where that gets expensive.
Reuse your existing specs
Run from real user regions
Retries that absorb flake
Alerting to on-call
History and dashboards
Root cause on failure
Key facts
Playwright tests as monitors, in facts
What actually changes when a suite moves from CI into production monitoring, and what you still have to plan for.
- What changes
The schedule and the vantage point
A Playwright test in CI runs on merge, from your build machine. The same test as a monitor runs continuously, from outside your network, against production.
- What does not change
The test code
Checkly runs Playwright itself, including multi-file suites, fixtures, and project configuration. There is no second scripting model to port to.
- Where it runs
22 public locations, plus private locations
Run the same suite from several regions to separate a global regression from a regional one.
- What a failure gives you
Traces, screenshots, and network logs
A failed run returns the Playwright trace and the OpenTelemetry trace for the requests it made, so the next step is a service rather than a reproduction session.
- How it is configured
A check definition in your repository
Point a check at a spec file or a Playwright project, set the frequency and locations, and deploy it from CI with the Checkly CLI.
Checkly CLI docs (opens in a new tab)Checkly monitoring as code docs (opens in a new tab)
- What to plan for
Production-safe test data
A test that writes to production needs a dedicated account, cleanup, and idempotent steps. That work is on you, not on the runner.
Facts checked . Vendor pricing and feature pages change without notice, so verify anything decision-critical against the linked source.
Fit check
Should your Playwright suite become production monitoring?
Checkly is a strong fit when
- You already have a Playwright suite covering the flows that matter and want them checked continuously in production.
- You want the same engineers who wrote the tests to own the monitors, in the same repository.
- You need to know which region a failure is limited to, not just that a test went red.
Checkly may not be the best fit when
- You have no end-to-end tests yet and want monitoring live today. Start with uptime and API checks and grow into browser checks.
- Your tests depend on seeded fixtures or a reset database that cannot exist in production.
- You want performance data from real user sessions rather than scripted runs.
Ship your first monitor in an afternoon
Point Checkly at your Playwright config, tag a spec, and deploy. The tests you already trust in CI become the production coverage you have been missing.