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Volcengine Kubernetes Engine

Creating workloads

Creating Deployments

A Deployment in Kubernetes is a workload that never preserves data or maintains state during running. You can create a Deployment in a cluster by using an image. This topic describes how to create a Deployment.

Prerequisites

A container image has been created. You can directly use an image from a third-party repository or upload an image to the Container Registry (CR) service. To upload an image to CR, see Pushing and pulling images.

Creating Deployments in the console

Go to the Deployment page.

In the left navigation bar, click Cluster.

On the Cluster page, click the name of the cluster for which you need to create a Deployment.

In the left navigation bar of the cluster management page, click Workload > Deployment.

On the Deployment page, click Create Deployment.

Configure the Deployment. For parameter details, see Workload configurations.

Click Confirm in the lower-right corner of the page.

Use the kubectl

tip

Before you start, make sure that the following conditions are met:

The kubectl tool has been installed on your on-premises computer. For details, see Installing and configuring kubectl.

The target cluster has been connected through kubectl. For details, see Connecting to clusters.

Create the YAML file of the workload. The code of the sample file deployment-demo.yaml is as follows:

apiVersion: apps/v1
kind: Deployment
metadata:
name: deployment-demo # The Deployment name.
namespace: default # The namespace where the Deployment resides.
spec:
replicas: 2 # The number of Deployment replicas.
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx # The container name.
image: doc-cn-beijing.cr.volces.com/vke/nginx-demo:v1.0 # The container image address and tag.
ports:
- containerPort: 80 # The exposed port number of the container.
resources:
requests: # The container CPU and memory requests.
cpu: "500m"
memory: "1024Mi"
limits: # The resource quotas, such as the CPU limit, memory limit, and number of RDMA cards.
cpu: "1"
memory: "2Gi"
vke.volcengine.com/rdma: 2

Run the following command to create the workload.

kubectl apply -f deployment-demo.yaml

Operation result

After you create the Deployment, you can view the status of the workload on the Workload > Deployment page. You can click the button in the Actions column to manage the created Deployment. For more operations, see Managing workloads.

Last updated: 2026.08.19 17:39:48