StormForge Wants to Simplify Kubernetes Automation

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Organizations use Kubernetes for many reasons, including its portability, flexibility, multicloud capability, and proven ability to increase productivity.

But as the popular open-source orchestration platform is increasingly deployed in the corporate world, Kubernetes is creating new and unexpected complexities. And this is only made worse by the explosion of data.

“Kubernetes is growing rapidly for the business benefits it offers – greater agility, faster innovation and effortless scalability,” said Dave Keil, board member of StormForge, which specializes in cloud-native application performance testing and resource optimization. . “It’s an incredibly flexible technology for running cloud-native applications, but we often see that with this flexibility comes greater complexity.”

This, in turn, results in rising costs: 68% of respondents to a recent survey conducted by the Cloud Native Computing Foundation (CNCF) said their cloud and Kubernetes-related bills have risen. Half of these saw costs rise by more than 20% in the past year.

Making Kubernetes easier

While Kubernetes, in its simplest definition, automates manual processes involved in managing containerized applications, the process — and the platform itself — are anything but simple. For this reason, more and more tools are being offered to unravel its complexity.

Companies such as Xtivia, Densify, Cast AI and StormForge are making their claim in the growing segment. In turn, in Cambridge, Mass. established StormForge help improve the efficiency of enterprise production environments with the launch of StormForge Optimize Live.

Chris Aniszczyk, CTO at CNCF, underlined the importance of such platforms: “Costs are often constrained by how well companies are able to accurately and effectively monitor Kubernetes costs, predict those costs, and implement processes that can eliminate unnecessary overspending. limit,” he said. “Intelligent and automated solutions like the ones we see coming from StormForge and others can help optimize cloud-native infrastructure and reduce unnecessary spend. We are encouraged by these technological advancements.”

StormForge embraces machine learning

The patent-pending machine learning (ML) model analyzes existing observation data from the StormForge platform to recommend real-time configuration changes. This reduces resource usage and costs while preserving application performance, said CEO and founder Matt Provo. Optimize Live is part of the existing StormForge platform, which, according to Provo, now closes the loop between pre-production and production optimization to help organizations maximize their Kubernetes ROI.

The platform’s ML is built specifically for Kubernetes and lays the groundwork for optimizing the entire Kubernetes stack, Provo said, including application, pod, and container. It extracts performance insights from all collected data to inform and optimize cloud-native environments.

ML is being applied to data companies already collect so they can “turn observability into usability” with recommendations for configuration changes, Keil said. The ability to optimize multiple parameters for multiple, competing dimensions “allows customers to better understand the inherent tradeoffs and make intelligent business decisions,” he said.

The company claims that platform users have seen 40% to 60% cost savings and 30% to 50% performance improvements.

“We’ve been able to provide insights into the application’s performance and ecosystem like we’ve never seen before,” said Provo. “We’ll show you what’s going wrong, or what’s gone wrong.”

Optimize Live runs in any CNCF certified distribution, includes automated optimization with one-click implementation for production optimization and rapid experimentation, and leverages existing observation and cost data to deliver insights and optimization.

“This is how we are all realizing the promise of Kubernetes and cloud natively,” says Provo.

Future Challenges

Keil pointed out that as more organizations scale their Kubernetes environment for day 2 operations, StormForge only expects accelerated complexity.

Several key gaps will continue to challenge organizations in 2022, he said. First and foremost, organizations will continue to move more and more workloads to production on Kubernetes; however, while the platform will provide new levels of flexibility, downstream complexity will often slow implementations.

A data-to-value gap will also continue to exist, with the amount of data collected by enterprises continuing to grow exponentially, making it increasingly difficult to gain insights and act on that information, Keil said. . Finally, a cloud-native skills gap will accelerate and will soon reach a “crisis point” for many large organizations.

“All of these three factors will continue to accelerate the demand for optimization solutions,” Keil said.

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