OPTIMIZER.md

Container resources optimizer

Table of contents

• Optimizers
• Enabling optimization

The Optimizer

Vamp Kubist allow to deploy an optimizer alongside deployments. The Optimizer is a lightweight application that will continuously apply bayesian optimization to the resources request and limit configured on the deployment containers, in order to reduce its resources consumption without affecting performances.

Enabling optimization

Enabling a deployment optimization is as simple as updating a deployment definition with a new Policy Executor, as shown in the example below:

imagePullSecret: []
labels: {}
metadata: {}
pod:
  containers:
    - environmentVariables:
        GET_FEEDBACK: "no"
        SHOP_VERSION: "1"
        VAMP_ELASTICSEARCH_URL: http://es-service:9200
      healthChecks: []
      image: magneticio/simpleservice:2.0.12
      metadata: {}
      ports:
        - containerPort: 9191
          hostPort: 0
      readyChecks: []
  metadata: {}
policies: []
replicas: 1
selectors:
  deployment: deployment1
policyExecutor:
  name: OptimizedDeploymentPolicyExecutor
  parameters:
    MIN_CPU: 400
    MAX_CPU: 1000
    MIN_MEMORY: 10000000
    MAX_MEMORY: 200000000000
    OBSERVATION_MINUTES: 2
    INITIAL_POINTS: 3

You can apply the above yaml by running

vamp update deployment deployment1 -a demo-app -f https://raw.githubusercontent.com/magneticio/vampkubistdocs/master/samples/optimized-deployment.yaml

As you can see this will add to the deployment the OptimizedDeploymentPolicyExecutor. This Executor will create a new deployment for the Optimizer inside the vamp-system namespace on your cluster. You can check that the optimizer has been deployed with kubectl by running

kubectl get deployment cro-kubist-demo-deployment1 -n=vamp-system -o yaml

As you can see from the provided yaml, the Executor allows for the configuration of a handful of parameters. More in detail MIN_CPU, MAX_CPU, MIN_MEMORY and MAX_MEMORY allow for configuring the boundaries for the tuning of cpu and memory requests and limits. OBSERVATION_MINUTES allows to specify the length of time the optimizer will observe the deployment behaviour before applying changes and INITIAL_POINTS allows to configure the number trial points before the algorithm actually starts working.

A container optimizer is entirey dependant to its associated deployment, so, should the deployment be deleted, Vamp Kubist will take care of also deleting the optimizer.