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Merge pull request #156 from NearNodeFlash/release-v0.1.2
Release v0.1.2
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‎.github/workflows/publish-main.yaml

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name: Publish `main` Documentation
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on:
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push:
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branches:
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- main
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on: [push]
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jobs:
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build:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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run: |
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mike deploy --push dev
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‎docs/guides/global-lustre/readme.md

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---
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authors: Blake Devcich <[email protected]>
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categories: provisioning
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---
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# Global Lustre
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## Background
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Adding global lustre to rabbit systems allows access to external file systems. This is primarily
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used for Data Movement, where a user can perform `copy_in` and `copy_out` directives with global
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lustre being the source and destination, respectively.
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Global lustre fileystems are represented by the `lustrefilesystems` resource in Kubernetes:
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```shell
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$ kubectl get lustrefilesystems -A
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NAMESPACE NAME FSNAME MGSNIDS AGE
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default mylustre mylustre 10.1.1.113@tcp 20d
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```
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An example resource is as follows:
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```yaml
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apiVersion: lus.cray.hpe.com/v1beta1
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kind: LustreFileSystem
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metadata:
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name: mylustre
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namespace: default
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spec:
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mgsNids: 10.1.1.100@tcp
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mountRoot: /p/mylustre
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name: mylustre
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namespaces:
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default:
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modes:
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- ReadWriteMany
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```
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## Namespaces
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Note the `spec.namespaces` field. For each namespace listed, the `lustre-fs-operator` creates a
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PV/PVC pair in that namespace. This allows pods in that namespace to access global lustre. The
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`default` namespace should appear in this list. This makes the `lustrefilesystem` resource available
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to the `default` namespace, which makes it available to containers (e.g. container workflows)
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running in the `default` namespace.
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The `nnf-dm-system` namespace is added automatically - no need to specify that manually here. The
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NNF Data Movement Manager is responsible for ensuring that the `nnf-dm-system` is in
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`spec.namespaces`. This is to ensure that the NNF DM Worker pods have global lustre mounted as long
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as `nnf-dm` is deployed. **To unmount global lustre from the NNF DM Worker pods, the
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`lustrefilesystem` resource must be deleted**.
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The `lustrefilesystem` resource itself should be created in the `default` namespace (i.e.
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`metadata.namespace`).
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## NNF Data Movement Manager
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The NNF Data Movement Manager is responsible for monitoring `lustrefilesystem` resources to mount
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(or umount) the global lustre filesystem in each of the NNF DM Worker pods. These pods run on each
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of the NNF nodes. This means with each addition or removal of `lustrefilesystems` resources, the DM
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worker pods restart to adjust their mount points.
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The NNF Data Movement Manager also places a finalizer on the `lustrefilesystem` resource to indicate
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that the resource is in use by Data Movement. This is to prevent the PV/PVC being deleted while they
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are being used by pods.
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## Adding Global Lustre
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As mentioned previously, the NNF Data Movement Manager monitors these resources and automatically
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adds the `nnf-dm-system` namespace to all `lustrefilesystem` resources. Once this happens, a PV/PVC
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is created for the `nnf-dm-system` namespace to access global lustre. The Manager updates the NNF DM
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Worker pods, which are then restarted to mount the global lustre file system.
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## Removing Global Lustre
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When a `lustrefilesystem` is deleted, the NNF DM Manager takes notice and starts to unmount the file
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system from the DM Worker pods - causing another restart of the DM Worker pods. Once this is
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finished, the DM finalizer is removed from the `lustrefilesystem` resource to signal that it is no
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longer in use by Data Movement.
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If a `lustrefilesystem` does not delete, check the finalizers to see what might still be using it.
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It is possible to get into a situation where `nnf-dm` has been undeployed, so there is nothing to
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remove the DM finalizer from the `lustrefilesystem` resource. If that is the case, then manually
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remove the DM finalizer so the deletion of the `lustrefilesystem` resource can continue.

