Successful resource optimization on Kubernetes can lead to so many good things starting with cloud cost-cutting, application performance enhancement and operational optimization. But with a lot of Kubernetes’ true potentials unrealized, companies often find themselves facing outrageous cloud bills but not much result to show for it. StormForge seeks to change that situation and for that it has a solution all ready to go. It’s the Kubernetes Optimization Platform they showcased at February’s Cloud Field Day event.
Kubernetes Is Not Easy
Kubernetes has a lot of complexity involving areas of security, cost, networking, especially resource management. First, there is a brain numbing variety of resource settings that need configuring at deployment. Add to that the plurality of containers. The number of combinations that can lead to are practically endless. It is impractical, let alone possible to humanly approach it.
So businesses end up taking the seemingly safer backroads that take them through lukewarm and often counterproductive strategies like over-provisioning, cutting back on resources and maximizing application efficiency through tuning. Sadly, none of these work very well, let alone help with the inflating cost situation.
StormForge at Enhancing Kubernetes Efficiency
Kubernetes is full of potentials and if that’s unrealized, it doesn’t make sense for businesses to use it. Thankfully, there is a way to utilize Kubernetes to its full potential – through continued innovation and optimization. StormForge has a solution, in fact two that enable systematic innovation and optimization on Kubernetes.
Founded in 2016, StormForge saw a way to get to the bottom of this problem that users are having with Kubernetes through Machine Learning. So, it designed a platform with technologies that are exclusively built to simplify management and optimize resources in Kubernetes and perform the complex and variable tasks in relatively no time.
The StormForge Platform: What It Does?
At the Cloud Field Day event in February, Rich Bentley, VP of Product Marketing at StormForge offered an overview of the StormForge Platform while detailing the capabilities and functions of its two constituent solutions- StormForge Optimize Pro and StormForge Optimize Live.
The StormForge Platform is powered by twin solutions StormForge Optimize Pro and the relatively newer Optimize Live. Working in non-prod environment, the StormForge Optimize Pro is a rapid experimentation-based solution that is designed to run countless trials and scenarios in an experiment and come up with the best recommendations for configuring the application. Using Machine Learning it analyzes input data to make recommendations by comparing outputs with goals.
The Optimize Live which is a relatively simpler technology uses observability metrics that are constantly generated in the environment to produce actionable analytics. Using ML, it makes recommendations for real-time changes like CPU updates, memory settings and more. These recommendations can take effect on their own when set to auto pilot or can be made to go through an approval process for the right results.
Together the solutions translate observability data into actionable intelligence and simultaneously improve resource efficiency at prod and non-prod levels. Leveraging machine learning, StormForge achieves this through organized implementation of experimentation and observation-based optimization.
What stood out most to me about the StormForge Platform is that it takes a holistic approach to operational optimization on Kubernetes. By bringing with it the power of Machine Learning, it causes a well-rounded development of cloud native environment. In the process it saves enterprises from painfully big cloud bills and resource wastage, while accelerating application performance.