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Spot/Preemptible Instances

The CAST AI autoscaler supports running your workloads on Spot/Preemptible instances. This guide will help you configure and run it in 5 minutes.

Available configurations


When to use: spot instances are optional

When a pod is marked only with tolerations, the Kubernetes scheduler could place such a pod/pods on regular nodes as well.

  - key:
    operator: Exists

Node Selectors

When to use: only use spot instances

If you want to make sure that a pod is scheduled on spot instances only, add nodeSelector as well as per the example below. The autoscaler will then ensure that only a spot instance is picked whenever your pod requires additional workload in the cluster.

  - key:
    operator: Exists
nodeSelector: "true"

Spot Reliability

When to use: there's a need to minimize workload interruptions

Autoscaler is able to identify which instance types are less likely to be interrupted. You can set a default reliability value cluster-wide in spot instance policy. If you want to control that per-workload, e.g. leave most const-efficient value globally and only choose more stable instances for specific pods, define this in deployment configuration by setting label on the pod.

Here's an example how it's done for the typical deployment:

      labels: 10

Reliability is measured by "what is the percentage of reclaimed instances during trailing month for this instance type". This tag specifies an upper limit - all instances below specified reliability value will be considered.

The value is a percentage (range is 1-100), and the meaningful values are:

  • 5: most reliable category; by using this value you'll restrict autoscaler to use only the narrowest set of spot instance types
  • 10 - 15: reasonable value range to compromise between reliability and price;
  • 25 and above: typically most instances fall into this category,.

For AWS, have a look at Spot instance advisor to get an idea which instances correspond to which reliability category.

Step-by-step deployment on Spot Instance

In this step-by-step guide, we demonstrate how to use Spot Instances with your CAST AI clusters.

To do that, we will use an example NGINX deployment configured to run only on Spot/Preemptible instances.

0. Pre-requisites

1. Enable relevant policies

To start using Spot instances autoscaler enable the following policies under the Policies menu in the UI:

  • Spot/Preemptible instances policy

    • This policy allows the autoscaler to use spot instances
  • Unschedulable pods policy

    • This policy requests an additional workload to be scheduled based on your deployment requirements (i.e. run on spot instances)

2. Example deployment

Save the following yaml file, and name it: nginx.yaml:

apiVersion: apps/v1
kind: Deployment
  name: nginx-deployment
    app: nginx
  replicas: 1
      app: nginx
        app: nginx
      nodeSelector: "true"
        - key:
          operator: Exists
        - name: nginx
          image: nginx:1.14.2
            - containerPort: 80
              cpu: '2'
              cpu: '3'

2.1. Apply the example deployment

With kubeconfig set in your current shell session, you can execute the following (or use other means of applying deployment files):

kubectl apply -f ngninx.yaml

2.2. Wait several minutes

Once the deployment is created, it will take up to several minutes for the autoscaler to pick up the information about your pending deployment and schedule the relevant workloads in order to satisfy the deployment needs, such as:

  • This deployment tolerates spot instances
  • This deployment must run only on spot instances

3. Spot Instance added

  • You can see your newly added spot instance in the cluster node list.

3.1. AWS instance list

Just to double-check, go to the AWS console and check that the added node has the Lifecycle: spot indicator.