使用 CodePipeline 进行部署
使用 AWS CodePipeline 构建自动化发布流水线,编排构建、测试和部署流程
使用 CodePipeline 进行部署 是 CoddyKit 上的免费 Serverless Backend with AWS Lambda & API Gateway 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 Serverless Backend with AWS Lambda & API Gateway 学习路径的一部分,你的进度在网页和 CoddyKit 应用中同步。 Serverless Backend with AWS Lambda & API Gateway 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。
Meet AWS CodePipeline
Welcome! In modern software development, automating releases is key. AWS CodePipeline helps you achieve Continuous Integration and Continuous Delivery (CI/CD) for your applications, including serverless ones.
CodePipeline is a fully managed service that automates your release process. It orchestrates the steps needed to get your code changes from a source repository through various stages and into production.
Why Use CodePipeline?
Automating your deployments with CodePipeline offers several benefits:
- Faster Releases: Deliver new features and bug fixes to users quicker.
- Improved Reliability: Standardized, automated processes reduce human error.
- Consistent Deployments: Ensures every change follows the same path and checks.
- Visibility: Track the status of your releases in real-time.
It acts as the central orchestrator for your serverless CI/CD.
Core Pipeline Stages
A CodePipeline typically consists of several stages, each with one or more actions. The most common stages are:
- Source: Where your code originates (e.g., CodeCommit, GitHub).
- Build: Where your code is compiled, tested, and packaged (e.g., CodeBuild).
- Deploy: Where your application is deployed to AWS resources (e.g., CloudFormation, SAM).
- Test: Where automated tests run to validate the deployed application.
These stages execute in a defined order, creating a workflow.
The Source Stage
The Source stage is the starting point of your pipeline. When you push new code to your repository, CodePipeline detects the change and automatically starts the pipeline.
Common source providers include AWS CodeCommit, GitHub, GitLab, and Amazon S3. For serverless applications, your source typically contains your Lambda code and serverless template (like a SAM template).
The Build Stage with CodeBuild
After the source code is retrieved, it moves to the Build stage. Here, AWS CodeBuild takes over. CodeBuild compiles your code, runs unit tests, and packages your serverless application artifacts.
For a serverless application, this often means creating a deployment package (a .zip file for Lambda) and preparing your AWS Serverless Application Model (SAM) template for deployment.
Buildspec for Serverless Apps
CodeBuild uses a buildspec.yml file in your source repository to define the build commands. Here's a common structure for a Python Lambda with SAM:
version: 0.2
phases:
install:
runtime-versions:
python: 3.9
build:
commands:
- echo "Building SAM application..."
- sam build --template template.yaml --debug
artifacts:
files:
- '**/*'
base-directory: .aws-sam/buildThe Deploy Stage with SAM
The Deploy stage takes the artifacts produced by the build stage and deploys them to your AWS account. For serverless applications, this typically involves AWS CloudFormation, often orchestrated by AWS SAM.
CodePipeline can directly integrate with CloudFormation to execute a SAM template. It uses Change Sets to preview and safely apply infrastructure updates, minimizing risks.
Deployment Action Example
In CodePipeline, a deploy action for a SAM application might look like this (conceptually, configured in the pipeline definition):
- Action Provider: CloudFormation
- Action Mode: REPLACE_ON_FAILURE or CREATE_UPDATE
- Stack Name: YourServerlessAppStack
- Template Path: The path to your SAM template (e.g.,
build-artifact::template.yaml) - Capabilities: CAPABILITY_IAM (required for many serverless deployments)
This tells CodePipeline to update your CloudFormation stack based on the provided template.
Adding a Test Stage
While unit tests run in the Build stage, a dedicated Test stage in CodePipeline allows for broader validation after deployment. This could include:
- Integration tests against the deployed API.
- Smoke tests to ensure basic functionality.
- End-to-end tests for critical user flows.
You can use another CodeBuild project or a Lambda function to execute these tests. If tests fail, the pipeline can stop the deployment.
Pipeline Check
Consider a serverless application deployed with AWS CodePipeline. Which of the following AWS services are commonly integrated into CodePipeline's stages for a typical serverless CI/CD workflow?
CodePipeline Recap
You've learned how AWS CodePipeline orchestrates your serverless application deployments. Key takeaways:
- CodePipeline automates CI/CD from code commit to deployment.
- It uses stages like Source, Build, and Deploy.
- CodeCommit provides the source, CodeBuild performs builds (using
buildspec.yml), and CloudFormation/SAM handles deployments. - Test stages ensure quality before production.
By leveraging CodePipeline, you create robust and repeatable deployment processes for your serverless applications!
常见问题解答
「使用 CodePipeline 进行部署」课时是免费的吗?
是的 — 「使用 CodePipeline 进行部署」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 Serverless Backend with AWS Lambda & API Gateway 课程的其余内容,请升级到 CoddyKit PRO。 Serverless Backend with AWS Lambda & API Gateway 课程共包含 4 节课。
「使用 CodePipeline 进行部署」这节课中我会学到什么?
使用 AWS CodePipeline 构建自动化发布流水线,编排构建、测试和部署流程 你通过在浏览器中直接运行的动手代码来练习 Serverless Backend with AWS Lambda & API Gateway,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 Serverless Backend with AWS Lambda & API Gateway 需要有经验吗?
无需任何先前经验。CoddyKit 上的 Serverless Backend with AWS Lambda & API Gateway 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 CodePipeline 进行部署」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 Serverless Backend with AWS Lambda & API Gateway 课中编写并运行代码吗?
能。每节 Serverless Backend with AWS Lambda & API Gateway 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
- CodeCommit 与 CodeBuild
- 使用 CodePipeline 进行部署
- 自动化无服务器部署
- 使用金丝雀发布与回滚实现安全部署