‎docs/guides/index.md

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* [Data Movement Configuration](data-movement/readme.md)
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* [Copy Offload API](data-movement/copy-offload-api.html)
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* [Lustre External MGT](external-mgs/readme.md)
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* [Global Lustre](global-lustre/readme.md)
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## NNF User Containers
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* [User Containers](user-containers/readme.md)
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## Node Management
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* [Draining A Node] (node-management/drain.md)

‎docs/guides/node-management/drain.md

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# Draining A Node
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The NNF software consists of a collection of DaemonSets and Deployments. The pods
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on the Rabbit nodes are usually from DaemonSets. Because of this, the `kubectl drain`
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command is not able to remove the NNF software from a node. See [Safely Drain a Node](https://kubernetes.io/docs/tasks/administer-cluster/safely-drain-node/) for details about
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the limitations posed by DaemonSet pods.
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Given the limitations of DaemonSets, the NNF software will be drained by using taints,
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as described in
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[Taints and Tolerations](https://kubernetes.io/docs/concepts/scheduling-eviction/taint-and-toleration/).
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## Drain NNF Pods From A Rabbit Node
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Drain the NNF software from a node by applying the `cray.nnf.node.drain` taint.
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The CSI driver pods will remain on the node to satisfy any unmount requests from k8s
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as it cleans up the NNF pods.
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```shell
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kubectl taint node $NODE cray.nnf.node.drain=true:NoSchedule cray.nnf.node.drain=true:NoExecute
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```
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To restore the node to service, remove the `cray.nnf.node.drain` taint.
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```shell
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kubectl taint node $NODE cray.nnf.node.drain-
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```
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## The CSI Driver
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While the CSI driver pods may be drained from a Rabbit node, it is advisable not to do so.
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**Warning** K8s relies on the CSI driver to unmount any filesystems that may have
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been mounted into a pod's namespace. If it is not present when k8s is attempting
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to remove a pod then the pod may be left in "Terminating" state. This is most
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obvious when draining the `nnf-dm-worker` pods which usually have filesystems
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mounted in them.
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Drain the CSI driver pod from a node by applying the `cray.nnf.node.drain.csi`
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taint.
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```shell
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kubectl taint node $NODE cray.nnf.node.drain.csi=true:NoSchedule cray.nnf.node.drain.csi=true:NoExecute
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```
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To restore the CSI driver pods to that node, remove the `cray.nnf.node.drain.csi` taint.
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```shell
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kubectl taint node $NODE cray.nnf.node.drain.csi-
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```
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This taint will also drain the remaining NNF software if has not already been
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drained by the `cray.nnf.node.drain` taint.

‎docs/guides/rbac-for-users/readme.md

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After the keys have been generated, a new kubeconfig file can be created for the "flux" user, similar to the one for the "hpe" user above. Again, substitute "flux" in place of "hpe".
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### Apply the provided ClusterRole and create a ClusterRoleBinding
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### Use the provided ClusterRole and create a ClusterRoleBinding
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DataWorkflowServices has already defined the role to be used with WLMs. Simply apply the `workload-manager` ClusterRole from DataWorkflowServices to the system:
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DataWorkflowServices has already defined the role to be used with WLMs, named `dws-workload-manager`:
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```console
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kubectl apply -f https://github.com/DataWorkflowServices/dws/raw/master/config/rbac/workload_manager_role.yaml
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kubectl get clusterrole dws-workload-manager
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```
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Create and apply a ClusterRoleBinding to associate the "flux" user with the `workload-manager` ClusterRole:
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Create and apply a ClusterRoleBinding to associate the "flux" user with the `dws-workload-manager` ClusterRole:
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ClusterRoleBinding
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```yaml

