StormForge announced StormForge Optimize Live, a new solution for automatically and intelligently improving the efficiency of production environments.
Optimize Live analyzes existing observability data using machine learning to recommend real-time configuration changes that reduce resource usage and cost while ensuring application performance. The new solution is part of the StormForge platform, which now closes the loop between pre-production and production optimization to proactively and continuously ensure peak efficiency for organizations using Kubernetes.
“StormForge Optimize Live builds out the StormForge platform to deliver the first intelligent optimization for cloud native pre-production and production cloud native environments,” said Matt Provo, CEO and founder, StormForge. “StormForge informs, optimizes and operates throughout the entire cloud-native development cycle for both developers and operations managers who require an intelligent and comprehensive platform that maximizes their returns on Kubernetes investments. This is how we all realize the promise of Kubernetes and cloud native.”
StormForge Optimize Live supports modern architecture and operations requirements by going a level deeper to draw performance insights on all the data collected, informing and optimizing cloud native environments.
StormForge Optimize Live is ML-powered multi-dimensional optimization. The ML goes beyond cost or performance to enable intelligent business trade-offs. It is purpose-built for Kubernetes and lays the foundation to optimize the entire Kubernetes stack, including application, pod and container. It runs in any CNCF-certified distribution. It includes automated optimization, enabling fast time-to-value with one-click deployment for production optimization and automated Rapid Experimentation for pre-production. And it leverages existing data to deliver insights and optimization from observability and cost data already being collected.
Additional StormForge Optimize Live features and benefits include:
- Leverages Machine Learning (ML) for continuous optimization of production environments
- Analyzes observability data to recommend resource settings (CPU, memory, replicas) for improved efficiency with initial Prometheus and Datadog integrations
- Provides improved recommendations versus those provided by VPA due to ML of customers’ specific environment
- Offers configurable policies for flexibility (for example, auto or manual approval of recommendations by namespace)
- Leverages the foundation of the StormForge platform with common user management, SSO, RBAC, release automation and more.
StormForge platform updates for enterprise-readiness also announced: RBAC system; 24/7 production support; and air-gapped deployment, including UI, SSO/SAML and release mechanics. Pre-production optimization and load testing improvements include: one-click, UI-based application scanning for easier experiment creation; improved visualization of experiments with trial logs and UI-based parameter editing; and Hail (perf testing engine) in-cluster for improved security & flexibility use for internal applications.
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