Helm Install
Installation
The Pipekit Agent must be installed onto each cluster where your Argo Workflow controller runs.
Helm Install
When you choose to connect a cluster in Pipekit, you will be provided with a Secret Access Key for the cluster and a unique Cluster ID. These need to be passed to the helm chart when installing the Pipekit Agent. You should store the Secret Access Key securely in a password manager or similar.
Argo CD
If you are using Argo CD, you can install the Pipekit Agent using the following steps:
Create and push a secret to your cluster containing your pipekitSecretAccessKey and pipekitClusterId
Create a new Argo CD Application Manifest, referencing that secret:
Argo CD offers other secrets management alternatives to ensure that your secrets are not stored in plaintext in your git repository. You can read more about them here.
Release Notes
Release notes are published on the Pipekit Releases site.
Pipekit Agent Helm Chart Values
There are other optional, configurable options within the Helm Chart. These are listed below.
Key | Type | Default | Description |
---|---|---|---|
configMap.additionalConfig | object |
| |
configMap.allowExternalWorkflows | bool |
| Allow Pipekit Agent to monitor workflows created without Pipekit. This is disabled by default. |
configMap.annotations | object |
| Add any additional annotations to the Pipekit Agent ConfigMap. |
configMap.externalWorkflowsCheckPeriod | string |
| The period at which the Pipekit Agent checks for external workflows. This is set to 10s by default. |
configMap.externalWorkflowsMaxWorkers | string | 10 | The maximum number of workers that the Pipekit Agent can use to execute external workflows. |
configMap.externalWorkflowsNamespaces | string |
| The list of comma-separated namespaces where the Pipekit Agent should look for external workflows. Notes: Pipekit Agent needs appropriate permissions to get, list, patch and delete workflows in the defined namespaces. |
configMap.logLevel | string |
| Set the logLevel for the Pipekit Agent. |
configMap.name | string |
| Specifies the name of the ConfigMap to create. Leave blank to auto-generate a name. |
configMap.sendLogsToPipekit | bool |
| Send Workflow logs to Pipekit. Pipekit will store and index logs for you to view at pipekit.io |
configMap.shouldDeleteExternalWorkflows | bool |
| Should the Pipekit Agent delete external workflows after execution. This is set to false by default. |
configMap.telemetryProtocols | string |
| set to 'none' to disable all telemetry |
deployment.image.imagePullSecrets | list |
| Allows you to define the name of existing imagePullSecrets to use for pulling the Pipekit Agent image. |
deployment.image.pullPolicy | string |
| The imagePullPolicy for the Pipekit Agent image. |
deployment.image.repository | string |
| The Pipekit Agent image name and repository. Change this if you wish to host the container yourself. |
deployment.image.tag | string |
| Allows you to pin to a specific image tag. The Chart.yaml contains a default value. |
deployment.nodeSelector | object |
| The Pipekit Agent pod's node selector. |
deployment.podAnnotations | object |
| Add any additional annotations to the Pipekit Agent pod. |
deployment.podLabels | object |
| Add any additional labels to the Pipekit Agent pod. |
deployment.resources | object |
| Set the Pipekit Agent pod's resource requests and limits. We suggest a minimal amount of resources below, but you should increase these if needed as actual resource usage will depend on usage. |
features | object |
| Enable and Disable features of the Pipekit Agent. |
features.metrics.argoWfControllerLabels | object |
| the labels we should use to select the workflow controller. Defaults to |
features.metrics.argoWfMetricsPath | string |
| The path where your Argo Workflows controller exposes metrics. |
features.metrics.argoWfMetricsPort | int |
| The port number of your Argo Workflows controller that exposes metrics. |
features.metrics.argoWfNamespace | string |
| The namespace where your Argo Workflows controller is running. This tells Pipekit Agent where to find the Workflow metrics. |
features.metrics.collectorLogLevel | string |
| The Pipekit Agent Metrics Collector will log at this level. |
features.metrics.collectorNodeSelector | object |
| A nodeselector for the opentelemetry collector |
features.metrics.collectorResources | object |
| Resource requests and limits for the collector |
features.metrics.deployment.image.imagePullSecrets | list |
| Allows you to define the name of existing imagePullSecrets to use for pulling the Pipekit Agent Operator image. |
features.metrics.deployment.image.pullPolicy | string |
| The imagePullPolicy for the Pipekit Agent Operator image. |
features.metrics.deployment.image.repository | string |
| The Pipekit Agent Operator image name and repository. Change this if you wish to host the container yourself. |
features.metrics.deployment.image.tag | string |
| Allows you to pin to a specific image tag. The Chart.yaml contains a default value. |
features.metrics.deployment.replicas | int |
| The number of replicas for the Pipekit Agent Metrics Collector. |
features.metrics.deployment.resources | object |
| Set the Pipekit Agent Controller Manager pod's resource requests and limits. We suggest a minimal amount of resources below, but you should increase these if needed as actual resource usage will depend on usage. |
