The most comprehensive K8s and application optimization solution
Unites developers, SREs, and platform engineers around one goal: delivering reliable, efficient services.
Benefits
Maximize Cost Efficiency and Reliability in Kubernetes
Full-Stack Optimization
Optimize from infrastructure to app runtimes – including JVM and Node.js – for deeper savings and better performance.
Instant Cost Savings
Cut cloud costs fast by fixing overprovisioned resources and scaling inefficiencies – no manual tuning required.
Proactive Reliability
Prevent incidents by detecting risky configs like missing limits or memory misalignments before they cause issues.
Compliance By Design
Identify deviations from Kubernetes and application best practices – like improper HPA settings or missing JVM configs – and ensure consistent, reliable deployments.
Get started in minutes
Easy setup via observability integrations
Connect Akamas Insights to your existing observability stack – no agents, no code changes.
In minutes, you can start analyzing metrics from Prometheus, Dynatrace, or Datadog to uncover inefficiencies and reliability risks across your Kubernetes environments.
Intelligent Prioritization
Detect optimization opportunities and estimate impact
Akamas automatically analyzes telemetry to identify where resources are wasted or risks arise – from workloads to nodes.
Each finding includes an estimated impact, helping teams prioritize what matters most to performance, reliability, and cost.
effortless cross-stack alignment
Kubernetes alone is not enough.
True efficiency starts at the runtime
Modern applications don’t run directly on Kubernetes, they run on language runtimes like the JVM or Node.js V8 engine, each with hundreds of configuration options that profoundly affect resource usage, reliability, and cost.
Teams that focus only on pods are optimizing the container, not the application. Akamas goes further, analyzing configuration across every layer – from Kubernetes Pods and HPA policies to JVM heap settings and V8 garbage collection – to surface the interactions that infrastructure metrics alone will never reveal.
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JVM on Kubernetes Optimization
Stop over-provisioning Java.
Let Akamas tune the JVM for you
Java powers over half of cloud costs in most enterprises, yet the JVM runs on default settings never designed for containerized environments. Heap misconfiguration, aggressive GC, and slow JIT warm-up cause OOM kills and CPU throttling that right-sizing pods alone can never fix.
Akamas continuously analyzes JVM heap, garbage collection, and Kubernetes pod resources together, recommending the exact settings that eliminate waste without compromising reliability. Teams running Akamas report up to a 58% reduction in cloud costs, 40% less memory, and 68% lower CPU usage – in production, without a single line of code change.
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Node.js Runtime Optimization
Bring intelligent optimization to your Node.js workloads
V8’s default heuristics are rarely tuned for containerized environments, leaving many Node.js services trapped in excessive GC cycles or at risk of OOM kills.
Akamas Insights now analyzes V8 heap settings alongside Kubernetes pod limits to surface the optimal runtime configuration – no code changes required. In benchmark tests, teams achieved up to a 45% performance increase and a 68% reduction in CPU usage.
HPA-Aware Optimization
Scale from a right-sized baseline, not a bloated one
Autoscaling from an over-provisioned pod simply replicates waste at scale.
Akamas now brings native support for HPA and KEDA workloads, optimizing the resource baseline your autoscaler scales from – without touching your carefully crafted scaling thresholds. The result: up to a 35% reduction in compute waste and rock-solid scaling stability with no CPU throttling.
Policy-Driven Governance
Customize tuning profiles and policies
Not every workload deserves the same optimization strategy.
Tuning Profiles let you apply aggressive cost-saving targets to dev namespaces while enforcing conservative safety buffers on tier-one services simultaneously, from the same interface. Create custom profiles from proven baselines, compare trade-offs side-by-side, and bulk-apply settings across hundreds of workloads. Teams see up to a 45% cost reduction in non-critical environments and a 60% drop in OOM errors for production services.
GitOps integration
Deliver optimization recommendations through your Git workflow
Autonomous agents that bypass your delivery pipeline create shadow configurations developers can’t trace or roll back.
Akamas Insights integrates directly with your GitOps source of truth – automatically opening Pull Requests with evidence-based configuration changes, including projected cost savings and latency improvements, for developer review. Every change is versioned, auditable, and compatible with Argo CD or Flux. Teams reduce time spent on resource configuration by up to 80% while maintaining 100% configuration traceability.
Cluster NODE POOL optimization
Right-size Kubernetes node groups
Akamas analyzes how workloads use cluster resources, evaluates instance families, sizes, and real utilization to uncover over-provisioning and misaligned capacity ratios.
It provides data-driven instance types recommendations for your node pools, enabling you to make the most from your Cluster Autoscaler and Karpenter setups to safely reduce cost while maintaining reliability with no effort.
EMpower
Who Can Benefit
from Akamas?
Akamas is designed for professionals who prioritize performance and efficiency.
Platform Engineers
- Gain full visibility into cluster efficiency and autoscaling behavior.
- Detect and fix misconfigured workloads that affect cluster reliability.
- Improve platform adoption by helping devs deliver more efficient, reliable workloads — no extra effort needed.
Developers
- Get app-aware recommendations — no need to tweak JVMs or K8s settings.
- Avoid OOMs, CPU throttling, and other performance incidents with zero manual tuning.
- Contribute to cost-saving goals without compromising app reliability.
SREs & DevOps
- Prevent incidents by spotting misconfigurations before they cause problems.
- Eliminate manual tuning with automation across workloads and runtimes.
- Address root causes — not just symptoms — by optimizing both K8s and app layers.
Performance Engineers
- Detect runtime inefficiencies like suboptimal JVM settings
- Leverage production insights to refine test scenarios.
- Enable app teams to adopt best practices for both performance and reliability.
See for Yourself
Experience the benefits of Akamas autonomous optimization.
No overselling, no strings attached, no commitments.