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For teams already using Playwright

Run Playwright at scale—without building the platform around it.

Keep the tests and CI you already use. Playrunner brings runners, environments, credentials, reports, integrations, and automatic sharding into one workflow—on your infrastructure or ours—without the scripts and CI matrices that normally hold it all together.

Try Playrunner locallySee how it works

Your tests stay. Your CI stays. The glue goes.

A Playrunner workflow mid-run: a smoke test branches on failure into an OpenAI analysis and a Jira bug, and on success through Slack, a regression suite, a report, and a deploy webhook. Individual nodes carry amber warning markers showing their own execution status.
Live run state on the canvas. Every node reports its own outcome, and the branch the run actually took is drawn between them.

The problem

Playwright runs the tests. Your team runs everything around them.

A reliable run needs more than a command. It needs compute, state, conditions, schedules, credentials, artefacts, and reporting, and teams end up building that themselves, one script at a time.

The orchestration layer

The operational pieces around a Playwright run.​

Use the parts you need. The workflow model stays the same as you grow.

Existing Playwright suites

Your tests and config, unchanged. No framework to adopt.

Dedicated runners

Provision on demand: local, managed cloud, or self-hosted.

Workflow orchestration

Conditions, parallel branches, shared environment data, dependent steps.

Schedules and triggers

Start on a schedule, an API call, or a webhook.

Artefacts and reporting

Logs, Playwright reports, and artefacts stay with the run.

Extensible integrations

Package-based plugins, plus a growing marketplace.

Automatic Playwright sharding

Set the limits. Playrunner chooses the plan.

Auto mode discovers the suite before it runs, fits the useful parallelism to your runner capacity, and turns one Playwright node into a complete sharded execution.

  • Discover the real workloadPlan from the current tests, files, and projects.
  • Use capacity safelyBound shards, workers, CPU, and memory with maximums.
  • Keep one resultRun every shard concurrently, then merge the reports.
Explore Auto shardingRead the launch post
An Environment node connected to a Playwright node using an Auto plan with four shards, one failed shard, and a successful report merge.
Four shards, two workers each, and one merged report—even when a shard fails.

How it fits

Keep your suite. Change how it runs.

Start with one workflow and move only the execution you no longer want to own.

1. Bring your existing tests

Connect the repo. Your tests and config stay as they are.

2. Choose where they run

Local Docker, managed cloud runners, or your own infrastructure.

3. Define the workflow

Wire triggers, conditions, branches, and downstream systems on the canvas.

4. Inspect the complete run

Follow state and logs live. Reports and artefacts stay attached to the run.

A regression test node on the canvas splitting into two paths: a red failure branch into an OpenAI analysis and a Jira bug, and a green success branch into a Slack alert and a deploy webhook.
One result, two paths. Failures go to triage, passes go to deploy, and the condition lives on the connection rather than in a script.

Early teams wanted

Already running Playwright? Help us remove the hard parts.

We want a few teams already maintaining runner infrastructure or CI glue. Run one real workflow, tell us where it is still too hard, and shape what we build next.

Try it with your suiteTalk to us about your setup

Go deeper

Evaluate the parts that matter to your team.

Try Playrunner locallyRun the full stack against a real Playwright project.Understand workflow executionHow the API, orchestrator, and runners coordinate a run.Compare runner optionsLocal, cloud, and self-hosted execution architecture.Browse integrationsSchedules, source control, messaging, and more.Contribute to the platformExtend runners, integrations, reporting, or the product.