Checkly now supports running checks in parallel from multiple locations. Parallel scheduling allows for faster discovery of regional outages and ensures you are always aware of the status of your service from every corner of the world.

Parallel scheduling is an addition to our existing scheduling strategy of round-robin, where each check run is executed on a single location. Compared to round-robin, parallel scheduling can allow you to detect regional outages up to 20x faster than before, depending on how many locations you are monitoring.

Alerts are sent as soon as a location is registered as failing or degrading, minimizing the time from failure to your engineers being notified.

Running a check in parallel

You can select if a check should be executed in parallel from all locations or one at a time, round-robin style, in the check or group settings. Just go to ‘Scheduling & Locations’ when editing a check.

The scheduling strategy can also be configured via the CLI:

import { ApiCheck, AssertionBuilder } from 'checkly/constructs'

new ApiCheck('hello-api-1', {
  name: 'Hello API',
  runParallel: true,
  locations: ['eu-central-1', 'us-east-1'],
  request: {
    method: 'GET',
    url: 'https://mac-demo-repo.vercel.app/api/hello',
    assertions: [
      AssertionBuilder.statusCode().equals(200)
    ],
  }
})

Live update

When scheduling a parallel check, the UI lets you view the progress, as the check run completes per location.

Parallel check runs already include support for the CLI, Terraform provider, public API, Private locations, and more. Note that during beta, dashboards are not fully supported.

Pricing and availability

• Parallel check scheduling is available on all current plans: Hobby, Team, and Enterprise. Deprecated plan types are not supported.

• Each location selected for a check running in parallel does a full check run per execution. An API check that runs in five locations will be billed for five check runs per execution.

Additional resources

• Global locations and scheduling documentation

• CLI documentation

• Terraform provider documentation

• If you have questions or feedback, join our Slack community and let us know.

We wish you happy holidays and look forward to hearing what you think of parallel scheduling!