Run the same Playwright test suite in separate CI jobs with a different --shard=current/total value in each job. For four jobs, use --shard=1/4 through --shard=4/4. To combine their results, have each job save a Playwright blob report, collect the reports, then run npx playwright merge-reports --reporter html ./all-blob-reports.
How Playwright sharding works
Sharding divides a test run across independent CI jobs or machines. The shard index is 1-based, and every job must use the same total while receiving a different index. For example, four concurrent jobs run the same code and configuration, with shard arguments 1/4, 2/4, 3/4, and 4/4. See Playwright’s sharding documentation and command-line reference.
Shards are not extra workers inside one machine: they are separate test runs that CI must launch. Playwright workers add another layer of concurrency within each run. A practical arrangement is to start with several CI shard jobs and one worker per job, then tune the worker count based on runner capacity and suite stability.
Choose shard and worker counts
Start with stable CI settings
Playwright recommends setting workers: 1 in CI “to prioritize stability and reproducibility.” This is a starting recommendation, not a requirement or universal fastest setting. More workers can help on capable runners, but also increase CPU and memory contention and may expose tests that share mutable state. See Playwright’s CI guidance and parallelism documentation.
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import { defineConfig } from '@playwright/test';
export default defineConfig({
workers: process.env.CI ? 1 : undefined,
reporter: process.env.CI ? 'blob' : 'html',
});This configuration uses a blob reporter in CI so shard results can later be merged, while retaining an HTML report for a local run. Adjust the worker setting only after checking runner resources and test behavior.
Balance across files or individual tests
By default, Playwright distributes files among shards, while tests within a file run sequentially. If a few files contain most of the suite’s work, shards may finish at noticeably different times. Setting fullyParallel: true allows distribution at individual-test granularity and can improve balance when tests are safe to run independently. Static skips and fixmes are not counted in shard balancing, according to the sharding guide.
import { defineConfig } from '@playwright/test';
export default defineConfig({
fullyParallel: true,
});Do not enable full parallelism solely to make shards look more balanced. It requires tests to tolerate independent execution. Browser contexts isolate browser state, but do not isolate external backend data: tests using the same account, records, or other shared resources can still collide. Use distinct test data or another isolation strategy. Playwright discusses these behavior differences in its parallelism guide.
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Run one shard in each CI job
For four jobs, each job runs the same command with its own index:
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npx playwright test --shard=1/4
npx playwright test --shard=2/4
npx playwright test --shard=3/4
npx playwright test --shard=4/4In a CI matrix, map the provider’s job index to Playwright’s 1-based index. Ensure all jobs use the same shard total and test code, and that no two jobs receive the same index. The provider’s matrix syntax and variable names differ; Playwright’s CI guide includes examples for GitHub Actions, CircleCI, and GitLab CI.
GitHub Actions matrix example
This illustrative workflow runs four shard jobs, uploads each job’s blob report under a distinct artifact name, and merges the artifacts in a separate job. Adapt the checkout, Node version, dependency installation, and browser installation to your project.
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name: Playwright tests
on: [push, pull_request]
jobs:
test:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
shard: [1, 2, 3, 4]
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: 20
- run: npm ci
- run: npx playwright install --with-deps
- run: npx playwright test --shard=${{ matrix.shard }}/4
- uses: actions/upload-artifact@v4
if: ${{ !cancelled() }}
with:
name: blob-report-${{ matrix.shard }}
path: blob-report
retention-days: 7
merge-reports:
if: ${{ !cancelled() }}
needs: [test]
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: 20
- run: npm ci
- uses: actions/download-artifact@v4
with:
path: all-blob-reports
pattern: blob-report-*
merge-multiple: true
- run: npx playwright merge-reports --reporter html ./all-blob-reports
- uses: actions/upload-artifact@v4
with:
name: playwright-report
path: playwright-report
retention-days: 7The upload step is conditioned so it can preserve a report when tests fail, where the runner permits; cancellation can still prevent artifact collection. Distinct artifact names avoid shards overwriting one another. A merge job should gather every available shard artifact before merging. Consult the current Playwright CI examples for provider-specific details.
Merge shard results into one HTML report
Set the CI reporter to blob. Each shard then writes an archive with run details and attachments. Upload or otherwise preserve each archive, download all shard outputs into one directory, and run:
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npx playwright merge-reports --reporter html ./all-blob-reportsThe merged HTML report is written to playwright-report by default. Playwright’s reporter documentation explains the blob reporter and merging workflow. If merging runs from different environments rather than shards, label those environments as described in the merge guidance so their results remain distinguishable.
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Improve speed without sacrificing reliability
- Measure shard completion times. More shards do not guarantee proportionally shorter runs. Suite distribution, job startup, runner capacity, and test behavior affect elapsed time; official documentation establishes no universal ideal shard count or speedup.
- Address uneven shards. Large files can skew file-level distribution. Consider
fullyParallel: trueonly after confirming independent test behavior. - Increase workers cautiously. First understand CPU and memory available to each runner. Raising worker counts can increase contention and reveal shared-state problems.
- Keep test data independent. Separate browser contexts do not prevent concurrent tests from modifying the same backend account or record.
- Avoid unnecessary browser installs. Install only browser engines your suite uses where appropriate; Playwright’s best-practices guide recommends limiting browser downloads to those needed.
- Retain reports after failures. Configure artifact upload to run despite test failure when your CI provider allows it, and use unique artifact names for every shard.
Troubleshoot common sharding problems
A shard reports no tests or the suite appears incomplete
Check that every job uses the same total, each index is between 1 and that total, and all indices are represented exactly once. Confirm that every job checks out the same test revision and uses compatible configuration and dependencies.
One shard takes much longer than the others
With default file-level distribution, a small number of long files can make work uneven. Inspect the suite’s file sizes and durations, then evaluate fullyParallel: true if test isolation permits it. Raising worker counts may help only when runner resources are sufficient and the tests remain reliable.
Tests fail only when run in parallel
Look for shared external state such as common accounts, records, or resources modified by concurrent tests. Assign unique data per test or shard, or serialize the tests that cannot safely overlap. Browser context isolation alone does not protect a shared backend.
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The merged report is missing shard results
Verify that every shard’s blob report artifact was uploaded, that artifact names are unique, and that the merge job downloads all artifacts into the directory passed to merge-reports. Also check that the upload step runs after a failed test command where the CI provider supports that behavior.
The merge command cannot find reports
Check the downloaded directory path and confirm it contains the blob report files rather than only nested artifact folders or unrelated files. Make the merge command’s input directory match the actual download layout.
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Frequently Asked Questions
Can I run Playwright sharding locally?
The shard option divides a test run, but the wall-clock benefit discussed here comes from launching separate shard runs concurrently; a single sequential command does not create concurrent CI machines.
Does Playwright guarantee equal test counts or equal durations per shard?
No equal-duration guarantee is established. File sizes, test durations, and skipped or fixed tests affect how balanced the work is.
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