Jul 6, 2021 · Jun 30, 2021 · Jun 30, 2021
diff --git a/_docs/administration/codefresh-runner.md b/_docs/administration/codefresh-runner.md
 - `KB_USAGE_THRESHOLD` - default 80 (percentage)
 - `INODE_USAGE_THRESHOLD` - default 80

 ## ARM Builds

 With hybrid runner it's possibe to run native ARM64v8 builds.

 >**Note:** Running both amd64 and arm64 images within the same pipeline - it is not possible. We do not support multi-architecture builds. One runtime configuration - one architecture. Considering one pipeline can map only to one runtime, it is possible to run either amd64 or arm64, but not both within a one pipeline

 The following scenario is an example of how to set up ARM Runner on existing EKS cluster:
 ##### Step 1 - Preparing nodes
 Create new ARM nodegroup:

 ```shell
 eksctl utils update-coredns --cluster <cluster-name>
 eksctl utils update-kube-proxy --cluster <cluster-name> --approve
 eksctl utils update-aws-node --cluster <cluster-name> --approve

 eksctl create nodegroup \
 --cluster <cluster-name> \
 --region <region> \
 --name <arm-ng> \
 --node-type <a1.2xlarge> \
 --nodes <3>\
 --nodes-min <2>\
 --nodes-max <4>\
 --managed
 ```

 Check nodes status:

 ```shell
 kubectl get nodes -l kubernetes.io/arch=arm64
 ```

 Also it's recommeded to label and taint the required ARM nodes:

 ```shell
 kubectl taint nodes <node> arch=aarch64:NoSchedule
 kubectl label nodes <node> arch=arm
 ```

 ##### Step 2 - Runner installation
 Use [values.yaml](https://github.com/codefresh-io/venona/blob/release-1.0/venonactl/example/values-example.yaml) to inject `tolerations`, `kube-node-selector`, `build-node-selector` into the Runtime Environment spec.

 `values-arm.yaml`

 {% highlight yaml %}
 {% raw %}
 ...
 Namespace: codefresh

 ### NodeSelector --kube-node-selector: controls runner and dind-volume-provisioner pods
 NodeSelector: arch=arm

 ### Tolerations --tolerations: controls runner, dind-volume-provisioner and dind-lv-monitor
 Tolerations:
 - key: arch
  operator: Equal
  value: aarch64
  effect: NoSchedule
 ...
 ########################################################
 ###                Codefresh Runtime                 ###
 ###                                                  ###
 ###         configure engine and dind pods           ###
 ########################################################
 Runtime:
 ### NodeSelector --build-node-selector: controls engine and dind pods
  NodeSelector:
    arch: arm
 ### Tolerations for engine and dind pods
  tolerations:
  - key: arch
    operator: Equal
    value: aarch64
    effect: NoSchedule
 ...
 {% endraw %}
 {% endhighlight %}

 Install the Runner with:
 ```shell
 codefresh runner init --values values-arm.yaml --exec-demo-pipeline false --skip-cluster-integration true
 ```

 ##### Step 3 - Post-installation fixes

 Change `engine` image version in Runtime Environment specification:

 ```shell
 # get the latest engine ARM64 tag
 curl -X GET "https://quay.io/api/v1/repository/codefresh/engine/tag/?limit=100" --silent | jq -r '.tags[].name' | grep "^1.*arm64$"
 1.136.1-arm64
 ```

 ```shell
 # get runtime spec
 codefresh get re $RUNTIME_NAME -o yaml > runtime.yaml
 ```

 under `runtimeScheduler.image` change image tag:
 {% highlight yaml %}
 {% raw %}
 runtimeScheduler:
  image: 'quay.io/codefresh/engine:1.136.1-arm64'
 {% endraw %}
 {% endhighlight %}


 ```shell
 # patch runtime spec
 codefresh patch re -f runtime.yaml
 ```

 For `local` storage patch `dind-lv-monitor-runner` DaemonSet and add `nodeSelector`:

 ```shell
 kubectl edit ds dind-lv-monitor-runner
 ```
 {% highlight yaml %}
 {% raw %}
    spec:
      nodeSelector:
        arch: arm
 {% endraw %}
 {% endhighlight %}

 ##### Step 4 - Run Demo pipeline

 Run a modified version of the *CF_Runner_Demo* pipeline:
 {% highlight yaml %}
 {% raw %}
 version: '1.0'
 stages:
  - test
 steps:
  test:
    stage: test
    title: test
    image: 'arm64v8/alpine'
    commands:
      - echo hello Codefresh Runner!
 {% endraw %}
 {% endhighlight %}


 ## Troubleshooting

 - **Problem:** You receive an error regarding the provided token or CLI context used for this installation might not have enough permissions.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -1601,6 +1601,150 @@ Override environment variables for `dind-lv-monitor` daemonset if necessary:
		- `KB_USAGE_THRESHOLD` - default 80 (percentage)
		- `INODE_USAGE_THRESHOLD` - default 80

		## ARM Builds

		With hybrid runner it's possibe to run native ARM64v8 builds.

