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Cloud computing

Compute on OVHcloud: Public Cloud instances and Managed Kubernetes Service

Choose and use OVHcloud compute: instance ranges (General Purpose, CPU, RAM, GPU, Discovery), images and cloud-init, snapshots, Managed Kubernetes Service (MKS) with node pools and scaling, and integration with the other universes.

1. Instances #

OpenStack VMs.

Ranges #

RangeUsage
General Purpose (b3)Applications, web servers
CPU (c3)Intensive computing
RAM (r3)Databases, caches
GPU (t1, t2, l4, l40s, h100…)AI, rendering
Discovery (d2)Tests, small needs
cat > init.yaml <<'EOF'
#cloud-config
package_update: true
packages: [nginx]
EOF
openstack server create --flavor b3-8 --image "Ubuntu 24.04" --network prive --key-name ma-cle --user-data init.yaml web-1
openstack server image create --name web-1-snap web-1     # instantané
openstack server list --long

2. Managed Kubernetes Service #

Kubernetes without managing the control plane.

Principles #

OVHcloud Managed Kubernetes Service
Node pools are sized automatically according to the load.
  • Managed, free control plane; only nodes are billed.
  • Node pools per range, with autoscaling and anti-affinity.
  • Automatic integration with the private network (vRack), Load Balancer and Block Storage volumes (CSI).
  • Version upgrades scheduled by the user.
kubectl --kubeconfig kubeconfig.yml get nodes -o wide
kubectl get nodepools.kube.cloud.ovh.com            # pools de nœuds (CRD OVHcloud)
kubectl create deployment web --image=nginx --replicas=3
kubectl expose deployment web --port=80 --type=LoadBalancer
kubectl get svc web -w                              # attendre l'IP publique

3. Choosing #

Instances, Kubernetes or other universes.

Guide #

NeedChoice
Classic application, a few serversInstances + Load Balancer
Microservices, containersManaged Kubernetes Service
Raw performance, licensing, physical isolationBare Metal (connected via vRack)
Existing VMware virtualizationHosted Private Cloud

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