Weatherproofing Kubernetes, CloudBolt Acquires StormForge
Weather symbols were drawn by myself, not from type font
Cloud computing containers are fragile. Unlike their rubberized kitchenware namesakes that can withstand dishwasher heat and being dropped from a height, cloud containers need careful provisioning, preparation and preening to keep them functional.
Because containerization allows software application development engineers to create single units of computing power that can be deployed independently, there is typically a price to pay for that flexibility and freedom. Containers can suffer from misconfiguration, they can offer attackers the opportunity to inject malicious code into their runtime, they may be woven together through flaky poorly tested application programming interfaces, or the container access authorization controls meant to oversee their existence may not be up to scratch.
The Kubernetes container orchestration project (created by Google and subsequently open sourced) continues to work to address many of those issues; this platform automates the deployment, scaling and management of containerized applications. It's no overstatement to say that Kubernetes has been lovingly adopted by the enterprise technology community.
All of which hopefully makes it clear why Kubernetes is key to modern cloud-native deployments, especially those that seek to deliver performance and cost effectiveness. Cloud cost management specialist CloudBolt Software has used this precise logic to now announce its acquisition of StormForge, a machine learning-powered Kubernetes resource optimization specialist.
Although CloudBolt styles itself with its trademarked Cloud ROI Company™ label, this is essentially FinOps i.e. not systems administration operations for financial services companies as such, but financially aligned operations expertise designed to enable cloud-native teams to operate effectively and with the highest return on investment for their resource spend. The company says that the integration of StormForge's ML-driven optimization capabilities into CloudBolt's FinOps platform will reduce what it calls 'insight-to-action' time in container environments.
"StormForge's innovative approach to Kubernetes optimization complements our vision perfectly," said Craig Hinkley, CEO of CloudBolt. 'This acquisition is like two pieces of a puzzle snapping into place, seamlessly integrating their technology into our third-generation FinOps platform. The market has been calling for a more unified, streamlined and intelligent way to manage costs and optimize Kubernetes operations. Together, we're delivering exactly that.'
CloudBolt first partnered with StormForge in early 2024, when the company became the inaugural member of CloudBolt's Technical Alliance Program. Aiming to further underline and validate this acquisition, Hinkley reminds us that as Kubernetes adoption skyrockets, so do the challenges. A recent Cloud Native Computing Foundation survey suggested that Kubernetes has driven up cloud spending for 49% of organizations, with 70% citing overspend as a result of workload overprovisioning.
Discussion surrounding overprovisioning is never far from any Kubernetes crowd. It typically happens due to over-cautious planning for additional computing power based upon a lack of historical data to detail how a cloud application might need to perform. Overprovisioning also occurs due to aggressively configured auto-scaling policies that automate the request for more container resources when the system detects a surge in demand which may not warrant additional resources long term.
CloudBolt says that inefficiencies in this space stem from two key challenges: the inherently dynamic nature of container workloads (which can make proper resource allocation and rightsizing extremely difficult) and the complexity of Kubernetes environments, which obscures granular cost visibility. The company says its acquisition of StormForge tackles these challenges and 'closes the FinOps for Kubernetes loop' so that IT teams can optimize and operate containers with efficiency.
"By combining our intelligent Kubernetes optimization platform with CloudBolt's cloud cost visibility, customers will now receive a closed loop solution, from reporting, through proven and powerful optimization capabilities," said Rod Squires, CEO of StormForge. 'Our shared goal is clear, to empower FinOps leaders with the tools that platform engineers trust and break open the longstanding 'black box' of container spending. Together, we're making Kubernetes optimization smarter, more transparent, and more actionable than ever before with a tool developed by engineers, for engineers.'
Squires and team say that unlike manual approaches that require specialized knowledge and constant attention, StormForge automatically adjusts resource requests and limits, along with the target utilization of the container 'pod' (a small component of a container) autoscaling, to match real-time demand, minimizing the risk of performance issues while consistently reducing cost waste across all Kubernetes deployments.
He suggests that the platform has been particularly transformative for industries like FinTech and hosting platforms, where Kubernetes has become crucial to modernization efforts.
As the practice of FinOps becomes more widely established (and if CloudBolt has anything to do with it more comprehensievly codified, standardized, operationalized and productized), we may see this space become increasingly sophisticated in its toolset offerings and increasingly granular in terms of engineering precision. CloudBolt CEO Hinkley talked about third-generation FinOps and he has detailed his company's approach to what it calls augmented FinOps.
In this augmented and extended world of FinOps, Kyle Campos, CloudBolt's chief technology and product officer says that cloud engineering teams will now be able to use AI and ML insights and apply intelligent automation and orchestration to their cloud estates both retrospectively and proactively. The mission here gravitates around a notion of complete cloud lifecycle cost and performance optimization, which is not a term that we usually talk about… yet.
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