Planning your environment based on tested cluster maximums

This document describes how to plan your Red Hat OpenShift Service on AWS environment based on the tested cluster maximums.

Oversubscribing the physical resources on a node affects resource guarantees the Kubernetes scheduler makes during pod placement. Learn what measures you can take to avoid memory swapping.

Some of the tested maximums are stretched only in a single dimension. They will vary when many objects are running on the cluster.

The numbers noted in this documentation are based on Red Hat testing methodology, setup, configuration, and tunings. These numbers can vary based on your own individual setup and environments.

While planning your environment, determine how many pods are expected to fit per node using the following formula:

required pods per cluster / pods per node = total number of nodes needed

The current maximum number of pods per node is 250. However, the number of pods that fit on a node is dependent on the application itself. Consider the application’s memory, CPU, and storage requirements, as described in Planning your environment based on application requirements.

Example scenario

If you want to scope your cluster for 2200 pods per cluster, you would need at least nine nodes, assuming that there are 250 maximum pods per node:

2200 / 250 = 8.8

If you increase the number of nodes to 20, then the pod distribution changes to 110 pods per node:

2200 / 20 = 110

Where:

required pods per cluster / total number of nodes = expected pods per node

Planning your environment based on application requirements

This document describes how to plan your Red Hat OpenShift Service on AWS environment based on your application requirements.

Consider an example application environment:

Pod type Pod quantity Max memory CPU cores Persistent storage

apache

100

500 MB

0.5

1 GB

node.js

200

1 GB

1

1 GB

postgresql

100

1 GB

2

10 GB

JBoss EAP

100

1 GB

1

1 GB

Extrapolated requirements: 550 CPU cores, 450 GB RAM, and 1.4 TB storage.

Instance size for nodes can be modulated up or down, depending on your preference. Nodes are often resource overcommitted. In this deployment scenario, you can choose to run additional smaller nodes or fewer larger nodes to provide the same amount of resources. Factors such as operational agility and cost-per-instance should be considered.

Node type Quantity CPUs RAM (GB)

Nodes (option 1)

100

4

16

Nodes (option 2)

50

8

32

Nodes (option 3)

25

16

64

Some applications lend themselves well to overcommitted environments, and some do not. Most Java applications and applications that use huge pages are examples of applications that would not allow for overcommitment. That memory can not be used for other applications. In the example above, the environment would be roughly 30 percent overcommitted, a common ratio.

The application pods can access a service either by using environment variables or DNS. If using environment variables, for each active service the variables are injected by the kubelet when a pod is run on a node. A cluster-aware DNS server watches the Kubernetes API for new services and creates a set of DNS records for each one. If DNS is enabled throughout your cluster, then all pods should automatically be able to resolve services by their DNS name. Service discovery using DNS can be used in case you must go beyond 5000 services. When using environment variables for service discovery, if the argument list exceeds the allowed length after 5000 services in a namespace, then the pods and deployments will start failing.

Disable the service links in the deployment’s service specification file to overcome this:

Example
Kind: Template
apiVersion: v1
metadata:
  name: deploymentConfigTemplate
  creationTimestamp:
  annotations:
    description: This template will create a deploymentConfig with 1 replica, 4 env vars and a service.
    tags: ''
objects:
  - kind: DeploymentConfig
    apiVersion: v1
    metadata:
      name: deploymentconfig${IDENTIFIER}
    spec:
      template:
        metadata:
          labels:
            name: replicationcontroller${IDENTIFIER}
        spec:
          enableServiceLinks: false
          containers:
          - name: pause${IDENTIFIER}
            image: "${IMAGE}"
            ports:
            - containerPort: 8080
              protocol: TCP
            env:
            - name: ENVVAR1_${IDENTIFIER}
              value: "${ENV_VALUE}"
            - name: ENVVAR2_${IDENTIFIER}
              value: "${ENV_VALUE}"
            - name: ENVVAR3_${IDENTIFIER}
              value: "${ENV_VALUE}"
            - name: ENVVAR4_${IDENTIFIER}
              value: "${ENV_VALUE}"
            resources: {}
            imagePullPolicy: IfNotPresent
            capabilities: {}
            securityContext:
              capabilities: {}
              privileged: false
          restartPolicy: Always
          serviceAccount: ''
      replicas: 1
      selector:
        name: replicationcontroller${IDENTIFIER}
      triggers:
      - type: ConfigChange
      strategy:
        type: Rolling
  - kind: Service
    apiVersion: v1
    metadata:
      name: service${IDENTIFIER}
    spec:
      selector:
        name: replicationcontroller${IDENTIFIER}
      ports:
      - name: serviceport${IDENTIFIER}
        protocol: TCP
        port: 80
        targetPort: 8080
      portalIP: ''
      type: ClusterIP
      sessionAffinity: None
    status:
      loadBalancer: {}
  parameters:
  - name: IDENTIFIER
    description: Number to append to the name of resources
    value: '1'
    required: true
  - name: IMAGE
    description: Image to use for deploymentConfig
    value: gcr.io/google-containers/pause-amd64:3.0
    required: false
  - name: ENV_VALUE
    description: Value to use for environment variables
    generate: expression
    from: "[A-Za-z0-9]{255}"
    required: false
  labels:
template: deploymentConfigTemplate

The number of application pods that can run in a namespace is dependent on the number of services and the length of the service name when the environment variables are used for service discovery. ARG_MAX on the system defines the maximum argument length for a new process and it is set to 2097152 KiB by default. The kubelet injects environment variables in to each pod scheduled to run in the namespace including:

  • <SERVICE_NAME>_SERVICE_HOST=<IP>

  • <SERVICE_NAME>_SERVICE_PORT=<PORT>

  • <SERVICE_NAME>_PORT=tcp://<IP>:<PORT>

  • <SERVICE_NAME>_PORT_<PORT>_TCP=tcp://<IP>:<PORT>

  • <SERVICE_NAME>_PORT_<PORT>_TCP_PROTO=tcp

  • <SERVICE_NAME>_PORT_<PORT>_TCP_PORT=<PORT>

  • <SERVICE_NAME>_PORT_<PORT>_TCP_ADDR=<ADDR>

The pods in the namespace start to fail if the argument length exceeds the allowed value and if the number of characters in a service name impacts it.