66 lines
2.8 KiB
Markdown
66 lines
2.8 KiB
Markdown
---
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tags:
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- docker
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- AWS
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---
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# AWS SAM and Docker
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_How would you use docker containers in AWS. How would this integrate with SAM.
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What are the benefits over just deploying from local via SAM_
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Amazon Web Services (AWS) provides several services for running Docker
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containers, such as Amazon Elastic Container Service (ECS) and AWS Fargate. To
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integrate Docker containers with AWS Serverless Application Model (SAM), you can
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use the AWS Lambda container image support feature, which allows you to package
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and deploy Lambda functions as container images.
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Here's a brief overview of how to use Docker containers in AWS with SAM:
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1. Create a Dockerfile for your Lambda function, using one of the AWS-provided
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base images for your preferred runtime (e.g., Python, Node.js, etc.).
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2. Build the Docker image using the docker build command.
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3. Push the Docker image to Amazon Elastic Container Registry (ECR) using the
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docker push command.
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4. In your AWS SAM template (template.yaml), define a Lambda function with the
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ImageUri property pointing to the Docker image stored in ECR.
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5. Deploy the serverless application using the sam deploy command.
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## Benefits of using Docker containers with AWS SAM over deploying from local:
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- Consistency:
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- Packaging your Lambda function as a container image ensures that the
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environment and dependencies are consistent across development, testing, and
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production stages. It eliminates the "it works on my machine" problem.
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- Custom runtimes:
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- AWS Lambda provides a set of pre-defined runtimes, but with container image
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support, you can use custom runtimes, giving you more flexibility and
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control over the execution environment.
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- Easier dependency management:
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- For complex applications with numerous dependencies or large package sizes,
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using container images simplifies dependency management and can help you
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stay within the Lambda package size limits.
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- Reuse of existing Docker workflows:
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- If you already have Docker workflows in place for building, testing, and
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deploying containerized applications, you can easily extend these workflows
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for your Lambda functions, reducing the learning curve and operational
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overhead.
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- Ease of local testing:
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- With AWS SAM CLI, you can test your Lambda functions locally as container
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images, closely mimicking the actual execution environment and reducing the
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chances of unexpected issues when deploying to AWS.
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> While using Docker containers with AWS SAM has its benefits, it may not be
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> suitable for every use case. If your Lambda functions have minimal
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> dependencies and simple execution environments, deploying directly from local
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> using SAM might be more straightforward and faster. However, for more complex
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> applications, using Docker containers can provide better consistency,
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> flexibility, and control over the execution environment.
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