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Last active Dec 12, 2017

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Honestbee Helm conventions

Honestbee - Helm Chart Conventions

Coding conventions for Helm Charts at Honestbee. This document is subject to change based on the ongoing Helm best practices discussion

NOTE: Official Best Practices have been updated - refer to the official Helm Chart Best practices

Kubernetes Chart requirements

Adapted from the Official Kubernetes Chart Requirements

Technical requirements

Recommended chart requirements, if any of these are not met - kindly highlight in README.md

  • All Chart dependencies should also be submitted independently
  • Must pass the linter (helm lint)
  • Must successfully launch with default values (helm install .)
    • All pods go to the running state
    • All services have at least one endpoint
  • Must link source GitHub repositories for images used in the Chart
  • Images should not have any major security vulnerabilities
  • Must be up-to-date with the latest stable Helm/Kubernetes features
    • Use Deployments in favor of ReplicationControllers
  • Should follow Kubernetes best practices
  • Provide a method for data persistence (if applicable)
  • Support application upgrades
  • Allow customization of the application configuration
  • Provide a secure default configuration
  • Do not leverage alpha features of Kubernetes
  • Includes a NOTES.txt explaining how to use the application after install

Documentation requirements

  • Must include an in-depth README.md, including:
    • Short description of the Chart
    • Any prerequisites or requirements
    • Customization: explaining options in values.yaml and their defaults
  • Must include a short NOTES.txt, including:
    • Any relevant post-installation information for the Chart
    • Instructions on how to access the application or service provided by the Chart

Honestbee Guidelines

General

  • Use yaml with 2 spaces indentation

File Naming convention

Each resource type should have its own file under the templates/ directory (do not stream multiple yaml documents into a single yaml file). These files have the following naming convention:

  1. Prefix the files with the name of the Chart component (i.e an elasticsearch cluster has master, client and data components).

  2. Use abbreviations of Kubernetes Resource Types (if they exist):

    Abbreviation Full name
    svc service
    deploy deployment
    cm configmap
    secret secret
    ds daemonset
    rc replicationcontroller
    petset petset
    po pod
    hpa horizontalpodautoscaler
    ing ingress
    job job
    limit limitrange
    ns namespace
    pv persistentvolume
    pvc persistentvolumeclaim
    sa serviceaccount

For example:

master-deploy.yaml  # deployment of a master component
web-deploy.yaml     # deployment of a web component
web-svc.yaml        # service definition of a web component
registry-rc.yaml    # replication controller of a registry component

Template Names

Template names are global, even when used in sub-charts. Due to this, template names should always be scoped to their chart.

Wrong:

{{- define "fullname" -}}
{{- printf "%s-%s" .Release.Name "kibana" | trunc 63 -}}
{{- end -}}

Right:

{{- define "kibana.fullname" -}}
{{- printf "%s-%s" .Release.Name "kibana" | trunc 63 -}}
{{- end -}}

Upper or Lower case Variables

Helm Classic used variables starting with an upper case letter.

When Helm was incubated by the Kubernetes project, Kubernetes maintainers however prefer to separate local variables by using lower case letters.

Additionally, lower case variables match the Kubernetes Manifest naming conventions, giving you the ability to include snippets from values.yaml directly into your Manifests:

template:
    metadata:
        labels:
          app: {{ template "scoped.fullname" . }}
      spec:
        containers:
        - name: {{ template "scoped.fullname" . }}
          image: "{{ .Values.image }}"
          resources:
{{ toYaml .Values.resources | indent 10 }}

Reference

Drawback?: this requires a default values.yaml to be present with resource default, allowing users to specify additional configuration values using the -f custom-values.yaml flag.

Going forward, all variables in Charts written at Honestbee should start with a lower case letter.

Flat or Nested Configuration Values

Flat names for values are preferred (as advised in the Helm guidelines), but nested variables can be very useful when used carefully.

At Honestbee, the following rule of thumb can be used:

If you have multiple parameters related to a single entity and at least 1 parameter is mandatory, use nested variables.

Reasoning: you can't omit the root of the nested variable, even if you intend every option in the hierarchy to be optional.

Following examples can be used as a guideline:

  1. Related Parameters of which none are mandatory:

    Nested:

    Ports:
      http: 5000
      node: 30650
      web: 80
      service: 80

    vs Flat:

    httpPort: 5000
    nodePort: 30650
    webPort: 80
    servicePort: 80

    If every Port has a default, it is better to use the flat version. With the flat version you can completely omit the whole Ports map.

