CoreWeave Static Node Pool Provisioning

Static provisioning allows you to deploy Fuzzball Substrate on pre-existing CoreWeave NodePool resources, rather than using dynamic provisioning where Fuzzball creates nodes on-demand. This approach is useful when you want more control over node lifecycle, need predictable capacity, or want to optimize costs by managing node pools directly.

Prerequisites

Before deploying the CoreWeave static provisioner, ensure you have completed:

1. Requirements - All prerequisites for deploying Fuzzball on CoreWeave
2. Deployment - Operator and FuzzballOrchestrate deployment
3. Initial Configuration - Provisioner and storage configuration
4. Pre-existing CoreWeave NodePool resources in your cluster

Architecture Overview

Static provisioning deploys Fuzzball substrate as DaemonSets on existing CoreWeave nodes:

• One DaemonSet per target: Each target corresponds to a CoreWeave NodePool or node, depending on your node selector.
• Automatic substrate deployment: Substrate pods run on all nodes matching the node selector
• Shared storage: Uses the same CoreWeave shared-vast storage configured from the Fuzzball deployment
• Node provisioner mapping: Each target maps to a Fuzzball node provisioner

Step 1: Create CoreWeave NodePool

Create a CoreWeave NodePool resource for your compute nodes. For example, to create a H100 GPU node pool:

# coreweave-nodepool-gpu.yaml
apiVersion: compute.coreweave.com/v1alpha1
kind: NodePool
metadata:
  name: fuzzball-h100-node-pool
spec:
  computeClass: default
  autoscaling: false
  instanceType: gd-8xh100ib-i128
  targetNodes: 2

Apply the node pool configuration:

$ kubectl apply -f coreweave-nodepool-gpu.yaml

Repeat this process for each node pool type you want.

Step 2: Create Node Provisioners

Define the node provisioners that map to your node pools:

# static-provisioner-definitions.yaml
definitions:
  - id: coreweave-gpu-large
    provisioner: static
    provisionerSpec:
      condition: "true"
      costPerHour: 49.24

Apply the definitions:

$ fuzzball cluster config set static-provisioner-definitions.yaml

Step 3: Install Static Provisioner Helm Chart

The coreweave-substrate-static Helm chart deploys substrate as DaemonSets on your node pools.

Create Values File

Create a values file mapping your targets to NodePool resources:

# static-provisioner-values.yaml
namespace: fuzzball

# Must match your Fuzzball version
imageTag: "<Version />"

# Image pull secret name
imagePullSecretName: "registry-image-credentials"

# Automatically patches CoreWeave NodePools with substrate taint
autopatchNodePools: true

# Define targets - one DaemonSet per target
targets:
  - name: fuzzball-gpu-large
    definitionId: "coreweave-gpu-large"
    nodeSelector:
      compute.coreweave.com/node-pool: "fuzzball-h100-node-pool"

Install the Chart

Install the static provisioner chart:

$ helm upgrade --install fuzzball-substrate-static \
  oci://depot.ciq.com/fuzzball/fuzzball-images/helm/coreweave-substrate-static \
  --namespace fuzzball \
  --version <Version /> \
  --values static-provisioner-values.yaml

Step 4: Verify Static Provisioning Deployment

Check DaemonSets

Verify that DaemonSets were created for each target:

$ kubectl get daemonsets -n fuzzball -l app=fuzzball-substrate-static

Expected output:

NAME                                DESIRED   CURRENT   READY   UP-TO-DATE   AVAILABLE   NODE SELECTOR
substrate-static-fuzzball-gpu-large       2         2       2            2           2   compute.coreweave.com/node-pool=fuzzball-h100-node-pool

Check Substrate Pods

Verify substrate pods are running on your nodes:

$ kubectl get pods -n fuzzball -l app=fuzzball-substrate-static -o wide

Check Fuzzball Scheduler Nodes

Check that Fuzzball recognizes the substrate nodes:

$ fuzzball node list

Configuration Reference

Values File Parameters

Target Configuration

Each target in the targets array supports:

Node Selector Examples

CoreWeave node pool selector:

nodeSelector:
  compute.coreweave.com/node-pool: "your-pool-name"

Instance type selector:

nodeSelector:
  compute.coreweave.com/instance-type: "cd-gp-a192-genoa"

Combining Static and Dynamic Provisioning

You can use both static and dynamic provisioning in the same deployment by defining both types of provisioners:

definitions:
  # Static provisioner
  - id: coreweave-gpu-large
    provisioner: static
    provisionerSpec:
      condition: "true"
      costPerHour: 49.24

  # Dynamic provisioner
  - id: coreweave-cpu-dynamic
    provisioner: coreweave
    provisionerSpec:
      instanceType: "cd-gp-a192-genoa"
      costPerHour: 7.78

Workflows can then choose which provisioner to use based on their requirements.

Upgrading Static Substrate

To upgrade Substrate on static nodes:

1. Update the imageTag in your values file
2. Run helm upgrade with the new values
3. The DaemonSet will perform a rolling update

$ helm upgrade fuzzball-substrate-static \
  oci://depot.ciq.com/fuzzball/fuzzball-images/helm/coreweave-substrate-static \
  --namespace fuzzball \
  --version <Version /> \
  --values static-provisioner-values.yaml

Scaling Static NodePools

Scale CoreWeave NodePool resources by updating the targetNodes field:

$ kubectl patch nodepool fuzzball-cpu-node-pool -n tenant-your-tenant-id \
  --type merge -p '{"spec":{"targetNodes":5}}'

This scales the node pool to 5 nodes. The Substrate DaemonSet will automatically deploy or remove pods as nodes are added or removed.