Merge 5df97fd into 7c39271

README-SAR.md

@@ -52,7 +52,7 @@ Additionally, you can specify a list of power values at deploy-time in the `Powe
 
 ### Usage in CI/CD pipelines
 
-If you want to run the state machine as part of your continuous integration pipeline and automatically fine-tune your functions at every deployment, you can execute it with the script `execute.sh` (or similar) by providing the following input parameters:
+If you want to run the state machine as part of your continuous integration pipeline and automatically fine-tune your functions at every deployment, you can execute it with the script `scripts/execute.sh` (or similar) by providing the following input parameters:
 
 ```json
 {

README.md

@@ -24,13 +24,15 @@ Last but not least, the state machine will generate a dynamic visualization of a
 
 ## How to deploy the state machine (AWS Serverless Application Repository)
 
-You can find this app in the [Serverless Application Repository](https://serverlessrepo.aws.amazon.com/applications/arn:aws:serverlessrepo:us-east-1:451282441545:applications~aws-lambda-power-tuning) and deploy it with just a few clicks.
+You can find this app in the [Serverless Application Repository](https://serverlessrepo.aws.amazon.com/applications/arn:aws:serverlessrepo:us-east-1:451282441545:applications~aws-lambda-power-tuning) and deploy it with just a few clicks in the AWS Management Console.
+
+You can also integrate the SAR app in your existing CloudFormation stacks - check the `scripts/deploy-sar-app.yml` and `scripts/deploy-sar-app.sh` files for a working reference.
 
 ## How to deploy the state machine (AWS SAM)
 
-In case you want to deploy it "manually", you can run `deploy.sh`.
+In case you want to deploy it "manually", you can run `scripts/deploy.sh`.
 
-The script uses [AWS SAM CLI](https://github.com/awslabs/aws-sam-cli) to create a new CloudFormation stack in your account.
+The script uses the [AWS SAM CLI](https://github.com/awslabs/aws-sam-cli) to create a new CloudFormation stack in your account.
 
 First, install AWS SAM and [configure your AWS credentials](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.html#cli-quick-configuration):
 
@@ -59,13 +61,13 @@ PowerValues='128,512,1024,1536,3008'
 You can finally deploy the serverless app:
 
 ```bash
-$ bash deploy.sh
+$ bash scripts/deploy.sh
 ```
 
 
 ## How to execute the state machine (programmatically)
 
-You can simply customize the input event in `sample-execution-input.json` and then run the `execute.sh` script. It will start a state machine execution, wait for the execution to complete, and then show the execution result in case of success.
+You can customize the input event in `scripts/sample-execution-input.json` and then run the `scripts/execute.sh` script. It will start a state machine execution, wait for the execution to complete, and then show the execution results.
 
 ## How to execute the state machine (web console)
 
@@ -112,7 +114,7 @@ Additionally, you can specify a list of power values at deploy-time in the `Powe
 
 ### Usage in CI/CD pipelines
 
-If you want to run the state machine as part of your continuous integration pipeline and automatically fine-tune your functions at every deployment, you can execute it with the script `execute.sh` (or similar) by providing the following input parameters:
+If you want to run the state machine as part of your continuous integration pipeline and automatically fine-tune your functions at every deployment, you can execute it with the script `scripts/execute.sh` (or similar) by providing the following input parameters:
 
 ```json
 {

scripts/deploy-sar-app.sh

@@ -0,0 +1,9 @@
+# config
+BUCKET_NAME=your-sam-templates-bucket
+STACK_NAME=lambda-power-tuning-app
+
+# package
+sam package --s3-bucket $BUCKET_NAME --template-file deploy-sar.yml --output-template-file packaged-sar.yml
+
+# deploy
+sam deploy --template-file packaged-sar.yml --stack-name $STACK_NAME --capabilities CAPABILITY_AUTO_EXPAND CAPABILITY_IAM

scripts/deploy-sar-app.yml

@@ -0,0 +1,20 @@
+AWSTemplateFormatVersion: '2010-09-09'
+Transform: AWS::Serverless-2016-10-31
+
+Resources:
+
+  PowerTuningApp:
+    Type: AWS::Serverless::Application
+    Properties:
+      Location:
+        ApplicationId: arn:aws:serverlessrepo:us-east-1:451282441545:applications/aws-lambda-power-tuning
+        SemanticVersion: 3.2.0
+
+      # Parameters:
+      #   PowerValues: 128,256,512,1024,1536,3008 # default RAM values
+      #   lambdaResource: '*' # IAM permission (ARN or prefix)
+      #   visualizationURL: https://lambda-power-tuning.show/ # you can use your own visualization URL
+
+Outputs:
+  PowerTuningStateMachine:
+    Value: !GetAtt PowerTuningApp.Outputs.StateMachineARN

execute.sh → scripts/execute.sh

@@ -1,6 +1,6 @@
 # config
 STACK_NAME=lambda-power-tuning
-INPUT=$(cat sample-execution-input.json)  # or use a static string
+INPUT=$(cat scripts/sample-execution-input.json)  # or use a static string
 
 # retrieve state machine ARN
 STATE_MACHINE_ARN=$(aws cloudformation describe-stacks --stack-name $STACK_NAME --query 'Stacks[0].Outputs[?OutputKey==`StateMachineARN`].OutputValue' --output text)
@@ -22,7 +22,7 @@ do
         sleep 1
     elif test "$STATUS" == "FAILED"; then
         # exit if failed
-        echo "The execution failed (check execution logs)"
+        echo -e "\nThe execution failed, you can check the execution logs with the following script:\naws stepfunctions get-execution-history --execution-arn $EXECUTION_ARN"
         break
     else
         # print execution output if succeeded

template.yml

@@ -4,7 +4,7 @@ Transform: AWS::Serverless-2016-10-31
 Metadata:
   AWS::ServerlessRepo::Application:
     Name: aws-lambda-power-tuning
-    Description: AWS Step Functions state machine to optimize Lambda functions
+    Description: "AWS Lambda Power Tuning is an open-source tool that can help you visualize and fine-tune the memory/power configuration of Lambda functions. It runs in your own AWS account - powered by AWS Step Functions - and it supports three optimization strategies: cost, speed, and balanced."
     Author: Alex Casalboni
     SpdxLicenseId: Apache-2.0
     LicenseUrl: LICENSE.txt