CloudBolt Software acquires StormForge to improve Kubernetes optimization
- CloudBolt Software has acquired StormForge to integrate machine learning capabilities for Kubernetes resource optimization.
- The acquisition aims to tackle overspending and misconfiguration issues commonly associated with Kubernetes.
- By combining resources, CloudBolt seeks to empower IT teams with tools to optimize container spending effectively.
In a significant move for cloud optimization, CloudBolt Software acquired StormForge, a company specializing in machine learning-powered resource optimization for Kubernetes. This acquisition is aimed at addressing the challenges posed by cloud computing containers, which can be fragile and prone to misconfiguration. The integration of StormForge's capabilities is expected to enhance CloudBolt's FinOps platform by reducing the "insight-to-action" time within container environments, helping to streamline resource management effectively. Kubernetes, developed by Google, has become an essential tool for many enterprises, automating the deployment and management of containerized applications. However, according to a Cloud Native Computing Foundation survey, 49% of organizations have experienced increased spending on cloud services due to Kubernetes, with 70% attributing overspend to workload overprovisioning. This issue typically arises from overly cautious planning regarding resource allocation or aggressive auto-scaling configurations that result in excessive resources being requested during peak demand periods. The acquisition of StormForge is part of CloudBolt's strategy to optimize these container environments by providing IT teams with advanced tools to manage and reduce costs associated with Kubernetes implementations. CloudBolt aims to combine its cloud cost visibility with StormForge’s optimization capabilities, creating a closed-loop solution that enhances operational efficiency. Industries like FinTech and hosting platforms, where Kubernetes has been crucial, stand to benefit significantly from this integration. CloudBolt’s leadership has articulated a vision for third-generation FinOps, which emphasizes the application of artificial intelligence and machine learning to manage cloud estate costs and performance proactively. The overarching goal of this enhanced FinOps approach is to provide complete lifecycle management of cloud costs while ensuring performance aligns with organizational needs.