Kubernetes Active Remediation empowers users to detect issues, gain contextualized insights and make changes to repair Kubernetes environments—all within one integrated workflow

NEW YORK, Nov. 12, 2024 /PRNewswire/ -- Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today announced the launch of Kubernetes Active Remediation, which builds on Datadog's automated troubleshooting capabilities to provide curated remediation guidance, best practices and end-to-end issue management for Kubernetes organizations.

Traditional monitoring tools track health and performance based on metrics, but teams need deeper insights and guidance to navigate the complexities of Kubernetes environments. Teams are also often slowed down by the limited availability of their organization's internal Kubernetes experts. Without actionable recommendations, diagnosing the root cause of issues can be time consuming and resource intensive, leading to prolonged downtime and decreased operational efficiency.

Kubernetes Active Remediation offers the deeper insights at scale that teams need by providing a comprehensive overview of cluster-level resource problems ranked by their importance and relevance. After a problematic cluster or workload has been identified, teams can view consolidated troubleshooting information, including root cause analysis and recommended fixes. They can then directly trigger deployment patches for the key issues from within the Datadog platform.

"Today's announcement builds on our launch of Kubernetes Autoscaling at DASH to empower users to detect issues, gain contextual insights and make changes to their Kubernetes resources directly from Datadog's unified platform," said Yrieix Garnier, VP of Product at Datadog. "Customers are looking for help to identify an issue, curate data about it and take steps to solve it. Kubernetes Active Remediation will help customers do just that so they can resolve issues faster."

Kubernetes Active Remediation helps organizations:

• Automate root-cause analysis and detection: Recommendations are automatically issued with full contextual data and triaged to the correct owner. Curated remediation actions can also be pre-approved by the DevOps or security teams to automate the process downstream.
• Directly repair Kubernetes environments: Explanations and suggestions are provided based on troubleshooting patterns that are commonly seen in Kubernetes environments. Once the user has the full context and recommended next steps, they can directly trigger deployment patches from within Datadog to remediate the issue.
• Improve troubleshooting and remediation speed: By accelerating a user's time to detect and resolve an issue, Datadog helps application development teams be more efficient, understand root causes and automate their remediation processes.

Kubernetes Active Remediation is now in preview. To learn more, please visit: https://www.datadoghq.com/blog/datadog-kubernetes-active-remediation.

About Datadog

Datadog is the observability and security platform for cloud applications. Our SaaS platform integrates and automates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, cloud security and many other capabilities to provide unified, real-time observability and security for our customers' entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior and track key business metrics.

Forward-Looking Statements

This press release may include certain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended including statements on the benefits of new products and features. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control, including those risks detailed under the caption "Risk Factors" and elsewhere in our Securities and Exchange Commission filings and reports, including the Quarterly Report on Form 10-Q filed with the Securities and Exchange Commission on May 8, 2024, as well as future filings and reports by us. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise.

Contact

Dan Haggerty

press@datadoghq.com

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SOURCE Datadog, Inc.