Datadog announced the general availability of its Continuous Integration (CI) Visibility product.
With insights into continuous integration pipelines, CI Visibility enables developers and engineering organizations to quickly determine and fix the root cause of issues detected in build and testing pipelines.
Datadog CI Visibility provides advanced monitoring and observability capabilities that not only help development and engineering teams understand when an issue occurs in their CI pipeline, but also provide the insights to help identify why the issue is occurring and how to resolve it. It does so by providing deep, end-to-end visibility across each stage of your development pipeline and each step of your test execution history. This new capability allows engineering teams to address CI issues quickly and maintain more efficient, reliable pipelines.
“Exceptional experiences that empower developers to stay in flow and achieve more is at the core of everything we do at GitHub," said Erica Brescia, Chief Operating Officer, GitHub. “We recently partnered with Datadog on integrating Actions ─ the #1 CI service for public and private repositories on GitHub ─ with Datadog’s new CI Visibility product to bring insights to developers' Actions pipelines. This experience offers an entirely new level of observability where developers need it most, and allows them to build, test, and ship faster. We’re excited to continue our partnership with Datadog and further improve the experience for developers around the world.”
“Improving DevOps performance requires transparent monitoring of KPIs such as release frequency and velocity," said Nima Badiey, VP Global Alliances at GitLab Inc. “Datadog CI Visibility helps Datadog users to monitor their GitLab CI/CD pipeline events and job information to gain deep, granular insights on pipeline and test performance over time. Operational insight is key to shipping code faster and more efficiently.”
“The combined power of Datadog and CircleCI makes life easier for DevOps teams. CircleCI’s insights can easily integrate into Datadog users' workflows to help them make even more informed decisions when an event occurs in their pipeline,” said Tom Trahan, VP Business Development, CircleCI. “To augment this data with observability insights, users can leverage Datadog CI Visibility to visualize key metrics such as build duration and failure rates, as well as detect flaky tests to ensure smooth, reliable workflows.”
“CI/CD is a core part of the DevOps toolkit, yet, until now, developers have never had the level of visibility into earlier-stage workflows that they have enjoyed in production,” said Ilan Rabinovitch, Senior Vice President, Product and Community, Datadog. “With the release of Datadog CI Visibility, we are delivering industry-first observability that extends from production environments to pre-production development and testing pipelines. This enables organizations to improve developer productivity by delivering more robust code more quickly—and ultimately deliver more resilient digital experiences at the speed that today’s customers demand.”
Datadog’s CI Visibility product delivers:
- Pipeline visibility: Visualize pipeline data across CI providers in a single pane of glass, and identify opportunities to improve the performance and reliability of your workflows.
- Testing visibility: Identify and debug flaky tests before they degrade the reliability of your test suites.
- Advanced performance analytics: Track the historical performance of your tests to identify regressions over time and view the code commit that introduced the flaky test. Visualize each service a test interacts with to understand why tests are failing, automatically surface common errors to reveal systemic issues, and correlate test results with related logs and network performance data.
- Support for heterogeneous environments: Out-of-the-box support for multiple CI providers, including Buildkite, CircleCI, GitHub Actions, GitLab and Jenkins, as well as instrumentation for tests in multiple languages, including Java, JavaScript, .NET, Python, Ruby and Swift.
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