Resource Limits

Protect your apps with resource limits.

Indicating Limits

By default, Pods have no resource limits, which means they can use as much CPU and memory as the node has available. To prevent one Pod from monopolizing all available resources, you should set resource limits for Pods. You should set both a memory limit and a CPU limit. If a Pod uses more than its resource limit, it is restarted (new container). If it continues to fail, it goes into a CrashLoopBackoff just like with liveness probes.

You can specify resource limits in the spec.containers[].resources.limits section of a Pod configuration. The following example sets a memory limit of 50 MiB for a container:

spec:                       # The Pod spec in the Deployment
   - image: kiamol/ch12-memory-allocator
       limits:             # Resource limits constrain compute power
         memory: 50Mi      # for the container; this limits RAM to 50 MB.

When you create this Pod, the container is automatically assigned a memory limit of 256 MiB. It will restart when it hits that limit

Namespace Quotas

You can also set resource limits at the namespace level. This is useful if you want to prevent a single user from monopolizing all the resources on a cluster. You can set a quota for the total amount of CPU and memory that can be used by all Pods in a namespace.

apiVersion: v1
kind: ResourceQuota
  name: memory-quota
  namespace: kiamol-ch12-memory
    limits.memory: 150Mi

Because resource quotas are proactive, Pods won’t be created if the limits they specify exceed what’s available in the quota. If there’s a quota in place, then every Pod spec needs to include a resource section so Kubernetes can compare what the spec needs to what’s currently available in the namespace.

Now, if a pod specifies a limit that is greater than the namespace quota, it will not be created. For example:

apiVersion: apps/v1
kind: Deployment
        - name: api
          image: kiamol/ch12-memory-allocator
              memory: 200Mi

CPU Limits

CPU limits to containers and quotas, but they work in a slightly different way. Containers with a CPU limit run with a fixed amount of processing power, and they can use as much of that CPU as they like—they aren’t replaced if they hit the limit

You can use multiples to give your app container access to many cores or divide a single core into “millicores,” where one millicore is one-thousandth of a core

   - image: kiamol/ch05-pi
     command: ["dotnet", "Pi.Web.dll", "-m", "web"]
            cpu: 250m    # 250 millicores limits the container to 0.25 cores.

Include both CPU and memory limits in your Pod specs.

Resource Constraint Failures

What if you have a namespace quota of 500m, but you have two replicas with a limit of 300m each? It will only deploy one pod. YOu can see it like this:

# after deploying your app with two repolicas
% kubectl get deploy -n kiamol-ch12-cpu                                                   

pi-web   1/2     1            1           44s

# Debug what happened (It will tell you it ran out of quota)
% kubectl describe replicaset -n kiamol-ch12-cpu

# Get resource quota
% kl get resourcequota -n kiamol-ch12-memory

Checking Available Resources

You can check cpu available on a node like so:

kubectl get nodes -o jsonpath='{.items[].status.allocatable.cpu}'

You can’t use 100% of the node’s CPU because Kubernetes system components allocate CPU themselves.

Also, when you scale things up, it is helpful to check the ReplicaSet to see if it is scaling up. If it is not, it is likely because it is hitting a resource limit.

kubectl get rs -l app=pi-web --all-namespaces

Don’t Use CPU Limits?

This blog post is controversial, Michal thinks it’s bad advice. I tend to agree with Michal.

Requests vs. Limits

No CPU limit

If you do not specify a CPU limit for a Container, then one of these situations applies:

  • The Container has no upper bound on the CPU resources it can use. The Container could use all of the CPU resources available on the Node where it is running.

  • The Container is running in a namespace that has a default CPU limit, and the Container is automatically assigned the default limit. Cluster administrators can use a LimitRange to specify a default value for the CPU limit.

Limits create requests by default

If you specify a CPU limit for a Container but do not specify a CPU request, Kubernetes automatically assigns a CPU request that matches the limit. Similarly, if a Container specifies its own memory limit but does not specify a memory request, Kubernetes automatically assigns a memory request that matches the limit.