Akamas is available as an integration in the Datadog Marketplace. The integration collects Kubernetes metrics from Datadog and turns them into ready-to-apply optimization recommendations. Akamas then sends those recommendations back into Datadog as events. Teams optimize pods, nodes, and application runtimes without leaving the platform they already use.
This brings Akamas’ autonomous optimization into the Datadog ecosystem. It helps developers, DevOps teams, and SREs unlock more performance, reliability, and efficiency in Kubernetes environments.
Actionable optimization insights, inside Datadog
Akamas generates full-stack recommendations for Kubernetes applications. These span pod sizing, cluster autoscaling, and the tuning of JVM and Node.js heap and garbage-collection settings.
With this integration, you can view Akamas-identified reliability risks directly within Datadog. The more your stack is optimized, the fewer reliability risks you face.
How the Akamas Datadog integration works
Akamas perfectly complements Datadog’s offering by turning observability data into proactive recommendations.
Akamas collects Kubernetes-related metrics from Datadog. These cover both infrastructure — clusters, nodes, and workloads — and application runtimes such as the JVM and Node.js. Akamas analyzes these performance and reliability patterns. It then sends the optimization opportunities it finds back into Datadog as events.
These insights help teams:
- Identify performance and efficiency improvements without switching tools
- Make smarter decisions around configuration and scaling
- Stay ahead of potential reliability issues
From observability data to proactive optimization
Akamas complements Datadog by turning observability data into proactive recommendations. Modern cloud-native environments are dynamic and complex. This integration bridges observability and optimization. Teams gain visibility into where they can do more with less, right from their monitoring platform.
The result is a tighter loop: the telemetry you already collect in Datadog becomes the input for continuous Kubernetes optimization.
Backed by analyst recognition
Akamas was named a Leader and Outperformer in the 2026 GigaOm Radar for Cloud Resource Optimization, extending a four-year Outperformer track record. The Datadog integration brings that same optimization engine into a platform your teams open every day.
Get started
Ready to drive efficiency and performance across your Kubernetes environments? Get Akamas Insights and connect it to Datadog; thanks to this integration, ready-to-apply optimization opportunities are a few clicks away.
Create your Akamas account and connect Insights to Datadog in minutes — no changes to your setup.
FAQs
The Akamas Datadog integration reads Kubernetes metrics from Datadog and returns optimization recommendations as Datadog events. It covers pod sizing, cluster autoscaling, and JVM and Node.js runtime tuning, so teams act on recommendations inside Datadog.
Akamas collects infrastructure metrics for clusters, nodes, and workloads. It also collects application-runtime metrics, such as those for the JVM and Node.js. Akamas uses this data to analyze performance and reliability patterns.
Akamas sends the optimization opportunities it identifies back into Datadog as events. Akamas-identified reliability risks also appear directly within Datadog, so teams review them alongside their existing dashboards.
No. Akamas complements Datadog rather than replacing it. Datadog provides the observability data; Akamas turns that data into proactive optimization recommendations for Kubernetes.
Akamas is listed in the Datadog Marketplace. Create an Akamas account, connect Insights to your Datadog data, and ready-to-apply optimization opportunities follow within a few clicks.
