I am using CloudFormation with SAM to deploy a stack which contains:
S3 Bucket
Cognito
AWS::Serverless::Api
AWS::Serverless::Function (authorizers + microservices, Type: Api and endpoints of the API Gateway)
Log Groups
To deploy my stack, I first run aws cloudformation package to package the lambda and then run aws cloudformation deploy to deploy the generated stack. This is working.
My goal now is to be able to update a microservice without deploying the entire stack (not building authorizers and other microservices), similar to serverless deploy function in the Serverless framework. This should preferably be one reusable template that uses a macro or just replaces text in the file.
The problem I am facing with this:
Running aws lambda update-function-code requires the lambda to be redeployed
To redeploy the lambda I have to declare AWS::Serverless::Function. For the function to be part of the API Gateway, AWS::Serverless::Api must be declared as well.
Declaring AWS::Serverless::Api requires all the other functions to be defined or they will be removed from the API Gateway.
I feel like I am stuck here and have not found other options of achieving my goal.
Since you're using SAM, I'd recommend deploying and updating your application using the sam cli commands.
You can run
sam build
sam package
sam deploy
When you run sam deploy, it deploys your application, but all subsequent sam deploy commands will update your existing cloudformation stack with only the appropriate resources that need updating.
If you opt for keeping with the standard Cloudformation cli commands, you could use the aws cloudformation update-stack command so that you're not re-deploying an entire new stack.
Related
I want to make two bucket(x,y) in S3 and make a lambda.
My goal is uploading files to S3(x) and it triggers lambda then lambda create and put file in S3(y)
Currently, I am developing lambda function on SAM.
Deploying lambda function by SAM
And I made two S3 buckets by cdk.
Then manually adding trigger and Iam policy to lambda to access S3
However I want to do this all automatically.
So my idea is ,
SAM can make two S3 bucket as stack and I don't need cdk anymore ?
cdk can include SAM development environment?
Any other way??
What is the best practice for this purpose??
My `solution is
Local development with SAM
AWS deployment is carried out by cdk only, SAM doesn't work anything for deployment.
My folder structure is below
cdk / bin
lib
cdk.json
etc
samproj/helloworld/app.py
/samconfig.toml
/template.yaml
/etc
For local developing, in samproj directory, do something like this, tutorial.
sam local invoke "HelloWorldFunction" -e events/event.json
And for AWS deployment by cdk project .
Just make lambda directly from samproj/helloworld directory in Stack.
export class CdkVrBaseStack extends Stack {
const lambda_ = new lambda.Function(this, 'TestLambda', {
functionName: 'testLambda',
runtime: lambda.Runtime.PYTHON_3_9,
code: lambda.Code.fromAsset('samproj/helloworld'),
handler: 'index.handler',
timeout: cdk.Duration.seconds(300),
Which services can be managed by the AWS SAM (Serverless Application Model) framework?
AWS Docs seem to list contradicting information:
https://aws.amazon.com/serverless/ lists plenty of services as serverless, incl. Lambda, Fargate, ..., SNS, SQS, ... DynamoDB, S3.
SAM resource reference lists only: Api, Application, Function, HttpApi, LayerVersion, SimpleTable, StateMachine.
Yet, I cannot find any mention in the SAM docs on how to create an S3 bucket.
An example doubt is - can I have an S3 bucket created using SAM framework?
Can SAM deploy to Fargate too?
You can add any CloudFormation component as part of your SAM config file. As noted in the SAM developer guide:
AWS SAM templates are an extension of AWS CloudFormation templates, with some additional components that make them easier to work with. For the full reference for AWS CloudFormation templates, see AWS CloudFormation Template Reference in the AWS CloudFormation User Guide.
I am using terraform to create all the infra(CodePipeline, lambda, buckets) on AWS
currently, I've created a pipeline that builds the source zip file and puts it on s3 bucket but the lambda still keeps using the older source. So, I update the URL manually in the AWS console and it works.
Now I want to automate the flow but available solutions are:
AWS SAM + CFT
Codebuild Stage to update the source using AWS CLI
Create a lambda that updates the source
Code Deploy + AWS SAM + CFT
I am not willing to use CFT at all since all of our code is in terraform and CFT requires me to create new lambdas instead of using old ones.
is there any other simpler way to update the lambda source through Codepipeline
The preferred way to deploy a Lambda via CodePipeline is using a CloudFormation Deploy action [1]. Since you are not looking to use CloudFormation, next option could be to run your terraform plan/apply commands from within a CodeBuild job that is part of the pipeline. You will need to provide the CodeBuild role required permission for resource creation (or export the credentials in Environment variabels for TF to use via this [2] method) and install the TF binary within install phase of buildspec.
Ref:
[1] Building a Continuous Delivery Pipeline for a Lambda Application with AWS CodePipeline - https://docs.aws.amazon.com/lambda/latest/dg/build-pipeline.html
[2] How to retrieve Secret Manager data in buildspec.yaml
I'm creating a new user pool in AWS Cognito. As you might know, CF support is missing for a lot of the features in Cognito, so I´ve resorted to using the CLI for Cognito. But I still want to use CloudFormation for other resources like API Gateway that will need to reference the new user pool.
Is there any way I can create parameters with the CLI that I can use in CloudFormation?
Yes, if you have Parameters in your template, then you can use the CloudFormation Deploy command to do exactly this.
For example, you can call aws cloudformation deploy --template-file <file_path> --stack-name <stack_name> --parameter-overrides ParameterKey1=ParameterValue1 ParameterKey2=ParameterValue2 ... where <file_path> is the path to your CloudFormation Template, and <stack_name> is the name of your CloudFormation Stack. If this stack doesn't exist yet, Deploy will create it, but if it does exist, Deploy will update it.
I am new to AWS lambda i have i am using serveless deploy to deploy my lambda function declared in serverless.yml file.
In that file i wrote a lambda function i deployed and it is working fine but problem is that whatever environment variable i gave is not available in console of that lambda function. I might be doing some minor mistake or for deploying environment variable there should be some other syntax.
I can go to lambda function in console and add environment variable manually.
But my doubt is can we do it while deploying it through serverless deploy
You can use versions and aliases provided by AWS Lambda
You can create different versions of the same lambda function and give them an alias. Like when you push your lambda code - create a version (say it's 5) - create an alias this (say TEST).
When you're sure that its ready for production, create a version(or choose an existing version and name that (say PROD).
Now whenever your lambda function executes, it gives lambda ARN
which contains alias, by that you can know which alias(in context.invokedFunctionArn) is
executed i.e. that can be used as the environment variable. While
invoking the function, you can mention which function to execute from
your invocation code.
let thisARN = context.invokedFunctionArn;
// Get the last string in ARN - It's either function name or the alias name
let thisAlias = thisARN.split(":").pop();
Now whenever you deploy a new code, just point the alias to that version.
You can use AWS console or CLI for that.
Take a look at this lambda versioning and aliases
For directly deploying to your alias(PROD), you can do this -
aws lambda update-alias \
--region region \
--function-name helloworld \
--function-version 2 \
--name PROD
serverless deploy
Serverless deploy works fine for deployment on any stage it also deploys environment variable in given stage, my case environment variable was not deployed of indentation problem in yaml file, and even serverless deploy command was not throwing error it was deploying function but environment variables were not deployed
In yaml file we can state the the stage where we want to deploy like this
provider:
name: aws
runtime: nodejs6.10
stage: dev
region: eu-west-2
Hope this will help if someone gets similar issue