By default, Playwright runs test files in [parallel](./test-parallel.md) and strives for optimal utilization of CPU cores on your machine. In order to achieve even greater parallelisation, you can further scale Playwright test execution by running tests on multiple machines simultaneously. We call this mode of operation "sharding". Sharding in Playwright means splitting your tests into smaller parts called "shards". Each shard is like a separate job that can run independently. The whole purpose is to divide your tests to speed up test runtime.
When you shard your tests, each shard can run on its own, utilizing the available CPU cores. This helps speed up the testing process by doing tasks simultaneously.
In a CI pipeline, each shard can run as a separate job, making use of the hardware resources available in your CI pipeline, like CPU cores, to run tests faster.
To shard the test suite, pass `--shard=x/y` to the command line. For example, to split the suite into four shards, each running one fourth of the tests:
Note that Playwright can only shard tests that can be run in parallel. By default, this means Playwright will shard test files. Learn about other options in the [parallelism guide](./test-parallel.md).
Sharding can be done at two levels of granularity depending on whether you use the [`property: TestProject.fullyParallel`] option or not. This affects how the tests are balanced across the shards.
**Sharding with fullyParallel**
When `fullyParallel: true` is enabled, Playwright Test runs individual tests in parallel across multiple shards, ensuring each shard receives an even distribution of tests. This allows for test-level granularity, meaning each shard will attempt to balance the number of individual tests it runs. This is the preferred mode for ensuring even load distribution when sharding, as Playwright can optimize shard execution based on the total number of tests.
**Sharding without fullyParallel**
Without the fullyParallel setting, Playwright Test defaults to file-level granularity, meaning entire test files are assigned to shards. In this case, the number of tests per file can greatly influence shard distribution. If your test files are not evenly sized (i.e., some files contain many more tests than others), certain shards may end up running significantly more tests, while others may run fewer or even none.
**Key Takeaways:**
- **With** `fullyParallel: true`: Tests are split at the individual test level, leading to more balanced shard execution.
- **Without** `fullyParallel`: Tests are split at the file level, so to balance the shards, it's important to keep your test files small and evenly sized.
- To ensure the most effective use of sharding, especially in CI environments, it is recommended to use `fullyParallel: true` when aiming for balanced distribution across shards. Otherwise, you may need to manually organize your test files to avoid imbalances.
In the previous example, each test shard has its own test report. If you want to have a combined report showing all the test results from all the shards, you can merge them.
Start with adding `blob` reporter to the config when running on CI:
```ts title="playwright.config.ts"
export default defineConfig({
testDir: './tests',
reporter: process.env.CI ? 'blob' : 'html',
});
```
Blob report contains information about all the tests that were run and their results as well as all test attachments such as traces and screenshot diffs. Blob reports can be merged and converted to any other Playwright report. By default, blob report will be generated into `blob-report` directory.
To merge reports from multiple shards, put the blob report files into a single directory, for example `all-blob-reports`. Blob report names contain shard number, so they will not clash.
GitHub Actions supports [sharding tests between multiple jobs](https://docs.github.com/en/actions/using-jobs/using-a-matrix-for-your-jobs) using the [`jobs.<job_id>.strategy.matrix`](https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstrategymatrix) option. The `matrix` option will run a separate job for every possible combination of the provided options.
The following example shows you how to configure a job to run your tests on four machines in parallel and then merge the reports into a single report. Don't forget to add `reporter: process.env.CI ? 'blob' : 'html',` to your `playwright.config.ts` file as in the example above.
1. First we add a `matrix` option to our job configuration with the `shardTotal: [4]` option containing the total number of shards we want to create and `shardIndex: [1, 2, 3, 4]` with an array of the shard numbers.
1. Then we run our Playwright tests with the `--shard=${{ matrix.shardIndex }}/${{ matrix.shardTotal }}` option. This will run our test command for each shard.
1. After all shards have completed, you can run a separate job that will merge the reports and produce a combined [HTML report](./test-reporters.md#html-reporter). To ensure the execution order, we make the `merge-reports` job [depend](https://docs.github.com/en/actions/using-jobs/using-jobs-in-a-workflow#defining-prerequisite-jobs) on our sharded `playwright-tests` job by adding `needs: [playwright-tests]`.
When merging reports from different OS'es you'll have to provide an explicit merge config to disambiguate which directory should be used as tests root.
