StormForge

StormForge is a platform designed to optimize Kubernetes applications by providing autonomous workload rightsizing. According to the vendor, this tool is aimed at small to large enterprises and caters to a wide range of professionals and industries, including DevOps Engineers, Site Reliability Engineers, Cloud Architects, IT Operations Managers, Financial Services, E-commerce, Healthcare, Technology, and Retail. StormForge aims to maximize resource efficiency, ensure application performance, and help organizations control cloud costs by automatically right-sizing over-provisioned containers.

Key Features

Maximize Density: According to the vendor, StormForge automatically rightsizes over-provisioned containers using vertical autoscaling, potentially increasing density by 50-70%. This feature aims to free up cluster capacity, eliminate wasted CPU and memory, and reduce the risk of CPU throttling and out-of-memory errors.

Ensure Application Performance: The vendor states that StormForge prevents CPU throttling and out-of-memory errors by automatically upscaling undersized workloads and utilizing horizontal pod autoscaling (HPA) replication. It continuously analyzes resource utilization to understand each workload's demand patterns, aiming to ensure optimal performance.

Free Your Devs: StormForge aims to save application teams from the cognitive load and toil of infrastructure sizing. According to the vendor, it continuously discovers and rightsizes workloads based on real-world utilization data, relieving developers from the manual effort of tuning and optimizing infrastructure settings.

Forget It's There: The vendor claims that StormForge puts estate-wide rightsizing on autopilot with hands-free lifecycle automation. It automatically discovers new pods, captures their metrics, learns their patterns, calculates optimum settings, and applies them. No human configuration or tuning is required.

Optimize Live: StormForge combines horizontal pod autoscaling (HPA) with vertical pod autoscaling (VPA) to provide bi-directional autoscaling, according to the vendor. It continuously optimizes resource utilization based on machine learning analysis, offering recommendations for configuration changes to minimize resource waste and improve performance.

Rightsize Accurately: Through machine learning analysis of resource utilization every 15 seconds, StormForge aims to accurately and efficiently size workloads while maintaining or improving application performance, availability, and resilience. Users can preview the impact of recommended settings and compare them against current settings.

Simplify at Scale: According to the vendor, StormForge simplifies workload discovery, analysis, and recommendations, making it accurate enough to approve and apply after just 1-2 weeks. It requires no human configuration or tuning and can begin optimizing clusters in minutes.

Approve: Users can tailor optimization for high-profile or outlier workloads, specifying optimization goals for extra performance or efficiency, resizing frequency, min/max requests, and including/excluding resource settings such as limits. StormForge allows users to apply recommended settings directly to pods or export them for integration with CI/CD tools.

Unify Visibility and Control: StormForge provides a centralized view to manage and optimize resources across the Kubernetes environment, according to the vendor. Users can see all pods in one place, track resource savings and opportunities across clusters, namespaces, nodes, and object types, and select automations to monitor their impact on resource utilization.