Kubernetes Optimization

Optimize Kubernetes resources to improve application efficiency, reliability, and performance.

 

Get insights and recommendations to allocate the right amount of resources to balance efficiency with performance.

Get The Right Analysis In Place

It is hard to create the right dashboards and metrics to track resources

Magalix monitors CPU and memory allocation and utilization for each pod continuously. The Magalix Resources Advisor analyzes usage patterns and uses statistical methods to estimate the right amount of CPU/memory that your pods need.

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Comprehensive And Easy To Understand Recommendations

Don’t juggle between different dashboards to get it right

In one view, see recommended resources, collected metrics, proposed limits and requests, and reasoning for why you should update your pod and node settings.

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All Scenarios Considered

Don’t worry about the possible changes. Focus on what makes a difference

Magalix considers all the possible resources configurations and categorizes them into 6 main groups so that you can tackle them based what you're trying to optimize for, whether it's app performance and UX, cost, or both.

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Optimize Resources In a Snap

Select and apply optimization with one click

Apply resources optimization from Magalix console as many times as you want, in real-time. You will get real-time feedback on each applied change. Nervous about delegating to the Magalix agent? You can revert changes with just one-click.

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Ed Sarkar
Director of DevOps at Spire Digital
"I recently discovered Magalix while browsing the GCP marketplace. It promised an auto-pilot, cost-cutting monitoring agent for our k8s platform. Sounds too good to be true. It is true."
Ewlad De Vries
CTO, Medstreaming
We were very impressed with the technical competence and the white glove treatment we received so far.
Waleed Osman
Support Lead at Medstreaming
"Magalix made it easy for us to understand performance issues in our containers, cluster resources utilization, achieve significant savings"
 

Optimize your Kubernetes resources

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