updated readme and stack.py file

Author: Emmanuel-AWS

Diff for: xray-lambdalayers-cdk-python/README.md

@@ -2,8 +2,16 @@
 
 # Overview
 
-This CDK example sets up AWS X-Ray for a Lambda function that uses Lambda Layers. The example demonstrates the use of the folder structure for a Lambda layer written in Python, and using constructs for deploying and using the layer and X-Ray.
+This CDK example sets up AWS X-Ray for a Lambda function that uses Lambda Layers. The example demonstrates the use of the folder structure for a Lambda layer written in Python, and using constructs for deploying and using the layer and X-Ray. 
 
+Important: This application uses various AWS services and there are costs associated with these services after the Free Tier usage - please see the [AWS Pricing page](https://aws.amazon.com/pricing/)  for details. You are responsible for any AWS costs incurred. No warranty is implied in this example.
+
+# Requirements
+
+ * [Create an AWS account](https://portal.aws.amazon.com/gp/aws/developer/registration/index.html)  if you do not already have one and log in. The IAM user that you use must have sufficient permissions to make necessary AWS service calls and manage AWS resources.
+ * [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html)  installed and configured
+ * [Git Installed](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
+ * [AWS Cloud Development Kit (AWS CDK)](https://docs.aws.amazon.com/cdk/v2/guide/getting_started.html) (AWS CDK >= 2.1.0) installed
 
 # Python Setup
 
@@ -19,80 +27,95 @@ you can create the virtualenv manually.
 To manually create a virtualenv on MacOS and Linux:
 
 ```
-$ python3 -m venv .venv
+python3 -m venv .venv
 ```
 
 After the init process completes and the virtualenv is created, you can use the following
 step to activate your virtualenv.
 
 ```
-$ source .venv/bin/activate
+source .venv/bin/activate
 ```
 
 If you are a Windows platform, you would activate the virtualenv like this:
 
 ```
-% .venv\Scripts\activate.bat
+.venv\Scripts\activate.bat
 ```
 
 Once the virtualenv is activated, you can install the required dependencies.
 
 ```
-$ pip install -r requirements.txt
+pip install -r requirements.txt
 ```
 To add additional dependencies, for example other CDK libraries, just add
 them to your `setup.py` file and rerun the `pip install -r requirements.txt`
 command. 
 
-At this point you can now synthesize the CloudFormation template for this code.
-
-```
-$ cdk synth
-```
-#CDK deploy
-
-A Lambda layer is a .zip file archive that can contain additional code or data. When deployed, CDK creates a layer .zip asset to be stored in a staging bucket managed by CDK. To enable this the AWS account being used needs to be bootstrapped.
+# How to Run X-Ray on the Lambda function using layers
 
-With default Profile,
+# Deployment Instructutions
+1. Create a new directory, navigate to that directory in a terminal and clone the GitHub repository:
 
 ```
-$ cdk bootstrap
+git clone https://github.com/aws-samples/serverless-patterns
 ```
 
-With specific profile,
+2. Change directory to the pattern directory:
 
 ```
-$ cdk bootstrap --profile test
+cd serverless-patterns/xray-lambdalayers-cdk-python
 ```
-# How to Run X-Ray on the Lambda function using layers
 
-# Deployment Instructutions
-1. Create a [lambda layer](https://docs.aws.amazon.com/cdk/api/latest/python/aws_cdk.aws_lambda/README.html#layers) for AWS X-Ray.
+3. Create a [lambda layer](https://docs.aws.amazon.com/cdk/api/latest/python/aws_cdk.aws_lambda/README.html#layers) for AWS X-Ray.
 To do this we'll install the python dependencies inside this folder: `lambda_layer_x_ray_stack/layers/`:
 
 ```
-pip install aws-xray-sdk -t lambda_layer_x_ray_stack/layers/xray/python/lib/python3.8/site-packages
+pip install aws-xray-sdk -t lambda_layer_x_ray_stack/layers/xray/python
 ```
 
 ```
 pip install boto3 -t lambda_layer_x_ray_stack/layers/boto3/python
 ```
 