		>Note: Running both amd64 and arm64 images within the same pipeline - it is not possible. We do not support multi-architecture builds. One runtime configuration - one architecture. Considering one pipeline can map only to one runtime, it is possible to run either amd64 or arm64, but not both within a one pipeline

		The following scenario is an example of how to set up ARM Runner on existing EKS cluster:
jesse-codefresh marked this conversation as resolved. Show resolvedHide resolved
		##### Step 1 - Preparing nodes
		Create new ARM nodegroup:

		```shell
		eksctl utils update-coredns --cluster <cluster-name>
		eksctl utils update-kube-proxy --cluster <cluster-name> --approve
		eksctl utils update-aws-node --cluster <cluster-name> --approve

		eksctl create nodegroup \
		--cluster <cluster-name> \
		--region <region> \
		--name <arm-ng> \
		--node-type <a1.2xlarge> \
		--nodes <3>\
		--nodes-min <2>\
		--nodes-max <4>\
		--managed
		```

		Check nodes status:

		```shell
		kubectl get nodes -l kubernetes.io/arch=arm64
		```

		Also it's recommeded to label and taint the required ARM nodes:

		```shell
		kubectl taint nodes <node> arch=aarch64:NoSchedule
		kubectl label nodes <node> arch=arm
		```

		##### Step 2 - Runner installation
		Use [values.yaml](https://github.com/codefresh-io/venona/blob/release-1.0/venonactl/example/values-example.yaml) to inject `tolerations`, `kube-node-selector`, `build-node-selector` into the Runtime Environment spec.

		`values-arm.yaml`

		{% highlight yaml %}
		{% raw %}
		...
		Namespace: codefresh

		### NodeSelector --kube-node-selector: controls runner and dind-volume-provisioner pods
		NodeSelector: arch=arm

		### Tolerations --tolerations: controls runner, dind-volume-provisioner and dind-lv-monitor
		Tolerations:
		- key: arch
		operator: Equal
		value: aarch64
		effect: NoSchedule
		...
		########################################################
		### Codefresh Runtime ###
		### ###
		### configure engine and dind pods ###
		########################################################
		Runtime:
		### NodeSelector --build-node-selector: controls engine and dind pods
		NodeSelector:
		arch: arm
		### Tolerations for engine and dind pods
		tolerations:
		- key: arch
		operator: Equal
		value: aarch64
		effect: NoSchedule
		...
		{% endraw %}
		{% endhighlight %}

		Install the Runner with:
		```shell
		codefresh runner init --values values-arm.yaml --exec-demo-pipeline false --skip-cluster-integration true
		```

		##### Step 3 - Post-installation fixes

		Change `engine` image version in Runtime Environment specification:

		```shell
		# get the latest engine ARM64 tag
		curl -X GET "https://quay.io/api/v1/repository/codefresh/engine/tag/?limit=100" --silent \| jq -r '.tags[].name' \| grep "^1.*arm64$"
		1.136.1-arm64
		```

		```shell
		# get runtime spec
		codefresh get re $RUNTIME_NAME -o yaml > runtime.yaml
		```

		under `runtimeScheduler.image` change image tag:
		{% highlight yaml %}
		{% raw %}
		runtimeScheduler:
		image: 'quay.io/codefresh/engine:1.136.1-arm64'
		{% endraw %}
		{% endhighlight %}


		```shell
		# patch runtime spec
		codefresh patch re -f runtime.yaml
		```

		For `local` storage patch `dind-lv-monitor-runner` DaemonSet and add `nodeSelector`:

		```shell
		kubectl edit ds dind-lv-monitor-runner
		```
		{% highlight yaml %}
		{% raw %}
		spec:
		nodeSelector:
		arch: arm
		{% endraw %}
		{% endhighlight %}

		##### Step 4 - Run Demo pipeline

		Run a modified version of the CF_Runner_Demo pipeline:
		{% highlight yaml %}
		{% raw %}
		version: '1.0'
		stages:
		- test
		steps:
		test:
		stage: test
		title: test
		image: 'arm64v8/alpine'
		commands:
		- echo hello Codefresh Runner!
		{% endraw %}
		{% endhighlight %}


		## Troubleshooting

		- Problem: You receive an error regarding the provided token or CLI context used for this installation might not have enough permissions.
Expand Down