VPA Recommender for Serverless Workloads

Source code is from this code. Change the image name to new image name instead of the default one in autoscaler/vertical-pod-autoscaler/deploy/recommender-deployment.yaml

Intro

Recommender is the core binary of Vertical Pod Autoscaler system. It computes the recommended resource requests for pods based on historical and current usage of the resources. The current recommendations are put in status of the VPA resource, where they can be inspected.

Running

• In order to have historical data pulled in by the recommender, install Prometheus in your cluster and pass its address through a flag.
• Create RBAC configuration from ../deploy/vpa-rbac.yaml.
• Create a deployment with the recommender pod from ../deploy/recommender-deployment.yaml.
• The recommender will start running and pushing its recommendations to VPA object statuses.

Implementation

The recommender is based on a model of the cluster that it builds in its memory. The model contains Kubernetes resources: Pods, VerticalPodAutoscalers, with their configuration (e.g. labels) as well as other information, e.g. usage data for each container.

After starting the binary, recommender reads the history of running pods and their usage from Prometheus into the model. It then runs in a loop and at each step performs the following actions:

• update model with recent information on resources (using listers based on watch),
• update model with fresh usage samples from Metrics API,
• compute new recommendation for each VPA,
• put any changed recommendations into the VPA resources.