Source: thenewstack.io
ML Can Prevent Getting Burned for Kubernetes Provisioning
DETROIT — In the rush to create, provision and manage https://thenewstack.io/docker-versus-kubernetes-start-here/ proper resource provisioning often gets left out. According to https://www.stormforge.io/?utm_content=inline-mention a company paying, for example, $1 million a month on cloud computing resources is likely wasting $6 million a year of resources on the cloud for unused Kubernetes clusters.
They include how https://thenewstack.io/platform-engineering-is-devops-evolved-new-report-shows/ teams can tend to estimate too conservatively or aggressively or overspend on resource provisioning.
The processes typically involve Kubernetes resource requests and limits, and predicting how the resources might impact quality of service for pods. Developers deploying an application on Kubernetes often need to set a CPU request, memory request and other resource limits.
They include how https://thenewstack.io/platform-engineering-is-devops-evolved-new-report-shows/ teams can tend to estimate too conservatively or aggressively or overspend on resource provisioning.
The processes typically involve Kubernetes resource requests and limits, and predicting how the resources might impact quality of service for pods. Developers deploying an application on Kubernetes often need to set a CPU request, memory request and other resource limits.
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