We’re excited to announce that Akamas is now available as an integration in Datadog. This integration brings Akamas’ autonomous optimization capabilities into the Datadog ecosystem – helping developers, DevOps teams, and SREs unlock greater performance, reliability, and efficiency in Kubernetes environments.
Actionable Optimization Insights in Datadog
Akamas enables teams to optimize applications by generating full-stack recommendations – from pod sizing and cluster autoscaling to tuning 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 entire stack is optimized, the less reliability risks you will face.
Datadog and Akamas – a Perfect Synergy
Akamas perfectly complements Datadog’s offering by turning observability data into proactive recommendations.
Get started with Akamas Insights – thanks to this integration ready-to-apply optimization opportunities are a few clicks away.
Akamas collects Kubernetes-related metrics from Datadog, covering both infrastructure (clusters, nodes, workloads) and application runtimes (e.g., JVM and Node.js). It uses this data to analyze performance and reliability patterns, then sends identified optimization opportunities 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
A New Level of Observability-Driven Optimization
Modern cloud-native environments are dynamic and complex. This integration bridges observability and optimization, giving teams visibility into where they can do more with less, right from their monitoring platform.
Get Insights
Ready to explore how Akamas can help you drive efficiency and performance improvements across your Kubernetes environments?
Get early access to Akamas Insights and learn how to integrate with Datadog.