StormForge hopes to simplify Kubernetes' automation

StormForge hopes to simplify Kubernetes' automation ...

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Organizations adopt the technology for many reasons, including its portability, flexibility, multicloud capability, and proven ability to increase productivity.

As the popular open-source orchestration platform is increasingly available in the enterprise arena, Kubernetes is creating new and unexpected challenges. This is only compounded by an explosion of data.

Kubernetes is rapidly expanding due to the benefits it offers, including increased agility, faster innovation, and effortless scalability, says Dave Keil, the head of StormForge, which operates in cloud-native application performance testing and resource optimization. It's an incredibly flexible technology for running, but we often notice that with this flexibility comes increased complexity.

65% of respondents to a survey conducted by the Cloud Native Computing Foundation (CNCF) claim that their cloud and Kubernetes-related bills have increased. Of those, half showed costs rising by more than 20% over the past year.

Making Kubernetes easier

While Kubernetes automates the manual processes involved in managing containerized applications at its simplest level, the process and the platform itself are all but simple. For this reason, an increasing number of solutions are being offered to remediate its shortcomings.

With the release of its StormForge Optimize Live, companies like Xtivia, Densify, Cast AI, and StormForge are taking on the game in the growing market. For its part, StormForge, based in Cambridge, Mass., wants to enhance enterprise production environments.

According to Chris Aniszczyk, the CEO of CNCF, Costs are often mitigated by how well companies are able to accurately and effectively monitor Kubernetes costs, predict those costs, and instill processes that reduce unnecessary overspend. 'Intelligent and automated solutions like those we see from StormForge and others can help improve cloud native infrastructure and reduce unnecessary spending. Were encouraged by these technological advances.

StormForge embraces machine learning.

Optimize Live is a component of the StormForge platform, which, according to Provo, is now avoiding preproduction and production optimization while maintaining application performance.

Provo said the platform's ML is based on the purpose-built for Kubernetes and sets the foundation to optimize the whole Kubernetes stack, including application, pod, and container. It extracts performance insights from all data collected to inform and optimize cloud native environments.

According to Keil, ML is applied to data already collecting so they may "turn observability into actionability" with recommendations for configuration changes. The ability to modify multiple parameters for multiple, competing dimensions, "allows customers to better understand the inherent tradeoffs and to make intelligent business decisions."

Platform users have seen a cost savings of 40% to 60%, compared to 30% to 50%.

Weve been able to provide insight into the applications performance and ecosystem, like we haven't seen before, Provo said. Were constantly demonstrating you what's going wrong, or what went wrong.

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

"This is how we all realize the promise of Kubernetes and the cloud native," said Provo.

Future challenges

StormForge insists that, as more organizations expand their Kubernetes space for day 2 operations, the complexity of the process will only be limited.

Several key gaps will continue to challenge organizations in 2022, according to the government. First and foremost, organizations will continue to increase and increase workloads on Kubernetes; however, while the platform will offer new levels of flexibility, downstream limitations will often slow down deployments.

There will continue to be a gap in data-to-value, in which the amount of information collected by businesses will continue to increase exponentially, making it more and more difficult to collect insights and act on that information. Finally, a cloud native skills gap will accelerate and will soon hit a "crisis point" for many large organizations.

"All three of these factors will continue to increase demand for optimization solutions," said Keil.

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