Efficiency

These checks ensure that CPU and memory settings are configured, so that Kubernetes can schedule your workload effectively.

Presence Checks

To simplify ensure that these values have been set, the following attributes are available:

key	default	description
cpuRequestsMissing	warning	Fails when resources.requests.cpu attribute is not configured.
memoryRequestsMissing	warning	Fails when resources.requests.memory attribute is not configured.
cpuLimitsMissing	warning	Fails when resources.limits.cpu attribute is not configured.
memoryLimitsMissing	warning	Fails when resources.limits.memory attribute is not configured.

Background

Configuring resource requests and limits for containers running in Kubernetes is an important best practice to follow. Setting appropriate resource requests will ensure that all your applications have sufficient compute resources. Setting appropriate resource limits will ensure that your applications do not consume too many resources.

Having these values appropriately configured ensures that:

• Cluster autoscaling can function as intended. New nodes are scheduled once pods are unable to be scheduled on an existing node due to insufficient resources. This will not happen if resource requests are not configured.

• Each container has sufficient access to compute resources. Without resource requests, a pod may be scheduled on a node that is already overutilized. Without resource limits, a single poorly behaving pod could utilize the majority of resources on a node, significantly impacting the performance of other pods on the same node.

Further Reading

• Kubernetes Docs: Managing Compute Resources for Containers (opens new window)
• Kubernetes best practices: Resource requests and limits (opens new window)
• Vertical Pod Autoscaler (can automatically set resource requests and limits) (opens new window)