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This guide demonstrates how to vertically scale a PostgreSQL cluster managed by KubeBlocks by adjusting compute resources (CPU and memory) while maintaining the same number of replicas.
Vertical scaling modifies compute resources (CPU and memory) for PostgreSQL instances while maintaining replica count. Key characteristics:
KubeBlocks orchestrates scaling with minimal impact:
Updating
to Running
Before proceeding, ensure the following:
kubectl create ns demo
namespace/demo created
KubeBlocks uses a declarative approach for managing PostgreSQL clusters. Below is an example configuration for deploying a PostgreSQL cluster with 2 replicas (1 primary, 1 replicas).
Apply the following YAML configuration to deploy the cluster:
apiVersion: apps.kubeblocks.io/v1
kind: Cluster
metadata:
name: pg-cluster
namespace: demo
spec:
terminationPolicy: Delete
clusterDef: postgresql
topology: replication
componentSpecs:
- name: postgresql
serviceVersion: 16.4.0
labels:
apps.kubeblocks.postgres.patroni/scope: pg-cluster-postgresql
disableExporter: true
replicas: 2
resources:
limits:
cpu: "0.5"
memory: "0.5Gi"
requests:
cpu: "0.5"
memory: "0.5Gi"
volumeClaimTemplates:
- name: data
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 20Gi
Monitor the cluster status until it transitions to the Running state:
kubectl get cluster pg-cluster -n demo -w
Expected Output:
NAME CLUSTER-DEFINITION TERMINATION-POLICY STATUS AGE
pg-cluster postgresql Delete Creating 50s
pg-cluster postgresql Delete Running 4m2s
Once the cluster status becomes Running, your PostgreSQL cluster is ready for use.
If you are creating the cluster for the very first time, it may take some time to pull images before running.
Expected Workflow:
Updating
to Running
Option 1: Using VerticalScaling OpsRequest
Apply the following YAML to scale up the resources for the postgresql component:
apiVersion: operations.kubeblocks.io/v1alpha1
kind: OpsRequest
metadata:
name: pg-cluster-vscale-ops
namespace: demo
spec:
clusterName: pg-cluster
type: VerticalScaling
verticalScaling:
- componentName: postgresql
requests:
cpu: '1'
memory: 1Gi
limits:
cpu: '1'
memory: 1Gi
What Happens During Vertical Scaling?
You can check the progress of the scaling operation with the following command:
kubectl -n demo get ops pg-cluster-vscale-ops -w
Expected Result:
NAME TYPE CLUSTER STATUS PROGRESS AGE
pg-cluster-vscale-ops VerticalScaling pg-cluster Running 0/2 52s
pg-cluster-vscale-ops VerticalScaling pg-cluster Running 1/2 64s
pg-cluster-vscale-ops VerticalScaling pg-cluster Running 2/2 2m6s
pg-cluster-vscale-ops VerticalScaling pg-cluster Running 2/2 2m6s
pg-cluster-vscale-ops VerticalScaling pg-cluster Succeed 2/2 2m6s
Option 2: Direct Cluster API Update
Alternatively, you may update spec.componentSpecs.resources
field to the desired resources for vertical scale.
apiVersion: apps.kubeblocks.io/v1
kind: Cluster
metadata:
name: pg-cluster
namespace: demo
spec:
terminationPolicy: Delete
clusterDef: postgresql
topology: replication
componentSpecs:
- name: postgresql
serviceVersion: 16.4.0
labels:
apps.kubeblocks.postgres.patroni/scope: pg-cluster-postgresql
disableExporter: true
replicas: 2
resources:
requests:
cpu: "1" # Update the resources to your need.
memory: "1Gi" # Update the resources to your need.
limits:
cpu: "1" # Update the resources to your need.
memory: "1Gi" # Update the resources to your need.
volumeClaimTemplates:
- name: data
spec:
storageClassName: ""
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 20Gi
Planning:
Execution:
Post-Scaling:
Verify the updated resources by inspecting the cluster configuration or Pod details:
kbcli cluster describe pg-cluster -n demo
Expected Output:
Resources Allocation:
COMPONENT INSTANCE-TEMPLATE CPU(REQUEST/LIMIT) MEMORY(REQUEST/LIMIT) STORAGE-SIZE STORAGE-CLASS
postgresql 1 / 1 1Gi / 1Gi data:20Gi standard
To remove all created resources, delete the PostgreSQL cluster along with its namespace:
kubectl delete cluster pg-cluster -n demo
kubectl delete ns demo
In this guide, you learned how to:
Vertical scaling is a powerful tool for optimizing resource utilization and adapting to changing workload demands, ensuring your PostgreSQL cluster remains performant and resilient.