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使用 Kubernetes 持续部署实现自动化部署

设置持续部署流水线，自动将应用的新版本部署到 Kubernetes 集群。

第 2 / 4 课11 个步骤

使用 Kubernetes 持续部署实现自动化部署 是 CoddyKit 上的免费 Docker & Kubernetes for Developers 课时。 这是第 2 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Docker & Kubernetes for Developers 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Docker & Kubernetes for Developers 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

What is Continuous Deployment?

After building and testing your code, the next step is getting it to users. Continuous Deployment (CD) automates this entire process, from code commit to production deployment, without human intervention.

It's the natural evolution of Continuous Integration (CI), where every successful build that passes all tests is automatically released.

Benefits of Automated K8s CD

Manually deploying to Kubernetes can be complex and error-prone. Automating deployments brings significant advantages:

  • Speed: New features reach users faster.
  • Consistency: Deployments are identical every time.
  • Reliability: Reduces human errors in complex K8s operations.
  • Scalability: Manages deployments across many services and clusters.

A Typical K8s CD Workflow

A basic Continuous Deployment pipeline for Kubernetes usually follows these stages:

  1. Code Commit: Developer pushes code to Git.
  2. CI (Build & Test): Automated build, tests run, Docker image created.
  3. Image Push: New Docker image pushed to a container registry (e.g., Docker Hub).
  4. K8s Manifest Update: Deployment manifest updated with the new image tag.
  5. Apply to Cluster: The updated manifest is applied to the Kubernetes cluster.

How Kubernetes Updates Work

In Kubernetes, you update an application by changing its Deployment manifest. The most common change is updating the Docker image tag to a newer version.

Kubernetes then intelligently manages the transition from the old version to the new one, ensuring your application remains available.

Deployment Manifest Update

Here's a simplified Kubernetes Deployment manifest. To update your application, you simply change the image tag (e.g., from v1.0.0 to v1.0.1) and apply the updated manifest.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app-deployment
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      containers:
      - name: my-app-container
        image: myregistry/my-app:v1.0.0 # Change this tag!
        ports:
        - containerPort: 80

Zero-Downtime Rolling Updates

Kubernetes uses a rolling update strategy by default. When you update a Deployment, it:

  • Gradually replaces old Pods with new ones.
  • Ensures a minimum number of Pods are always running.
  • Avoids downtime by not taking all old Pods down simultaneously.

This ensures a smooth transition to your new application version.

Health Checks for Reliability

For automated deployments, liveness and readiness probes are crucial:

  • Liveness Probe: Tells Kubernetes if your application is still running. If it fails, Kubernetes restarts the Pod.
  • Readiness Probe: Tells Kubernetes if your application is ready to serve traffic. New Pods won't receive traffic until this probe passes.

These prevent unhealthy versions from taking user requests.

Dealing with Failed Deployments

Even with automation, issues can arise. Kubernetes tracks deployment history, allowing for easy rollbacks:

  • If a new version is buggy, you can quickly revert to a previous, stable version.
  • The command kubectl rollout undo deployment/my-app-deployment can revert to the last successful deployment.

This capability is a safety net for CD.

Popular CD Tools Integration

Many CI/CD tools can automate Kubernetes deployments. They often integrate by:

  • Running kubectl commands in pipeline scripts.
  • Using Kubernetes APIs directly.

Examples include Jenkins, GitLab CI/CD, GitHub Actions, and CircleCI. These tools orchestrate the steps from image build to K8s deployment.

Deployment Update Quiz

You've pushed a new Docker image of your application to your registry. What is the most common and direct way to trigger an update for an existing Kubernetes Deployment to use this new image?

在交互式课程中回答

CD to Kubernetes: Recap

In this lesson, we explored Continuous Deployment (CD) for Kubernetes. You learned:

  • CD automates application releases.
  • How K8s manages updates using rolling updates.
  • The importance of probes and rollbacks.
  • How CI/CD tools integrate with Kubernetes for automation.

Next, we'll dive deeper into GitOps, a powerful methodology for K8s CD.

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常见问题解答

「使用 Kubernetes 持续部署实现自动化部署」课时是免费的吗？

是的 — 「使用 Kubernetes 持续部署实现自动化部署」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Docker & Kubernetes for Developers 课程的其余内容，请升级到 CoddyKit PRO。 Docker & Kubernetes for Developers 课程共包含 4 节课。

「使用 Kubernetes 持续部署实现自动化部署」这节课中我会学到什么？

设置持续部署流水线，自动将应用的新版本部署到 Kubernetes 集群。 你通过在浏览器中直接运行的动手代码来练习 Docker & Kubernetes for Developers，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Docker & Kubernetes for Developers 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Docker & Kubernetes for Developers 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 2 节课，共 4 节。

「使用 Kubernetes 持续部署实现自动化部署」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Docker & Kubernetes for Developers 课中编写并运行代码吗？

能。每节 Docker & Kubernetes for Developers 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

  1. 将 Docker 集成到持续集成流水线
  2. 使用 Kubernetes 持续部署实现自动化部署
  3. Kubernetes 的 GitOps 简介
  4. 使用 Helm Chart 管理 Kubernetes 清单
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