Java remains one of the most common platforms for distributed systems, but managing it efficiently on Kubernetes is a challenge. The Java Virtual Machine (JVM) controls heap and garbage collection, while Kubernetes only sees container-level metrics. This disconnect means that container memory metrics often miss what’s actually happening in the JVM.
While most workloads can rely on container-level signals for effective resource automation, Java applications are an exception – Java’s unique memory management makes traditional container-based approaches less accurate and efficient.
Teams end up tuning heap sizes, chasing OOMErrors, or overprovisioning memory to stay safe. The result is wasted resources and unpredictable performance.
Introducing The Next Generation of Java Optimization
Today, we’re solving that problem with Java Optimization, the latest addition to the ScaleOps Platform. This new capability expands our automated resource management with JVM-level intelligence, bringing full control to Java application’s resource needs.
How it Works
ScaleOps analyzes Java memory behavior, including heap activity, garbage collection, and OOM patterns, and dynamically manages both Java heap and workload memory requests in real time.
Java Optimization builds on ScaleOps’ core strengths, delivering new depth and precision to workload optimization – eliminating guesswork, preventing runtime instability, and maximizing memory utilization across every Java workload.
Reduce memory waste: Automatically manage Java heap allocation to align with actual application usage, minimizing overprovisioning and cutting resource costs.
Reclaim engineering time: Replace manual Java resource tuning with continuous, automated optimization, freeing up engineers from operational overhead
Troubleshoot faster: Gain real-time visibility into heap, garbage collection and OOMErrors to quickly identify inefficiencies and simplify troubleshooting
Why it matters
Java Optimization brings Kubernetes and Java resource management into one continuous system, something no other solution provides.
By connecting heap behavior with real-time resource automation, ScaleOps eliminates a long-standing blind spot in running Java on Kubernetes. The result is reduced cost, fewer performance issues, and a more predictable, cost-efficient environment for Java applications in production.
Java Optimization extends the ScaleOps approach to intelligent resource management deeper into the application layer. It’s another step toward a fully self-managing environment. Java Optimization is live now, just in time for KubeCon North America. Want to see Java Optimization and the ScaleOps platform in action?
Get started with a free trial or book a demo today.