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.