Java remains one of the most common languages for distributed systems, but managing it efficiently on Kubernetes is a huge 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 miss what’s actually happening inside the JVM. As a result, VPA and other workload rightsizing tools make incorrect or unusable recommendations because they lack true JVM-level visibility.
This issue is a major pain point for Kubernetes users and makes Java resource management far more complex and risky than it should be: teams end up tuning heap sizes, chasing OOMErrors, or overprovisioning memory to stay safe. The result is wasted resources and continuous performance issues.
Introducing The Next Generation of Java Resource Management
Today, we’re solving that problem with Automated Java Resource Management, 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 with automated JVM parameter management.
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.
It’s built on ScaleOps’ core strengths, delivering new depth and precision to workload optimization – eliminating guesswork, preventing 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
Free 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
ScaleOps 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 closes a long-standing gap in running Java on Kubernetes and finally allows teams to automate Java workloads with confidence. The outcome is reduced cost, fewer performance issues, and a far more stable production environment.
Automated Java Resource Management extends the ScaleOps approach to intelligent resource management deeper into the application layer. It’s another step toward a fully self-managing environment.
Want to see Automated Java Resource Management and the ScaleOps platform in action?
Get started with a free trial or book a demo today.