NEW YORK — Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today announced Datadog Kubernetes Autoscaling, a set of capabilities that intelligently automates resource optimization and can automatically scale customers’ Kubernetes environments based on real-time and historical utilization metrics. With this announcement, Datadog is the first observability vendor to enable customers to make changes to their Kubernetes environments directly from the platform.

When deploying applications on Kubernetes, teams often choose to overprovision resources as a way to avoid infrastructure capacity issues from impacting end users. This can lead to a large amount of wasted compute and increased cloud costs. In fact, according to Datadog’s recent report, State of Cloud Costs 2024, 83% of container costs were associated with idle resources. For this reason, it’s critical organizations have a solution in place which can monitor resource usage and optimize infrastructure performance and computing costs while ensuring applications remain performant with enough resources to scale.

Datadog Kubernetes Autoscaling continuously monitors and automatically rightsizes Kubernetes resources. This leads to significant cost savings for an organization’s cloud infrastructure and helps to ensure optimal application performance for workloads, improved user experiences and better ROI on container assets. Customers are able to identify workloads and clusters with a high number of idle resources, implement a one-time fix through intelligent automation or enable Datadog to automatically scale the workload on an ongoing basis. These new capabilities empower operators to decide the right balance on cost and user experience based on their risk profiles.

“Containers are a leading area of wasted spend because so many costs are associated with idle resources, but organizations also can’t risk degrading performance or not having enough resources to scale. The key for businesses is to find a balance between control and automation where they can automate actions when they are ready,” said Yrieix Garnier, VP of Product at Datadog. “Datadog Kubernetes Autoscaling provides this balance. By connecting automated Kubernetes rightsizing with real-time cost and performance data, Datadog is the only enterprise-grade, unified platform that provides end-to-end observability, security and resource management at scale for any Kubernetes-driven organization.”

Datadog Kubernetes Autoscaling helps organizations balance flexibility, control and automation so that they can:

• Control Cloud Costs: Optimize cloud costs and improve application performance with automated resource scaling for Kubernetes workloads within the Datadog platform.
• Simplify, Democratize and Automate Resource Optimization: Teams can leverage a unified view and an intuitive UI that displays Kubernetes resource utilization and cost metrics, making it simple for any team member to understand and scale resources.
• Unify Monitoring and Resource Management: Datadog’s unified, enterprise-grade platform gives organizations full visibility into how rightsizing impacts their workload and cluster performance, backed by high-resolution trailing container metrics, so teams can take action based on this rich context.

Datadog Kubernetes Autoscaling is now in beta. To learn more, please visit: https://www.datadoghq.com/blog/datadog-kubernetes-autoscaling.

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

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