+4. Each bucket name has to be globally unique so update the source and resized bucket names by replacing < your-name > with your name and any random digits in the lambda_layer_x_ray_stack_stack.py file. 
+
+5. Update the pillow arn in the lambda_layer_x_ray_stack_stack.py file to the latest version in your region. See [Klayers](https://github.com/keithrozario/Klayers/tree/master/deployments/python3.8/arns) and select your region and the latest pillow package version arn.
+
 ```
-Create a lambda layer from the console and select specify an ARN. Go to [Library ARNS](https://github.com/keithrozario/Klayers/tree/master/deployments/python3.8/arns) and select your region and the latest pillow package version arn. Paste this into the console and click add. 
+layerpillow = lambda_.LayerVersion.from_layer_version_arn(self, 'pillowlayerversion', 'Your_Region_Pillow_ARN')
 ```
 
-2. Deploy application via `cdk`:
+6. Deploy application via `cdk`:
+
+At this point you can now synthesize the CloudFormation template for this code.
 
 ```
 cdk synth
-cdk deploy
 ```
 
+A Lambda layer is a .zip file archive that can contain additional code or data. When deployed, CDK creates a layer .zip asset to be stored in a staging bucket managed by CDK. To enable this the AWS account being used needs to be bootstrapped.
+
+With default Profile,
+
+```
+cdk bootstrap
+```
+
+With specific profile,
+
+```
+cdk bootstrap --profile test
+```
+
+Now we can deploy our stack.
+```
+cdk deploy
+```
 
 # Testing
 
-On the AWS Mangement Console, navigate to the lambda function and invoke it a few times. Go to the AWS X-Ray service and check that a Service Map has been created and is displaying traces. 
+On the AWS Mangement Console, navigate to the source S3 bucket and upload a few images. Go to the AWS X-Ray service and check that a Service Map has been created and is displaying traces. 
 
 
 ## Useful commands
@@ -108,4 +131,4 @@ Enjoy!
 # Documentation 
 
 1. AWS Documentation for using [AWS CDK in Python](https://docs.aws.amazon.com/cdk/latest/guide/work-with-cdk-python.html)
-2. AWS Documentation for using [AWS Lambda with AWS X-Ray](https://docs.aws.amazon.com/lambda/latest/dg/services-xray.html)
+2. AWS Documentation for using [AWS Lambda with AWS X-Ray](https://docs.aws.amazon.com/lambda/latest/dg/services-xray.html)

Diff for: xray-lambdalayers-cdk-python/lambda_layer_x_ray_stack/lambda_layer_x_ray_stack_stack.py

@@ -1,3 +1,4 @@
+from importlib.resources import Package
 from aws_cdk import (
     Stack,
     RemovalPolicy,
@@ -7,7 +8,6 @@
     aws_lambda_event_sources as eventsources
 )
 from constructs import Construct
-from aws_xray_sdk.core.recorder import TRACING_NAME_KEY
 import os
 
 class LambdaLayerXRayStackStack(Stack):
@@ -16,7 +16,7 @@ def __init__(self, scope: Construct, construct_id: str, **kwargs) -> None:
         super().__init__(scope, construct_id, **kwargs)
 
         # Change pillow arn to latest version in your region. See https://github.com/keithrozario/Klayers/tree/master/deployments/python3.8/arns
-        layerpillow = lambda_.LayerVersion.from_layer_version_arn(self, 'pillowlayerversion', 'arn:aws:lambda:us-east-2:770693421928:layer:Klayers-python38-Pillow:14')
+        layerpillow = lambda_.LayerVersion.from_layer_version_arn(self, 'pillowlayerversion', 'Your_Region_Pillow_ARN')
 
          # --------------------------------------------------------
         # Create buckets for thumbnail