Open Source Goldilocks: What and How

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What is a Goldilocks?

Goldilocks is an Open Source tool by Fairwinds. And Goldilocks provides us a dashboard that gives us recommendations on how to set our resource requests. It is a utility that can help us to identify a starting point for resource requests and limits. It gives us a Right-size to our Kubernetes Deployments by comparing memory and CPU settings against actual usage.
Goldilocks doesn’t recommend resource requests/limits by itself. It utilizes a Kubernetes project called VPA

Vertical Pod Autoscaler(VPA)

Vertical Pod Autoscaler (VPA) is a component you install in your cluster. It increases and decreases container CPU and memory resource configuration to align cluster resource allotment with actual usage.

With VPA, there are two different types of resource configurations that we can manage on each container of a pod:

Requests
Limits

Component Of VPA

The VPA Recommender
The VPA Updater
The VPA Admission Controller

We can utilize the VPA recommendation engine by running a controller in the cluster that’s gonna watch for the namespaces that are labeled with goldilocks.fairwinds.com/enabled=true. Within those enabled namespaces, we look at the deployments object and then, create an equivalent VPA object. That VPA is set with Mode:OFF and it doesn’t even update the resource requests and limits. It just gives us a recommendation. This alone is sort of cool, but in order to view these recommendations, you would have to use kubectl to query each and every VPA object. For medium to large deployments, this can get very tedious. That’s where the dashboard comes in.

Goldilocks Dashboard provides us a visualization of VPA recommendations. Now we can see the services in a cluster and it is showing two types of recommendations, depending on the QoS class we desire for our deployments

Prerequisite for Goldilocks

1. Kubectl ( kubectl should be connected to the cluster you want to install VPA)

2. VPA

3. Metrics sever

Installation of Goldilocks

We can install Goldilocks using the Helm chart.

helm repo add fairwinds-stable https://charts.fairwinds.com/stable
helm install --name goldilocks --namespace goldilocks --set 
installVPA=true fairwinds-stable/goldilocks

How Goldilocks work

vi vpa_demo.yaml

apiVersion: autoscaling.k8s.io/v1beta2
kind: VerticalPodAutoscaler
metadata:
  name: demovpa
  namespace: demo
spec:
  targetRef:
    apiVersion: "apps/v1"
    kind: Deployment
    name: vpa
  updatePolicy:
    updateMode: "Auto"
  resourcePolicy:
    containerPolicies:
    - containerName: "vpa"
      minAllowed:
        cpu: "250m"
        memory: "100Mi"
      maxAllowed:
        cpu: "500m"
        memory: "600Mi"

kubectl apply -f vpa_demo.yaml

vi deployment_demo.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: deployment
  namespace: demo
spec:
  selector:
    matchLabels:
      app: deployment
  replicas: 2
  template:
    metadata:
      labels:
        app: deployment
    spec:
      securityContext:
        runAsNonRoot: true
        runAsUser: 65534 
      containers:
        - name: devops1
          image: ubuntu:latest
          resources:
            requests:
              cpu: 100m
              memory: 50Mi
            limits:
              cpu: 511m
              memory: 263Mi
          command: ["/bin/sh"]
          args:
            - "-c"
            - "while true; do timeout 0.5s yes >/dev/null; sleep 0.5s; done"

kubectl apply -f deployment_demo.yaml