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Use Playwright to capture pages in a GitLab CI job, save the image files in a known directory, and archive that directory as a job artifact. If you have a Playwright Test suite, GitLab can run sharded copies of the job using parallel and Playwright’s --shard option. A plain list of URLs does not get distributed automatically; your script must partition that list itself.
Choose the right bulk-capture design
“Bulk screenshots” can mean capturing many URLs in one script or dividing a Playwright Test suite across CI jobs. These are different approaches:
- URL-list script: Your code reads a URL list and captures each page. To run it across jobs, partition the list yourself, for example by assigning each URL a stable index and selecting the entries for that job.
- Playwright Test suite: GitLab can launch multiple instances of the same job, while Playwright’s shard option assigns portions of the test suite to those instances. The tests must use Playwright Test’s shard semantics.
The GitLab CI examples below use the second design. Playwright’s official GitLab CI guide documents a Docker-image job and sharding patterns.
Set up Playwright screenshot output
Configure the capture code to write screenshot files into a directory inside the repository checkout, such as screenshots/. Ensure the directory exists before writing, and use stable, unique file names so parallel jobs do not produce ambiguous outputs. For example, derive a file name from a page identifier rather than using a single shared name for every capture.
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Playwright’s screenshot API guide covers capturing page screenshots. For a suite that already uses Playwright Test, the key CI requirement is that each test writes its output to the expected path. A screenshot of a page can be saved with the page screenshot API; a test can also use Playwright Test’s screenshot assertions where that suits the test workflow.
Run Playwright Test as a GitLab CI job
Add a job that uses a Playwright container image, installs the project dependencies, runs the tests, and uploads the screenshot directory. This configuration adapts the documented patterns; it has not been executed as a project-specific pipeline.
stages:
- capture
screenshots:
stage: capture
image: mcr.microsoft.com/playwright:v1.63.0-noble
script:
- npm ci
- npx playwright test
artifacts:
when: always
paths:
- screenshots/
expire_in: 1 weekThe image tag is the version shown in the Playwright CI guide accessed in October 2026. Match the Playwright package version in your project to the container image version, and check the current guide before adopting a tag because versions change. The repository must include the required package manifest and lockfile for npm ci, as well as a Playwright Test configuration and tests that perform the captures.
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artifacts:paths is relative to the job’s repository checkout. when: always is included here so files can be retained when the job fails; GitLab otherwise uploads artifacts on successful jobs by default. The one-week expiry is an example choice, not a recommendation for every project. Omit expire_in to use the instance default, or choose a retention period appropriate to your team.
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Shard a Playwright Test suite across jobs
For a sufficiently large suite, set GitLab’s parallel count and pass the predefined node variables to Playwright:
stages:
- capture
screenshots:
stage: capture
image: mcr.microsoft.com/playwright:v1.63.0-noble
parallel: 4
script:
- npm ci
- npx playwright test --shard=$CI_NODE_INDEX/$CI_NODE_TOTAL
artifacts:
when: always
paths:
- screenshots/
expire_in: 1 weekGitLab creates multiple instances of the job. Each receives a different CI_NODE_INDEX and the shared CI_NODE_TOTAL; together, those values tell Playwright which shard to run. Playwright’s documentation recommends a single worker in CI by default for stability and reproducibility, with sharding across CI jobs as a way to distribute a larger suite. Workers inside a job and GitLab’s parallel job instances are separate forms of concurrency.
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Do not assume that this command divides an arbitrary array of URLs. It divides Playwright Test work. If your captures run in a standalone script rather than tests, implement URL partitioning in that script or adapt the captures into Playwright Test cases.
Combine browser projects and shards
If you need multiple configured browser projects as well as shards, GitLab supports parallel:matrix. Each matrix combination starts a job, so the number of jobs—and therefore browser launches, resource demand, and artifact output—grows with the combinations. Use the project and shard variables in the command only after defining matching values in the matrix; follow Playwright’s current GitLab CI examples for the exact pattern.
