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Prepare Linux for Edge Volumes (preview)

  • Artiklu

The article describes how to prepare Linux for Edge Volumes using AKS enabled by Azure Arc, Edge Essentials, or Ubuntu.

Note

The minimum supported Linux kernel version is 5.1. At this time, there are known issues with 6.4 and 6.2.

Prerequisites

Note

Azure Container Storage enabled by Azure Arc is only available in the following regions: East US, East US 2, West US, West US 2, West US 3, North Europe, West Europe.

Uninstall previous instance of Azure Container Storage enabled by Azure Arc extension

If you previously installed a version of Azure Container Storage enabled by Azure Arc earlier than 2.1.0-preview, you must uninstall that previous instance in order to install the newer version. If you installed the 1.2.0-preview release or earlier, use these instructions. Versions after 2.1.0-preview are upgradeable and do not require this uninstall.

  1. In order to delete the old version of the extension, the Kubernetes resources holding references to old version of the extension must be cleaned up. Any pending resources can delay the clean-up of the extension. There are at least two ways to clean up these resources: either using kubectl delete <resource_type> <resource_name>, or by "unapplying" the YAML files used to create the resources. The resources that need to be deleted are typically the pods, the PVC referenced, and the subvolume CRD (if Cloud Ingest Edge Volume was configured). Alternatively, the following four YAML files can be passed to kubectl delete -f using the following commands in the specified order. These variables must be updated with your information:

    • YOUR_DEPLOYMENT_FILE_NAME_HERE: Add your deployment file names. In the example in this article, the file name used was deploymentExample.yaml. If you created multiple deployments, each one must be deleted on a separate line.
    • YOUR_PVC_FILE_NAME_HERE: Add your Persistent Volume Claim file names. In the example in this article, if you used the Cloud Ingest Edge Volume, the file name used was cloudIngestPVC.yaml. If you used the Local Shared Edge Volume, the file name used was localSharedPVC.yaml. If you created multiple PVCs, each one must be deleted on a separate line.
    • YOUR_EDGE_SUBVOLUME_FILE_NAME_HERE: Add your Edge subvolume file names. In the example in this article, the file name used was edgeSubvolume.yaml. If you created multiple subvolumes, each one must be deleted on a separate line.
    • YOUR_EDGE_STORAGE_CONFIGURATION_FILE_NAME_HERE: Add your Edge storage configuration file name here. In the example in this article, the file name used was edgeConfig.yaml.
    kubectl delete -f "<YOUR_DEPLOYMENT_FILE_NAME_HERE.yaml>"
kubectl delete -f "<YOUR_PVC_FILE_NAME_HERE.yaml>"   
kubectl delete -f "<YOUR_EDGE_SUBVOLUME_FILE_NAME_HERE.yaml>"
kubectl delete -f "<YOUR_EDGE_STORAGE_CONFIGURATION_FILE_NAME_HERE.yaml>"

  2. After you delete the files for your deployments, PVCs, Edge subvolumes, and Edge storage configuration from the previous step, you can uninstall the extension using the following command. Replace YOUR_RESOURCE_GROUP_NAME_HERE, YOUR_CLUSTER_NAME_HERE, and YOUR_EXTENSION_NAME_HERE with your respective information:

    az k8s-extension delete --resource-group YOUR_RESOURCE_GROUP_NAME_HERE --cluster-name YOUR_CLUSTER_NAME_HERE --cluster-type connectedClusters --name YOUR_EXTENSION_NAME_HERE

Arc-connected Kubernetes cluster

These instructions assume that you already have an Arc-connected Kubernetes cluster. To connect an existing Kubernetes cluster to Azure Arc, see these instructions.

If you want to use Azure Container Storage enabled by Azure Arc with Azure IoT Operations, follow the instructions to create a cluster for Azure IoT Operations.

Single-node and multi-node clusters

A single-node cluster is commonly used for development or testing purposes due to its simplicity in setup and minimal resource requirements. These clusters offer a lightweight and straightforward environment for developers to experiment with Kubernetes without the complexity of a multi-node setup. Additionally, in situations where resources such as CPU, memory, and storage are limited, a single-node cluster is more practical. Its ease of setup and minimal resource requirements make it a suitable choice in resource-constrained environments.

However, single-node clusters come with limitations, mostly in the form of missing features, including their lack of high availability, fault tolerance, scalability, and performance.

A multi-node Kubernetes configuration is typically used for production, staging, or large-scale scenarios because of features such as high availability, fault tolerance, scalability, and performance. A multi-node cluster also introduces challenges and trade-offs, including complexity, overhead, cost, and efficiency considerations. For example, setting up and maintaining a multi-node cluster requires extra knowledge, skills, tools, and resources (network, storage, compute). The cluster must handle coordination and communication among nodes, leading to potential latency and errors. Additionally, running a multi-node cluster is more resource-intensive and is costlier than a single-node cluster. Optimization of resource usage among nodes is crucial for maintaining cluster and application efficiency and performance.

In summary, a single-node Kubernetes cluster might be suitable for development, testing, and resource-constrained environments. A multi-node cluster is more appropriate for production deployments, high availability, scalability, and scenarios in which distributed applications are a requirement. This choice ultimately depends on your specific needs and goals for your deployment.

Minimum hardware requirements

Single-node or 2-node cluster

  • Standard_D8ds_v5 VM recommended
  • Equivalent specifications per node:
    • 4 CPUs
    • 16 GB RAM

Multi-node cluster

  • Standard_D8as_v5 VM recommended
  • Equivalent specifications per node:
    • 8 CPUs
    • 32 GB RAM

32 GB RAM serves as a buffer; however, 16 GB RAM should suffice. Edge Essentials configurations require 8 CPUs with 10 GB RAM per node, making 16 GB RAM the minimum requirement.

Minimum storage requirements

Edge Volumes requirements

When you use the fault tolerant storage option, Edge Volumes allocates disk space out of a fault tolerant storage pool, which is made up of the storage exported by each node in the cluster.

The storage pool is configured to use 3-way replication to ensure fault tolerance. When an Edge Volume is provisioned, it allocates disk space from the storage pool, and allocates storage on 3 of the replicas.

For example, in a 3-node cluster with 20 GB of disk space per node, the cluster has a storage pool of 60 GB. However, due to replication, it has an effective storage size of 20 GB.

When an Edge Volume is provisioned with a requested size of 10 GB, it allocates a reserved system volume (statically sized to 1 GB) and a data volume (sized to the requested volume size, for example 10 GB). The reserved system volume consumes 3 GB (3 x 1 GB) of disk space in the storage pool, and the data volume consumes 30 GB (3 x 10 GB) of disk space in the storage pool, for a total of 33 GB.

Cache Volumes requirements

Cache Volumes requires at least 4 GB per node of storage. For example, if you have a 3-node cluster, you need at least 12 GB of storage.

Next steps