自动化无服务器部署

Welcome to the final lesson on CI/CD for serverless applications! We've covered source control, building, and pipeline orchestration.

Today, we'll focus on the crucial last step: automating the deployment of your serverless applications to AWS.

Automated deployments are essential for modern serverless development. They bring several key benefits:

• Speed: Deploy new features or bug fixes rapidly.
• Consistency: Ensure every deployment follows the same process, reducing human error.
• Reliability: Integrate with testing to deploy only validated code.
• Rollback: Quickly revert to a previous working version if issues arise.

This ensures your users always get a stable and up-to-date experience.

Serverless deployments heavily rely on Infrastructure as Code (IaC). This means defining your AWS resources (like Lambda functions, API Gateways, DynamoDB tables) in code.

The two main IaC tools we use for serverless on AWS are AWS CloudFormation and AWS Serverless Application Model (SAM).

SAM is an extension of CloudFormation, making it easier to define serverless resources.

A SAM template describes your serverless application. When deployed, SAM translates this into CloudFormation, which then provisions your AWS resources.

Here's a minimal SAM template for a simple Lambda function:

The sam deploy command is what you'd typically run from your local machine to deploy a SAM application. In a CI/CD pipeline, CodeBuild will execute this or a similar CloudFormation command.

It takes your packaged application (often a .zip file uploaded to S3) and creates/updates a CloudFormation stack.

In AWS CodePipeline, the 'Deploy' stage is where your application gets provisioned onto AWS. This stage typically follows a 'Build' stage where your code is compiled and packaged.

You configure a 'Deploy' action within this stage to use either AWS CloudFormation or directly deploy a SAM template via CloudFormation.

To add a deployment action in CodePipeline:

1. Choose AWS CloudFormation as the Action provider.
2. Set the Action mode to Create or update a stack.
3. Specify the Stack name (e.g., my-prod-app).
4. Provide the Template and Configuration artifacts (output from your Build stage).
5. Define an IAM role that CloudFormation will assume to create resources.

This links your built artifact to the deployment process.

A common CI/CD practice is deploying to different environments (e.g., dev, staging, prod).

You can achieve this by:

• Using different stack names for each environment.
• Passing CloudFormation parameters to override values in your template (e.g., database names, API endpoints).
• Having separate CodePipelines or stages for each environment.

This allows you to test thoroughly before deploying to production.

AWS CloudFormation (and thus SAM) includes built-in rollback capabilities. If a deployment fails (e.g., a resource cannot be created), CloudFormation automatically attempts to revert the stack to its previous stable state.

You can monitor deployment progress directly in the AWS CodePipeline console, CloudFormation console, or via CloudWatch events.

When automating serverless deployments with AWS CodePipeline and SAM/CloudFormation, what is the primary purpose of the 'Deploy' stage?

In this lesson, we learned about automating serverless deployments using AWS CodePipeline with SAM and CloudFormation.

• Automated deployments provide speed, consistency, and reliability.
• Infrastructure as Code (IaC) with SAM/CloudFormation defines your resources.
• The sam deploy command (or CloudFormation actions) provisions resources.
• CodePipeline's 'Deploy' stage uses IaC artifacts to create/update AWS stacks.
• Parameter overrides enable environment-specific deployments.
• CloudFormation provides automatic rollback for failed deployments.

You now have a complete picture of building a CI/CD pipeline for your serverless applications!