Scale Deployment

Use this action to up or downscale a Kubernetes deployment. The attack scales the deployment to the specified replica count at the beginning of the attack and rolls it back to the old replica count whenever the attack stops. Intermediate changes of the replica count, i.e., by third-party tools, don't cause a re-scaling by the attack.

Use Cases

Verify that your deployment is successfully scaled up and the new pod is taken into account by your load balancer
Check how long it takes to scale your deployment to a desirable amount of pods (in combination with a pod count check)

Parameters

Name	Required	Description	Default
Duration	true	How long should the new scale be used?	180s
Replica Count	true	The desired replica count	1

Rollback

At the end of the attack or in case of an error, the old desired replica count will be restored.

Useful Templates

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Keep Deployment's pods down

Check what happens when all pods of a Kubernetes deployment aren't coming up again.

Motivation

Typically, Kubernetes tries to keep as many pods running as desired for a Kubernetes deployment. However, some circumstances may prevent Kubernetes from achieving this, like missing resources in the cluster, problems with the deployment's probes, or a CrashLoopBackOff. You should validate what happens to your upstream services that are using the given deployment as a downstream service.

Structure

To keep the pods down for a given deployment, we first kill all the pods in the deployment. Simultaneously, we will scale down the Kubernetes deployment to 0 to simulate that these pods can't be scheduled again. At the of the experiment, we automatically roll back the deployment's scale to the initial value.

Deployment

Downstream Service

Kubernetes

Kubernetes cluster

Kubernetes deployments

Kubernetes pods

Faultless scaling of Kubernetes Deployment

Ensure that you can scale your deployment in a reasonable time without noticeable errors.

Motivation

For an elastic and resilient cloud infrastructure, ensure that you can scale your deployments without user-visible errors and within a reasonable amount of time. Long startup times, hiccups in the load balancer, or resource misallocation are undesirable but sometimes unnoticed and unexpected.

Structure

For the duration of the experiment and the deployment's upscaling, verify that a user-visible endpoint offered is responding within expected success rates and that no monitors are alerting. As soon as the deployment is scaled up, the newly scheduled pod should be ready to receive traffic within a reasonable time, e.g., 60 seconds.