StormForge announced a broad expansion of the Optimize Live product, including support for Java Virtual Machine (JVM) Workload Optimization and automated out-of-memory (OOM) Response, expanding market reach and bolstering application performance, reliability, and efficiency. These enhancements further establish Optimize Live as the most robust and flexible Kubernetes workload rightsizing solution, enabling organizations to dramatically cut cloud costs while improving reliability and unburdening engineers from manual toil. 

Java is the most popular programming language for Kubernetes application workloads, with 65% of all application workloads run in a JVM, yet automated rightsizing tools have lacked support for JVM's unique requirements. This gap has led to suboptimal performance and resource utilization while leaving platform engineers, Kubernetes administrators, and developers of JVM workloads challenged by the significant manual toil required to optimize these workloads efficiently. 

Optimize Live's JVM Workload Optimization reduces common out-of-memory errors by using machine learning to generate tailored recommendations for heap and off-heap sizes, as well as Kubernetes resource requests and limits. Users can review and apply these recommendations through a user-friendly interface or deploy them automatically, benefiting from continuous performance monitoring and adjustments as applications evolve. 

"For anyone trying to rightsize JVM applications on Kubernetes, it can feel like trying to solve a Rubik's cube with a blindfold on," said Nick Walker, Director of Product, StormForge. "That's why we're so excited to offer JVM Workload Optimization and give users rightsizing recommendations that handle the JVM's unique resource needs. Now they can continuously rightsize their JVM applications, improving reliability - rather than putting applications at risk of performance issues." 

JVM Workload Optimization is currently in limited availability. Platform engineering teams interested in participating can sign up atm stormforge.io/jvm-workload-optimization-limited-availability-signup/.  

Another major challenge that teams managing Kubernetes often face is workloads that crash due to OOM events. These common incidents can lead to service disruptions that inflict reputational harm to the business. 

The Optimize Live OOM Response feature helps Kubernetes users avoid application downtime by automatically detecting OOM events and increasing memory resources, ensuring stable workload operations without manual intervention. StormForge's machine learning continues analyzing the increased memory consumption to refine the recommendations over time for optimal resource allocation. Detailed reports track OOM events declining over time to measure impact as they're automated away.

"With this release, our rightsizing recommendations now provide proactive optimization for all common workload types paired with reactive protection from OOM Response, ensuring that every platform team is empowered to drive automated optimization in their environment while improving the reliability of their platform," Walker said.

Rounding out this feature release is the addition of a Mutating Admission Webhook, which further simplifies the integration of CPU and memory recommendations with popular GitOps deployment tools, including Argo CD and Flux.