Control concurrency and avoid slowdowns
GitLab’s current YAML reference permits a numeric parallel value from 1 through 200. That is a configuration range, not a promise that the requested jobs will run at once. Actual throughput depends on available runner concurrency and instance-level active-job limits; excess jobs can wait in the queue.
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Choose a shard count based on the capacity available to the project and the target site’s limits. Consider CPU and memory per runner, the number of browser processes, the site’s request-rate restrictions, test runtime, and the amount of output. More jobs can reduce the work assigned to each job, but can also increase queueing, resource contention, requests to the site, and artifact volume. There is no universally optimal count established by the documentation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep and retrieve the screenshot artifacts
GitLab archives files and directories listed under artifacts:paths. By default, later stages fetch artifacts from earlier stages; use dependencies or needs:artifacts when you want to control which outputs are downloaded. For several parallel jobs, plan how to identify which job produced each file. Use unique names or directories that include a shard or job identifier rather than relying on same-named outputs to combine cleanly.
GitLab’s job artifacts guide states that the default maximum artifact file size is 100 MB for the final archive. This is an archive limit, not a stated per-image limit. Check the effective limit for your project or instance before scaling up. If the archive is too large, consider reducing capture dimensions or image quality, capturing fewer pages per job, or adjusting the permitted limit through the appropriate GitLab administration.
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Set access deliberately when screenshots may expose private pages, account details, or other content visible to the runner. GitLab documents artifacts:access controls for artifact UI and API access, but notes that these controls do not necessarily prevent job-token access through runner APIs. Avoid publishing internal captures through a public Pages site unless you have checked the project’s access configuration.
Troubleshoot common failures
- No screenshots appear in the artifact: Confirm the capture routine writes to the path listed under
artifacts:paths, that the path is relative to the checkout, and that the job reaches the code that writes the files. Check the job log for capture errors. - Some shard jobs have no captures: A shard may receive no applicable tests if the suite is too small for the chosen shard count or the test selection does not match the sharding plan. Check Playwright’s shard output and right-size the shard count.
- Parallel jobs overwrite or confuse outputs: Give each page a unique, stable name and, if needed, include the shard identifier in the output path. Confirm each job writes under the directory archived by GitLab.
- Jobs queue instead of running together: The configured parallel count does not create additional runner capacity. Check the runners’ concurrency settings and applicable instance active-job limits.
- The artifact upload fails because it is too large: Check the final archive size against the project or instance limit. The documented default maximum is 100 MB for the archive; reduce output volume or arrange an appropriate limit change.
- Captures fail only on the target website: Authentication, consent handling, lazy loading, page readiness, and rate limits are site-specific. Inspect the browser and job logs, then adjust the capture flow and concurrency for that site rather than assuming GitLab sharding resolves those conditions.
Or skip the browser setup
If your goal is simply to request screenshots without maintaining browser automation in CI, ScreenshotNeo offers a website screenshot API and MCP server. One GET request can return an image or PDF. For an API key and the available parameters, see the ScreenshotNeo documentation.
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webpScreenshotNeo accepts cookie and consent banners before capture and removes more than 60 known consent platforms, newsletter popups, and chat widgets; each of those steps can be turned off. Bot checks and CAPTCHAs, blank pages, timeouts, failed loads, and cache hits are not billed, and responses identify the page verdict and billing status in headers. Its MCP server provides take_screenshot, get_page_info, and capture_pdf for AI agents and MCP clients. The Free plan includes 1,000 screenshots per month with no card; paid plans start at $5 for 3,000 screenshots. Every feature is available on every plan.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsFrequently Asked Questions
Does GitLab’s Playwright sharding split a plain list of URLs?
No. The documented --shard approach distributes Playwright Test work; a standalone URL-list script needs its own partitioning logic.
Can GitLab merge screenshots from all parallel jobs into one artifact automatically?
Each parallel job produces its own job artifacts. Give outputs clear, unique names and retrieve the artifacts through GitLab’s job or pipeline interface, or use a later job configured to fetch the needed artifacts.
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