Fault-Tolerant AI Pipelines with Rook-Ceph Object Storage on Kubernetes

Question

Pulumi · Accepted Answer

Building fault-tolerant AI pipelines with Rook-Ceph Object Storage on Kubernetes involves setting up a resilient storage system that can handle the demands of AI workload and data management. To achieve this, we will use Rook to orchestrate the deployment of Ceph, a distributed object, block, and file storage platform on a Kubernetes cluster.

Rook is an open-source cloud-native storage orchestrator for Kubernetes, providing the platform, framework, and support for a diverse set of storage solutions to natively integrate with cloud-native environments.

Ceph is a highly scalable and resilient storage solution that will provide the underlying storage required by AI pipelines. It offers three types of storage: object, block, and file, which can be consumed by applications like databases, AI models, backup systems, and more.

For the sake of this guide, the assumption is that you have a Kubernetes cluster already up and running. The program does not cover the Kubernetes cluster setup itself but focuses on setting up Rook-Ceph Object Storage within a Kubernetes cluster.

Here's a basic Pulumi program written in Python that demonstrates how to deploy Rook-Ceph Object Storage on a Kubernetes cluster:

```python
import pulumi
import pulumi_kubernetes as k8s

# Assuming a Kubernetes cluster is already set up and the `kubeconfig` is configured.

# We will start by deploying the Rook operator, which will manage the lifecycle of Ceph within our cluster.
rook_operator = k8s.yaml.ConfigFile("rookOperator",
    file="https://raw.githubusercontent.com/rook/rook/master/cluster/examples/kubernetes/ceph/operator.yaml"
)

# Next, we need to create a Rook Ceph cluster.
# This resource definition should be in a file named 'cluster.yaml' located in your working directory.
ceph_cluster = k8s.yaml.ConfigFile("cephCluster",
    file="cluster.yaml",
    opts=pulumi.ResourceOptions(depends_on=[rook_operator])
)

# Once the Rook-Ceph cluster is set up, we can define a CephBlockPool.
# Below is an example definition for a `CephBlockPool`. You could define the spec
# based on your specific requirements for replication and failure domains.
ceph_block_pool = k8s.apiextensions.CustomResource("cephBlockPool",
    api_version="ceph.rook.io/v1",
    kind="CephBlockPool",
    metadata={
        "name": "replicapool",
        "namespace": "rook-ceph" # Assuming rook-ceph is the namespace used for the cluster
    },
    spec={
        "replicated": {
            "size": 3  # Set the replication size to 3 for fault-tolerance
        }
    },
    opts=pulumi.ResourceOptions(depends_on=[ceph_cluster])
)

# To allow access to the Ceph storage, we need to create a storage class
# that refers to the CephBlockPool we just created.
ceph_storage_class = k8s.storage.v1.StorageClass("cephStorageClass",
    metadata={
        "name": "rook-ceph-block"
    },
    provisioner="rook-ceph.rbd.csi.ceph.com",
    parameters={
        "pool": "replicapool",
        "clusterID": "rook-ceph", # Ensure this matches the namespace of Rook
        "csi.storage.k8s.io/provisioner-secret-name": "rook-csi-rbd-provisioner",
        "csi.storage.k8s.io/provisioner-secret-namespace": "rook-ceph",
        "csi.storage.k8s.io/controller-expand-secret-name": "rook-csi-rbd-provisioner",
        "csi.storage.k8s.io/controller-expand-secret-namespace": "rook-ceph",
        "csi.storage.k8s.io/fstype": "ext4"
    },
    reclaim_policy="Retain",
    allow_volume_expansion=True,
    opts=pulumi.ResourceOptions(depends_on=[ceph_block_pool])
)

# Exporting the storage class name for easier access when creating persistent volume claims
pulumi.export("storageClassName", ceph_storage_class.metadata["name"])
```

Before deploying, save your resource definitions for the Rook-Ceph Cluster (usually named `cluster.yaml`) with specifications tailored to your needs according to Rook-Ceph's documentation.

Pulumi will automate the deployment process as defined by the configurations you've laid out. When you run this Pulumi program with `pulumi up`, it will apply the configurations on your Kubernetes cluster, creating the Ceph storage environment.

The `StorageClass` serves as an abstraction layer over the underlying storage, translating the requests for persistent volumes into actual storage provisioned by Ceph. By setting `reclaimPolicy` to `Retain`, we ensure that data persists even after a `PersistentVolumeClaim` is deleted. This is an essential feature for fault-tolerant systems where data durability is crucial.

To consume the storage, applications within your Kubernetes cluster can now simply define `PersistentVolumeClaims` that refer to the `rook-ceph-block` storage class.

This setup will give you a fault-tolerant storage solution that can be used not only by AI pipelines but by other workloads as well that require resilient storage.