  2. Related (repeated) Parameters of which at least 1 is mandatory

    Flat:

    masterReplicaCount: 1
    masterMemRequest: 1Gi
    masterMemLimit: 2Gi
    masterImage: master
    masterIsSchedulable: true
    workerReplicaCount: 3
    workermemRequest: 1Gi
    workermemLimit: 1Gi
    workerImage: worker

    vs Nested:

    master:
      replicaCount: 1
      isSchedulable: true
      memRequest: 1Gi
      memLimit: 2Gi
      image: master
    worker:
      replicaCount: 3
      memRequest: 1Gi
      memLimit: 1Gi
      image: worker

    Nested variables can improve readability and maintainability. In this case, at least 1 key for each map needs to exist, with all defaults this may look like this:

    master:
      replicaCount: 1
    worker:
      replicaCount: 3

Labels

A cluster can be used to deploy multiple applications and services. To be able to correctly filter components in services and replication controllers we should define labels to achieve this.

This section defines a set of labels that should be used.

heritage (mandatory)

All manifests must specify the {{ .Release.Service | quote }} label in the metadata section. This enables querying a cluster to list all components deployed using Helm:

kubectl get deploy,svc -l heritage=Tiller

release (mandatory)

All manifests must specify the {{ .Release.Name | quote }} label in the metadata section. This enables querying a cluster to list all components deployed for a particular release:

kubectl get deploy,svc -l release=rolling-badger

chart (mandatory)

All manifests must specify the {{ .Chart.Name }}-{{ .Chart.Version }} label in the metadata section. This enables identifying the chart and version of cluster resources.

kubectl describe deploy rolling-badger-elasticsearch | grep chart

Note: helm list and helm status <release> give you the same?

app (mandatory)

All manifests must specify the app label in the metadata section.

kubectl get deploy,svc -l app=elasticsearch

When the manifests deploy more than one resource, the app label should be defined to group all the components under one label. This enables querying a cluster to list all components deployed for a particular app, while ensuring services can be created to expose just a particular component where needed:

For example, if in a GitLab deployment gitlab-workhorse and sidekiq are defined in different manifests, these manifests should both have the app: gitlab label grouping the components together.

component (optional)

Custom labels can be be defined to provide fine-grained filtering of pods in services and replication controllers. For example, a MariaDB pod can have a component: label to indicate if it’s a master or slave allowing the Services to correctly filter Pods.

Split Release, App & Component in selectors

Split release and component from app label and add release to selector. i.e - don't use fullname templates for labels (do use fullname templates for resource names).

Wrong

  selector:
    app: {{ printf "%s-%s-%s" .Release.Name .Chart.Name "worker" }}
    # or
    app: {{ template "kibana.fullname" }}

Right

  selector:
    app: {{ .Chart.Name }}
    release: {{ .Release.Name }}
    component: worker

Order

At Honestbee the preferred order is:

    heritage: {{ .Release.Service | quote }}
    release: {{ .Release.Name | quote }}
    chart: "{{ .Chart.Name }}-{{ .Chart.Version }}"
    app: {{ template "scoped.fullname" }}
    component: ...

Container Image tags

Use versioned images, avoid using the latest tag.

If the latest tag is used, define imagePullPolicy: Always.

Provide links to image source (GitHub or DockerHub) in README.

Ports

Always define named ports in the podSpec. Whenever possible name the ports with the IANA defined service name (eg. iana?search=http).

Pod Lifecycle Management

All containerSpecs should define probes of type livenessProbe and readinessProbe. (note: all probes are ran by kubelet in the kubelet network namespace)

Three primitives are available for setting up these probes (only 1 may be specified per probe):

  • HTTP check (httpGet)

    Performs an HTTP Get against the container’s IP address on a specified port and path expecting on success that the response has a status code greater than or equal to 200 and less than 400.

  • Container Execution Check (exec)

    Executes a specified command inside the container expecting on success that the command exits with status code 0.

  • TCP Socket Check (tcpSocket)

    Performs a tcp check against the container’s IP address on a specified port expecting on success that the port is open.

Liveness Probe

A liveness probe checks if the container is running and responding normally. If the liveness probe fails, the container is terminated and subject to the pod's RestartPolicy. The RestartPolicy is applicable to all containers in the pod (default: Always).

Below is an example livenessProbe for a mariadb podSpec.

...
    spec:
      containers:
      - name: mariadb
        image: bitnami/mariadb:5.5.46-0-r01
        livenessProbe:
          exec:
            command:
            - mysqladmin
            - ping
          initialDelaySeconds: 30
          timeoutSeconds: 5

Here an exec probe is setup to check the status of the MariaDB server at 5 second intervals using the mysqladmin ping command. The Pod will be restarted if the command returns an error for any reason.

To allow the container to boot up before the liveness probes start, the initialDelaySeconds should be set high enough to allow the container to start or the container will be prematurely terminated by the probe (default failureThreshold before termination is 3).