‎docs/guides/storage-profiles/readme.md

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$ kubectl patch nnfstorageprofile durable -n nnf-system --type merge -p '{"data":{"default":false}}'
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```
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# Creating The Initial Default Profile
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Create the initial default profile from scratch or by using the [NnfStorageProfile/template](https://github.com/NearNodeFlash/nnf-sos/blob/master/config/examples/nnf_v1alpha1_nnfstorageprofile.yaml) resource as a template. If `nnf-deploy` was used to install nnf-sos then the default profile described below will have been created automatically.
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To use the `template` resource begin by obtaining a copy of it either from the nnf-sos repo or from a live system. To get it from a live system use the following command:
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```shell
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kubectl get nnfstorageprofile -n nnf-system template -o yaml > profile.yaml
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```
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Edit the `profile.yaml` file to trim the metadata section to contain only a name and namespace. The namespace must be left as nnf-system, but the name should be set to signify that this is the new default profile. In this example we will name it `default`. The metadata section will look like the following, and will contain no other fields:
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```yaml
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metadata:
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name: default
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namespace: nnf-system
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```
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Mark this new profile as the default profile by setting `default: true` in the data section of the resource:
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```yaml
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data:
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default: true
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```
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Apply this resource to the system and verify that it is the only one marked as the default resource:
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```shell
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kubectl get nnfstorageprofile -A
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```
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The output will appear similar to the following:
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```shell
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NAMESPACE NAME DEFAULT AGE
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nnf-system default true 9s
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nnf-system template false 11s
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```
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The administrator should edit the `default` profile to record any cluster-specific settings.
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Maintain a copy of this resource YAML in a safe place so it isn't lost across upgrades.
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## Keeping The Default Profile Updated
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An upgrade of nnf-sos may include updates to the `template` profile. It may be necessary to manually copy these updates into the `default` profile.
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# Profile Parameters
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## XFS

‎docs/repo-guides/release-nnf-sw/readme.md

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## Primer
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This document is based on the process set forth by the [DataWorkflowServices Release
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Process](https://dataworkflowservices.github.io/v0.0.2/repo-guides/create-a-release/readme/).
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Process](https://dataworkflowservices.github.io/latest/repo-guides/create-a-release/readme/).
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Please read that as a background for this document before going any further.
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## Requirements
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|Repo |Update|
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|---------------------|------|
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|`nnf-mfu` |The new version of `nnf-mfu` is referenced by the `NNFMFU` variable in several places:<br><br>`nnf-sos`<br>1. `Makefile` replace `NNFMFU` with `nnf-mfu's` tag.<br><br>`nnf-dm`<br>1. In `Dockerfile` and `Makefile`, replace `NNFMU_VERSION` with the new version.<br>2. In `config/manager/kustomization.yaml`, replace `nnf-mfu`'s `newTag: <X.Y.Z>.`|
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|`nnf-mfu` |The new version of `nnf-mfu` is referenced by the `NNFMFU` variable in several places:<br><br>`nnf-sos`<br>1. `Makefile` replace `NNFMFU` with `nnf-mfu's` tag.<br><br>`nnf-dm`<br>1. In `Dockerfile` and `Makefile`, replace `NNFMU_VERSION` with the new version.<br>2. In `config/manager/kustomization.yaml`, replace `nnf-mfu`'s `newTag: <X.Y.Z>.`<br><br>`nnf-deploy`<br>1. In `config/repositories.yaml` replace `NNFMFU_VERSION` with the new version.|
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|`lustre-fs-operator` |update `config/manager/kustomization.yaml` with the correct version.|
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|`dws` |update `config/manager/kustomization.yaml` with the correct version.|
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|`nnf-sos` |update `config/manager/kustomization.yaml` with the correct version.|
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12. Follow steps 6-7 from the previous section to finalize the release of `nnf-deploy`.
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**Please review documenation for changes you may have made**
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**The software is now released!**
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## Clone a release

‎external/nnf-dm

Submodule nnf-dm updated 187 files

‎mkdocs.yml

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- 'Storage Profiles': 'guides/storage-profiles/readme.md'
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- 'User Containers': 'guides/user-containers/readme.md'
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- 'Lustre External MGT': 'guides/external-mgs/readme.md'
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- 'Global Lustre': 'guides/global-lustre/readme.md'
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- 'Draining A Node': 'guides/node-management/drain.md'
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- 'RFCs':
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- rfcs/index.md
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- 'Rabbit Request For Comment Process': 'rfcs/0001/readme.md'

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