StormForge announced significant advancements in its solution, including node optimization and reporting, general availability of Java heap size recommendations, and pay-as-you-go pricing on AWS Marketplace. These innovations empower organizations to achieve unprecedented efficiency and cost savings in their Kubernetes environments.

Node Optimization and Reporting: Deeper Cluster Insights Unlocked

Kubernetes provides flexibility in managing workloads across a range of cloud environments. However, efficiently and cost-effectively optimizing Kubernetes clusters remains challenging, especially when it comes to selecting the right nodes to run workloads.

StormForge's new Node Optimization feature leverages machine learning to ensure that workloads are placed on the most suitable node types-such as compute-optimized or memory-optimized nodes-leading to improved cluster performance and resource efficiency.

"Cluster autoscalers are inherently greedy algorithms. They are looking at the set of unscheduled pods right in front of them and making decisions without any foresight," said Nick Walker, Director of Product at StormForge. "With our ML-powered solution, we can provide future-facing predictions that guide the autoscaler to make smarter decisions, ensuring optimal utilization of resources across the entire cluster."

The new Node Optimization and Reporting capabilities provide users with greater clarity on cluster utilization, helping them track the impact of pod right-sizing and identify inefficiencies in node usage. By optimizing node selection and bin-packing, organizations can achieve more efficient utilization of cluster resources.

Java Heap Size Recommendations: Precision Optimization for the JVM

At KubeCon NA 2024, StormForge previewed its Java Heap Size Recommendation feature, and today, the company is proud to announce its general availability. This feature automatically analyzes critical Java metrics-such as heap and non-heap usage, as well as garbage collection data-and provides tailored recommendations for heap size adjustments alongside requests and limits.

StormForge's solution automates heap size optimization, eliminating the need for engineers to manually sift through dashboards and tweak configurations, which is notoriously error-prone and time-consuming. This precision optimization improves application performance, stability, and resource efficiency.

"Having SREs and platform engineers manually tweak Java heap sizes is like having your accountant take your laundry to the dry cleaner," said Walker. "It's a waste of time and resources. With StormForge, we automate that process so your team can focus on higher-value tasks."

Amazon Marketplace Pay-as-You-Go Pricing: Effortlessly Start with Optimize Live

StormForge is also introducing a Pay-as-You-Go pricing model via AWS Marketplace, making it easier than ever for organizations to start optimizing their Kubernetes environments. With this flexible pricing option, customers can scale their usage without the need for long-term contracts or sales engagements, ensuring that they only pay for the resources they consume.

This model offers seamless integration with AWS accounts, enabling users to leverage Enterprise Discount Plans (EDP) and Private Pricing Agreements (PPA) to easily manage cloud costs while enhancing the efficiency and reliability of their Kubernetes workloads.

To get started, customers can visit the StormForge listing on AWS Marketplace and begin using the Pay-as-You-Go pricing option to optimize their Kubernetes resources.