This is useful if you have a huge CloudFormation stack with multiple Lambda functions using the same code artifact but you don't want to re-deploy the whole stack just because you've added one line in a Lambda function. Use this to quickly upload a new version of your function's code.
- Before you use lambda-updater, make sure that your AWS CLI is installed and configured.
- Before you use lambda-updater, make sure that your CloudFormation stack exists, i.e. you've successfully deployed it at least once.
npm install -g lambda-updater
yarn global add lambda-updater
lambda-updater \ --cfn cfn.yml \ --stack java-starter \ --target target/target.jar \ --functionName JavaExampleFunction \ --useS3 shesse-lambdas
After that, just use the following command and all Java or NodeJS functions from your CloudFormation template get updated:
lambda-updater --cfn path --stack stack-name --target jsOrJarFile [--functionName name] [--useS3 bucketName] [--debug]
--cfn the relative path to your CloudFormation template
--stack the stack name for your CloudFormation template
--target a path to the JS or JAR file containing all your function code; just the functions matching the target type will be updated (might be useful if you're using Java and NodeJS functions in one project)
--functionName optional: if you just want to update one single function, provide the logical function name (= resource id in your CloudFormation template)
--useS3 optional: pass a bucket name and your target file will be uploaded to S3 first. This is useful and faster if your artifact file is quite large for a Lambda function (> 10MB). Target file will be uploaded to [LAMBDA_BUCKET]/_lambda-updater/[FILENAME]. Please consider the limitations on this approach.
--debug optional: prints out some further debug logs.
The logical function name is what you define in your CloudFormation template. Example:
AWSTemplateFormatVersion: '2010-09-09' Resources: YourLogicalFunctionName: Type: AWS::Serverless::Function Properties: # ...
If you have a function defined in your template which hasn't been deployed yet, it will be ignored and of course not updated. In this case there might be a different amount of functions in the logs which have been found and which actually have been updated.
Copyright (c) 2017 Sebastian Hesse
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