features.metrics.enabled | bool |
| Enable and Disable Pipekit Workflow metrics. This passes Workflow metrics from your cluster to Pipekit in order to view them in the Workflow Metrics dashboard. # You must sign up here to use this feature or email hello@pipekit.io. |
features.metrics.k8sAuthType | string |
| kubernetes authentication method, defaults to serviceAccount alternative setting is none |
features.metrics.otelCollectorImage | string |
| The docker name of the opentelemetry contrib collector image to deploy |
features.metrics.otelCollectorTag | string |
| The tag of the collector image to use |
features.workflows | object |
| Enable and Disable the Pipekit Agent. This communicates with Pipekit and allows you to run and manage your workflows. |
fullnameOverride | string |
| Completely replace the generated name with the provided name. |
metrics.enabled | bool |
| Enables a Service and ServiceMonitor for Prometheus metrics. |
nameOverride | string |
| Replaces the name of the chart in Chart.yaml. |
secrets.annotations | object |
| Add any additional annotations to the Pipekit Agent Secret. Requires secrets.existingSecret to be blank. |
secrets.existingSecret | string |
| The name of an existing secret containing your pipekitSecretAccessKey and pipekitClusterId. |
secrets.name | string |
| Specifies the name of the Secret to create. Leave blank to auto-generate a name. Requires secrets.existingSecret to be blank. |
secrets.pipekitClusterId | string |
| Enter the pipekitClusterId provided by Pipekit when you added the cluster. Requires secrets.existingSecret to be blank. |
secrets.pipekitSecretAccessKey | string |
| Enter the pipekitSecretAccessKey provided by Pipekit when you added the cluster. Requires secrets.existingSecret to be blank. |
serviceAccount.annotations | object |
| Add any additional annotations to the Pipekit Agent ServiceAccount and ServiceAccount Token Secret. |
serviceAccount.create | bool |
| Specifies whether a ServiceAccount should be created. If false, you must provide an existing ServiceAccount name. |
serviceAccount.name | string |
| Specifies the name of the ServiceAccount to create if serviceAccount.create is true. Otherwise, specifies the name of an existing ServiceAccount to use. |
Secrets
If you wish to provide your own secret you need to populate it with the pipekitSecretAccessKey and pipekitClusterId values, using the defined data keys below:
Chart var | .data. in Secret |
secrets.pipekitSecretAccessKey | PIPEKIT_SECRET_ACCESS_KEY |
secrets.pipekitClusterId | PIPEKIT_CLUSTER_ID |
eg:
You must use single quotes '' to escape special characters such as $, , *, =, and ! in your strings. If you don't, your shell will interpret these characters.
Enabling Externally Triggered Workflows
If you wish to enable externally triggered workflows, you can set the following values in your Helm install command:
You can additionally set configMap.externalWorkflowsCheckPeriod
, configMap.externalWorkflowsNamespace
and configMap.shouldDeleteExternalWorkflows
. Refer to the values table above for more information.
Pipekit Agent Cluster Permissions
The Pipekit Agent needs to interact with Argo Workflows on your cluster. In order to do this, we create a ServiceAccount and ClusterRole for the Pipekit Agent. If you wish to manually manage this ServiceAccount and ClusterRole, you can set serviceAccount.create to false and provide the name of an existing ServiceAccount to use.
The required minimum permissions are:
Upgrading Pipekit Agent
Checking the latest version
Pipekit Agent is automatically published to Artifact Hub. You can use this service to configure automatic notifications of new versions, either via an RSS feed or a webhook.
Alternatively, you can search the helm repo for the latest version of the Pipekit Agent using the following command:
For further information on the helm search repo
command, please refer to the official Helm documentation.
Changes to the default values.yaml
Prior to upgrading, you should ensure that you understand any changes to the default values.yaml and the impact those changes may have on your installation. This page is always updated with the latest available helm chart values for the Pipekit Agent.
If you wish to upgrade to an older version of the Pipekit Agent helm chart, you can extract the default values for that version using the following command:
The Pipekit-Agent values file is commented so you can see what each value does.
You can extract your existing values from your current installation using the following command:
For further information the helm commands used above, please refer to the official Helm documentation.
Upgrading the Pipekit Agent
To upgrade the Pipekit Agent, you can use the following command:
For more information on using Helm to perform upgrades, please check the official Helm documentation.
Automating the upgrades using Gitops
If you use a Gitops tool such as Argo CD, you can simply commit your changes to your git repository and the tool will handle the Helm upgrade for you.
If you wish to automate the upgrade process, we recommend a third party tool called Renovate Bot that can be configured to automatically raise pull requests for you when a new version of the Pipekit Agent is released.
Upgrade Support
If you have an issue upgrading your Pipekit Agent that isn't addressed here, please contact us over Slack, or by email at support@pipekit.io.
Last updated