Playwright Dashboard
A playwright dashboard shows test results, pass rates, and failure logs in one view. Teams set it up by sending test run data to a web viewer. Most teams start with local HTML reports and then move to hosted dashboards. Hosted viewers let the whole team inspect traces, screenshots, and error logs together. Still, test runners and dashboard backends often hold broad roles on shared systems. If a test runner has wide database rights, one bad script can alter data. How a playwright dashboard work
GitLab Security Dashboard: the complete guide
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A playwright dashboard shows test results, pass rates, and failure logs in one view. Teams set it up by sending test run data to a web viewer. Most teams start with local HTML reports and then move to hosted dashboards. Hosted viewers let the whole team inspect traces, screenshots, and error logs together. Still, test runners and dashboard backends often hold broad roles on shared systems. If a test runner has wide database rights, one bad script can alter data.
How a playwright dashboard works in practice
The test runner executes browser steps and records every action in a trace file. When the run finishes, a reporter sends those logs to the dashboard server. The server stores test results, timing data, and failure images in a database. Users log in to the web app to check broken tests and flaky runs. Teams also link the dashboard to source control so pull requests show test status.
To set this up, engineers pick a built-in reporter or an outside reporting service. The build pipeline holds an API key that lets the runner upload test artifacts. On the dashboard side, admins create user roles for developers and quality engineers. Viewers can read test logs, while admins can delete old runs or change project rules. The test suite itself also needs credentials to seed data into staging databases.
What native dashboard permissions solve and leave open
Built-in dashboard roles control who can log in and view stored test reports. They stop guests from deleting project history or changing webhook rules in the web app. Role settings also let teams split test results by project or team name.
Still, app roles only check who logs in to the reporting interface. They do not inspect what the test runner or backend database queries do in flight. Test scripts often connect to staging databases with admin keys to set up state. Those same test logs can capture real emails, phone numbers, or card numbers from screens. If a developer queries the dashboard database directly, native web roles do not apply. Broad database keys let a single command drop tables or export raw user records. Teams need a way to check individual commands and mask sensitive fields in results.
GitLab Security Dashboard: architecture patterns and best practices
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Managing test runner and database credentials
Shared test setups often reuse one static database account across many build pipelines. When a test fails, engineers also log in to staging databases to check the state. Sharing one static password makes it hard to see who ran which query. If that password leaks in a build log, anyone on the network can use it.
A safer pattern separates human debug sessions from automated test runner accounts. Each engineer should log in with their own identity instead of a shared team password. Read-only checks should not use the same role that runs schema changes. Masking rules should rewrite matched fields like emails and card numbers in query results. Recording every command and query gives the security team a clear audit trail.
Add runtime guardrails and masking beside your databases and APIs
Login rules, role grants, and CI checks govern who connects to your stack. Yet any allowed script, engineer, or AI agent still runs commands with the full scope of its role. For workloads on Postgres, MySQL, SQL Server, MongoDB, ClickHouse, Kubernetes, SSH, or internal HTTP services, hoop.dev sits beside the service as an open-source proxy, a sidecar for your database or API.
Before a query runs, hoop.dev guardrails check the statement against your rules. An AI Analyzer you configure can score intent or hold risky calls for human review. Next, hoop.dev data masking rewrites sensitive fields in responses, and each verdict is logged per listener. Explore the MIT-licensed project on GitHub.
Frequently asked questions
What is the difference between a local HTML report and a playwright dashboard?
A local report saves one test run as static files on a single machine. A dashboard stores history across many runs so teams can track flaky tests over time.
Why do test traces and dashboard databases create data privacy risks?
Test suites often run against staging databases that contain copies of real customer data. Screenshots, network logs, and database queries can capture emails, phone numbers, or card numbers.
How should teams limit database permissions during automated test runs?
Give the test runner a narrow role that only writes to specific test tables. Require individual logins and command checks when engineers inspect the database by hand.