--- title: "Alternative to DataDog for Playwright Testing" description: "DataDog vs Currents" canonical: "https://currents.dev/posts/datadog-vs-currents" updated: "2025-06-26" --- # Alternative to DataDog for Playwright Testing Published 2025-06-26 by Currents Team. Canonical URL: https://currents.dev/posts/datadog-vs-currents DataDog vs Currents --- In this article, we'll compare Currents and DataDog specifically for Playwright testing, to help you make an informed decision. We'll be looking at DataDog's [Test Optimization](https://docs.datadoghq.com/tests/) product. ## **Overview** ### **DataDog** DataDog is a widely respected observability platform trusted by engineering teams across the globe. With deep integrations across infrastructure, applications, and services, it offers powerful tools for monitoring, logging, tracing, and more. Its testing solution supports Playwright through its JavaScript tracer, offering features like flaky test detection, analytics, code coverage and more. #### **How it Works** DataDog does not offer a native Playwright reporter, and instead uses a [Tracer](https://github.com/DataDog/dd-trace-js) to instrument tests and collect telemetry. It uses Node's [diagnostics_channel](https://nodejs.org/api/diagnostics_channel.html) to listen to Playwright lifecycle events. DataDog’s approach, while useful, is more limited than a native Playwright reporter. Without native integration, it lacks deep runtime awareness and access to Playwright-specific metadata, making it less effective for debugging and observability. Test Details: Attempt Screenshots 1. Playwright runs on your own CI/CD pipeline. 2. Playwright uses browsers running on your CI. 3. Test execution is traced via the Datadog Tracer and visualized in the Datadog dashboard. ### **Currents** Currents is a cloud-based test observability platform designed to optimize test execution. It is particularly effective for managing large test suites and ensuring their reliability over time. Currents is designed as a best-in-class Playwright observability platform. Its native Playwright reporter integrates with existing CI/CD pipelines to optimize test execution, provide real-time insights, and enhance team productivity. It offers reporting, debugging, analytics, flaky test detection, faster executions with test orchestration, and historical insights. #### **How it Works** 1. Playwright runs on your own CI/CD pipeline. 2. Currents [orchestrates test execution to optimize parallel runs](https://docs.currents.dev/guides/parallelization-guide/pw-parallelization/playwright-orchestration). 3. Playwright uses browsers running on your CI. 4. Test results are collected in the Currents dashboard. ## **Highlights** ### 1. **Playwright Native Capabilities** DataDog Test Run Details DataDog provides a helpful view into the trace of your Playwright tests; however, it lacks key debugging artifacts such as screenshots, video recordings, and terminal output. Without these, it can be harder to understand what actually happened during a failing test or reproduce bugs locally. Additionally, test results are only reported after execution is complete, rather than streamed in near real time, making it harder to catch issues early and potentially less resilient to crashes or CI timeouts. DataDog also lacks data and visual cues to indicate which Playwright project a test belongs to. Since Playwright projects are commonly used to run the same test suite across multiple browsers, this creates confusion in the dashboard. Test runs appear duplicated, with no indication of whether a given result came from Chromium, Firefox, or WebKit. You just see the same test name multiple times and can’t tell which browser or configuration it was run against, without going deeper into the test details. Test Details: Attempt Screenshots By contrast, Currents shows you everything! Even when a test crashes or times out. Since [each step is streamed in near real-time](https://docs.currents.dev/guides/parallelization-guide/step-level-reporting), each test attempt is tracked with full context: logs, errors, console output, traces, screenshots, and videos. You can immediately see the last executed step before the failure, making it much easier to understand what went wrong and fix the issue quickly. Furthermore, Currents has full support for Playwright's native capabilities, including [test annotations](https://playwright.dev/docs/test-annotations), [trace viewer](https://playwright.dev/docs/trace-viewer-intro), [code coverage](https://playwright.dev/docs/api/class-coverage) and [visual testing](https://playwright.dev/docs/test-snapshots). | Capability | DataDog | Currents | | -------------- | ------- | ---------------------------------------------------------------------------------- | | Logs | ✅ | ✅ | | Errors | ✅ | ✅ | | Screenshots | ❌ | ✅ | | Videos | ❌ | ✅ | | Projects | ❌ | ✅ | | Tags | ❌ | ✅ | | Trace Viewer | ❌ | ✅ | | Attachments | ❌ | ✅ | | Annotations | ❌ | ✅   [Learn more](https://docs.currents.dev/guides/playwright-annotations) | | Code Coverage | ❌ | ✅   [Learn more](https://docs.currents.dev/guides/coverage) | | Visual Testing | ❌ | ✅   [Learn more](https://docs.currents.dev/guides/playwright-visual-testing) | Note: Although Playwright tags are not supported, DataDog supports [their own tags](https://docs.datadoghq.com/tests/setup/javascript/?tab=playwright#adding-custom-tags-to-tests) with custom Playwright annotations. DataDog also has code coverage support, but it is [not available for Playwright](https://docs.datadoghq.com/tests/code_coverage?tab=javascripttypescript) as of June 25th, 2025. ### 2. **Speeding up Tests** While fundamentally different, both products offer smart solutions to accelerate test execution. However, **DataDog’s solution isn’t available for Playwright**, and it currently offers no alternative to help speed up Playwright tests. **DataDog:** [Test Impact Analysis](https://docs.datadoghq.com/tests/test_impact_analysis) automatically selects and runs only the relevant tests for a given commit based on the code being changed. As of June 25th, 2025, this feature does not support on Playwright, and is only available for Jest, Mocha, Cucumber, and Cypress. **Currents:** [Orchestration](https://docs.currents.dev/guides/ci-optimization/playwright-parallelization) smartly distributes your tests to be run in parallel, reducing the time it takes to run your tests and cutting CI costs. Customer Case:{" "} { "How FundGuard sped up their CI E2E test pipeline by 50% and cut costs down by 70%" } ### 3. **GitHub Integration** **DataDog:** Supports posting [test summaries](https://docs.datadoghq.com/tests/developer_workflows#test-summaries-in-github-pull-requests) as comments to GitHub PRs. Additionally, it provides convenient shortcuts to create issues in GitHub, which can be useful for open source projects, or companies using GitHub as their primary issue tracker. **Currents:** Supports posting [test summaries](https://docs.currents.dev/resources/integrations/github/github-app#run-comment) as comments to GitHub PRs, and [commit status checks](https://docs.currents.dev/resources/integrations/github/github-app#commit-status-checks), which helps teams quickly understand test results in context, block merges on failed tests, and surface flaky or quarantined tests directly in the developer workflow. ## **Feature Comparison Table** Here's a detailed comparison of how these two solutions stack up against each other: | Category | DataDog | Currents | | ---------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Setup & Integration** | | | | **Test Execution and Performance** | | | | **Reporting** | | | | **Debug Capabilities** | | | | **Analytics** | | | | **Workflow Automation** | | | | **Team Collaboration** | | | | **Security** | | | | **Infrastructure** | | | | **Cost Model** | | | ## **Conclusion** Datadog is a strong choice for teams looking to extend their existing observability stack into the testing space. While it offers a broad set of features for test optimization and CI visibility, most of these are not yet supported for Playwright. This limits its usefulness for teams relying on Playwright for end-to-end testing. For teams invested in Playwright, using a platform with a native reporter is key to fully leverage the framework’s capabilities. Currents stands out as the purpose-built choice. With native Playwright support, real-time streaming, intelligent orchestration, and deep GitHub/GitLab integrations. Currents enables faster feedback cycles, deeper debugging, simpler CI workflows, and more efficient scaling.