To better understand the flow of container states, consider a Running pod with 2 containers. Assume container 1 terminates with Failure.

  • if restartPolicy is:
    • Always: restart container, pod stays Running
    • OnFailure: restart container, pod stays Running
    • Never: Pod stays Running
  • When container 2 exists with Failure...
    • if restartPolicy is:
      • Always: restart container, pod stays Running
      • OnFailure: restart container, pod stays Running
      • Never: pod becomes Failed
        • if running under a controller, pod will be recreated elsewhere

Readiness Probe

To ensure traffic is sent only to pods once a probe succeeds, ensure a readinessProbe is defined in the containerSpec.

A readiness probe indicates whether the container is ready to service requests. If the readiness probe fails, the endpoints controller will remove the pod’s IP address from the endpoints of all services that match the pod until readiness probes succeed again.

The setup of a readiness probe is similar to a liveness probe:

...
    spec:
      containers:
      - name: mariadb
        image: bitnami/mariadb:5.5.46-0-r01
        ports:
        - name: mysql
          containerPort: 3306
        livenessProbe:
          exec:
            command:
            - mysqladmin
            - ping
          initialDelaySeconds: 30
          timeoutSeconds: 5
        readinessProbe:
          exec:
            command:
            - mysqladmin
            - ping
          initialDelaySeconds: 5
          timeoutSeconds: 1

Because we want the Pod to start receiving traffic as soon as it's ready, a lower initialDelaySeconds value is specified.

A lower timeoutSeconds ensures that the Pod does not receive any traffic as soon as it becomes unresponsive. If the failure was temporary, the Pod would resume normal functioning after it has recovered.

Note: Allowing different probes for liveness and readiness, provides a way to define applications with fine grained traffic control for maintenance windows.

Volumes

Volumes are required to persist container data and a method for data persistence (if applicable) should be specified.

Example (works for AWS, GCE, minikube):

{{- if .Values.persistence.enabled -}}
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: {{ template "scoped.fullname" . }}
  labels:
    app: {{ template "scoped.fullname" . }}
    chart: "{{ .Chart.Name }}-{{ .Chart.Version }}"
    release: "{{ .Release.Name }}"
    heritage: "{{ .Release.Service }}"
  annotations:
    volume.alpha.kubernetes.io/storage-class: {{ .Values.persistence.storageClass | quote }}
spec:
  accessModes:
    - {{ .Values.persistence.accessMode | quote }}
  resources:
    requests:
      storage: {{ .Values.persistence.size | quote }}
{{- end -}}

with values.yaml:

## Enable persistence using Persistent Volume Claims
## ref: http://kubernetes.io/docs/user-guide/persistent-volumes/
##
persistence:
  enabled: true
  storageClass: generic
  accessMode: ReadWriteOnce
  size: 8Gi

Services

To expose the web applications running in a Kubernetes cluster, a Service resource type needs to be created. Service objects are used for discovering and routing traffic to each Pod resource. The set of Pods targeted by a Service is determined by label selectors. The following is a sample of a simple Service.yaml manifest.

Note that the chart: "{{ .Chart.Name }}-{{ .Chart.Version }}" label is not used in the label selectors as its inclusion will not allow for rolling updates.

Also note that if multiple deployments of the same chart within the same namespace is required, include Release information in the fullname template and use the fullname template in the application selector.

Lastly, named ports should be used to specify the service targetPort, allowing us to change the port numbers in the podSpec without the need to change the Service manifests.

Secrets and ConfigMaps

Objects of type ConfigMap are intended to hold configuration values. Putting this information in a ConfigMap is more flexible than adding it to the Manifest template or baking it into a docker image.

Objects of type Secret are intended to hold sensitive information, such as passwords, OAuth tokens, and ssh keys. Secrets allow the use of specialized controllers to store data encrypted.

Another difference between configMaps and Secrets is that volumeMounts for configMaps update (with inotify) in existing pods, while Secrets do not change by design and require pods to be re-created. (See chart tips & tricks)

Example:

apiVersion: v1
kind: ConfigMap
metadata:
  name: {{ template "scoped.component-configmap" . }}
  labels:
    heritage: {{ .Release.Service | quote }}
    release: {{ .Release.Name | quote }}
    chart: "{{ .Chart.Name }}-{{ .Chart.Version }}"
    app: {{ template "scoped.fullname" . }}
data:
{{ (.Files.Glob "files/component/*").AsConfig | indent 2 }}

Note AsSecrets and AsConfig utility functions.

Documenting Parameters

The README for each chart should document all parameters. A helpful one-liner to grep all Values from a chart templates directory:

grep -Rohe '.Values.[a-zA-z0-9.]*' ./templates | cut -d. -f3- | sort -u

(remove -h flag to show file where parameter is used)

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