Java Heap Optimization

The Only Rightsizing Solution That Actually Understands Java

Stop guessing at container resources. Get ML-powered rightsizing that understands JVM heap behavior, eliminates OOMKills, and cuts Kubernetes costs.

With over 60% of all Kubernetes workloads running on the JVM, Java dominates enterprise container environments—yet configuring memory correctly requires getting two interrelated settings right container limits and heap size. When you’re managing hundreds of Java microservices, each with unique memory characteristics manual tuning becomes impossible. Get it wrong and containers OOM. Most teams just overprovision by 2-3x rather than risk getting paged at 3am. This is why we built a solution that understands both container limits AND JVM internals.
 

Why It Matters

JVM-Aware Intelligence That Prevents Crashes

Finally, rightsizing that sees inside the JVM. We analyze heap usage, garbage collection patterns, and non-heap memory to prevent OOMKills before they happen—even as your application evolves.

Continuous Protection as Code Changes 

Your app’s memory profile changes with every feature release. Our ML continuously adapts recommendations, catching memory spikes from new deployments before they cause 3am pages.

Higher Cost Reduction, Lower Performance Risk 

Traditional tools only see container metrics and guess at safety margins. We see everything—heap, non-heap, GC overhead—so we can cut deeper while actually improving reliability.

Zero-Touch Automation for Platform Teams Stop fielding tickets for Java tuning. Deploy once, and let intelligent automation handle heap sizing, container limits, and HPA settings across hundreds of services.

Primary Features:

• JVM Metrics Collection: Direct visibility into heap usage, non-heap memory, and garbage collection behavior
• Dual-Layer Optimization: Coordinated recommendations for both Java heap settings and Kubernetes resource limits
• ML-Powered Recommendations: Machine learning trained on Java workload patterns
• OOM Response System: Automatic memory increases when OOM events are detected, with continuous learning
• GitOps Integration: Mutating admission webhooks for seamless integration with ArgoCD and Flux
• Universal Java Support: Works with any JVM language—Java, Kotlin, Scala, Groovy

Next Steps 

See Your Java Workloads Optimized → Take a free trial and see the savings for yourself

Supporting Resources:

• How to Use StormForge Optimize Live’s Java Workload Optimization
• How Java Workload Optimization and OOM Response Empowers Platform Teams