Maintaining Workload Uptime
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This topic describes how you can maintain workload uptime for Kubernetes clusters deployed with Pivotal Container Service (PKS).
To maintain workload uptime, configure the following settings in your deployment manifest:
- Configure workload replicas to handle traffic during rolling upgrades.
- Define an anti-affinity rule to evenly distribute workloads across the cluster.
To increase uptime, you can also refer to the documentation for the services that run on your clusters, and configure your workload based on the recommendations of the software vendor.
The PKS tile contains an errand that upgrades all Kubernetes clusters. Upgrades run on a single VM at a time. While one worker VM runs an upgrade, the workload on that VM goes down. The additional worker VMs continue to run replicas of your workload, maintaining the uptime of your workload.
Note: Ensure that your pods are bound to a ReplicaSet or Deployment. Naked pods are not rescheduled in the event of a node failure. For more information, see Configuration Best Practices in the Kubernetes documentation.
To prevent workload downtime during a cluster upgrade, Pivotal recommends running your workload on at least three worker VMs and using multiple replicas of your workloads spread across those VMs. You must edit your manifest to define the replica set and configure an anti-affinity rule to ensure that the replicas run on separate worker nodes.
Set the number of workload replicas to handle traffic during rolling upgrades. To replicate your workload on additional worker VMs, deploy the workload using a replica set.
spec.replicas value in your deployment manifest:
kind: Deployment metadata: # ... spec: replicas: 3 template: metadata: labels: app: APP-NAME
See the following table for more information about this section of the manifest:
|Set this value to at least 3 to have at least three instances of your workload running at any time.|
|Use this app name when you define the anti-affinity rule later in the spec.|
To distribute your workload across multiple worker VMs, you must use anti-affinity rules. If you do not define an anti-affinity rule, the replicated pods can be assigned to the same worker node. See the Kubernetes documentation for more information about anti-affinity rules.
To define an anti-affinity rule, add the
spec.template.spec.affinity section to your deployment manifest:
kind: Deployment metadata: # ... spec: replicas: 3 template: metadata: labels: app: APP-NAME spec: containers: - name: MY-APP image: MY-IMAGE ports: - containerPort: 12345 affinity: podAntiAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: "app" operator: In values: - APP-NAME topologyKey: "kubernetes.io/hostname"
See the following table for more information:
|This value matches
|This value matches the
Kubernetes evenly spreads pods in a replication controller over multiple Availability Zones (AZs).
For more granular control over scheduling pods, add an
Anti-Affinity Rule to the deployment spec by replacing
For more information on scheduling pods, see Advanced Scheduling in Kubernetes on the Kubernetes Blog.
If an AZ goes down, PersistentVolumes (PVs) and their data also go down and cannot be automatically re-attached. To preserve your PV data in the event of a fallen AZ, your persistent workload needs to have a failover mechanism in place.
Depending on the underlying storage type, PVs are either completely free of zonal information or can have multiple AZ labels attached. Both options enable a PV to travel between AZs.
To ensure the uptime of your PVs during a cluster upgrade, Pivotal recommends that you have at least two nodes per AZ. By configuring your workload as suggested, Kubernetes reschedules pods in the other node of the same AZ while BOSH is performing the upgrade.
For information about configuring PVs in PKS, see Configuring and Using PersistentVolumes.
For information about the supported storage topologies for PKS on vSphere, see PersistentVolume Storage Options on vSphere.
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