Integration Options

Using Layers
Without Layers
Serverless Framework
AWS SAM
AWS CDK
Using Layers
Using Layers
Step 1: Deploy your function to AWS Lambda

Bundle all your Python module files, along with any additional required Python libraries and upload it to the AWS Lambda console using the 'Upload a.zip file' option for the code entry type option. Note that Thundra dependencies are not expected to be in the artifact to be uploaded as it comes with layer that will be mentioned at later steps.
Step 2: Configure your function
Add api key to the environment variables on Amazon Lambda Console
Add thundra layer
 Click on the Layers option on your Lambda function console in the Designer tab. Then select Add Layer button and add Thundra Layer's ARN.
arn:aws:lambda:${region}:269863060030:layer:thundra-lambda-python-layer:${latest-version} 
Latest layer version of thundra python layer
Note that the region part of the ARN is dynamic, so you need to change it according to the region where you deploy your function. So let say that you deploy your Lambda function to Oregon (us-west-2) region, and the layer version is 12. The layer ARN will be:arn:aws:lambda:us-west-2:269863060030:layer:thundra-lambda-python-layer:12
Configure handler
Set handler to thundra.handler.wrapper . Set thundra_agent_lambda_handler environment variable value to to your handler.
Step 3: Invoke your deployed function by clicking on the Test button on the top right
Clicking on the 'Test' button on the top right of the AWS console will result in an invocation of your function after you have configured test data as per the specifications of your function.
Step 4: Monitor your function with Thundra

Upon your first invocation ever, the Next button shall appear in the Invocation Monitor bar below and clicking it shall allow you to see monitoring data from your invocation.

Without Layers
Without Layers
Step 1: Install Thundra’s python package
  On the project directory run following command:
pip3 install thundra -t .
Step 2: Deploy your function to AWS Lambda

Bundle all your Python module files, along with any additional required Python libraries and upload it to the AWS Lambda console using the 'Upload a.zip file' option for the code entry type option. 
Step 3: Configure your function
Add api key to the environment variables on Amazon Lambda Console
Configure handler
Set handler to thundra.handler.wrapper . Set thundra_agent_lambda_handler environment variable value to to your handler.
Step 4: Invoke your deployed function by clicking on the Test button on the top right
Clicking on the 'Test' button on the top right of the AWS console will result in an invocation of your function after you have configured test data as per the specifications of your function.
Step 5: Monitor your function with Thundra

Upon your first invocation ever, the Next button shall appear in the Invocation Monitor bar below and clicking it shall allow you to see monitoring data from your invocation.
Serverless Framework
Serverless Framework
Step 1: Install Thundra’s serverless plugin to automatically wrap your functions
npm install serverless-plugin-thundra
Step 2: Adding Thundra's Serverless Plugin in serverless.yml File

After installing Thundra’s serverless plugin, please specify it as a plugin for your serverless environment by adding it under the plugins section of your serverless.yml file.
serverless.yml
plugins:  
    - serverless-plugin-thundra
Step 3: Add thundra component to custom
 Add the thundra component under custom with apiKey under that, as seen below:
serverless.yml
custom:
    thundra:
        apiKey: <YOUR THUNDRA API KEY>
Step 4: Add thundra_apiKey to environment variables under provider section in serverless.yml 
serverless.yml
provider: 
    environment:
        thundra_apiKey: <YOUR THUNDRA API KEY>
Step 5: Deploy & Test app 
serverless deploy
serverless invoke --function functionName
Step 6: Monitor your function with Thundra

Upon your first invocation ever, the Next button shall appear in the Invocation Monitor bar below and clicking it shall allow you to see monitoring data from your invocation.
AWS SAM
AWS SAM
Step 1: Add configuration changes on SAM template.yml
Add thundra_apiKey environment variable with your thundra api key. 
Globals:
  Function:
	...
    Environment:
      Variables:
          thundra_apiKey: <your_api_key>
Add the Thundra layer to Layers in globals section. ThundraAWSAccountNo and ThundraPythonLayerVersion parameters are defined under the Parameters section in the following configuration:
Latest layer version of thundra python layer:​
Parameters:
  ThundraAWSAccountNo:
    Type: Number
    Default: 269863060030
​
  ThundraPythonLayerVersion:
    Type: Number
    Default: 12 # Or use any other version
​
Globals:
  	...
    Function:
      ...
      Layers:
          - !Sub arn:aws:lambda:${AWS::Region}:${ThundraAWSAccountNo}:layer:thundra-lambda-python-layer:${ThundraPythonLayerVersion}
​
	…
​
Change Handler of functions to be wrapped to thundra.handler.wrapper or set Handler in the Globals section if you want to wrap all of the functions in your SAM configuration file.
Globals:
  Function:
    ...
​
    Handler: thundra.handler.wrapper
​
For each function that is wrapped, add thundra_agent_lambda_handler environment variable with handler path of your function.
Resources:
  HelloWorldFunction1:
    Type: AWS::Serverless::Function
    Properties:
      Environment:
          Variables:
              thundra_agent_lambda_handler: hello_world_1.app.lambda_handler
​
An example configuration:
Parameters:
  ThundraAWSAccountNo:
    Type: Number
    Default: 269863060030
​
  ThundraPythonLayerVersion:
    Type: Number
    Default: 11 # Or use any other version
​
Globals:
  Function:
    Runtime: python3.7
    Timeout: 5
​
    Handler: thundra.handler.wrapper
    Layers:
        - !Sub arn:aws:lambda:${AWS::Region}:${ThundraAWSAccountNo}:layer:thundra-lambda-python-layer:${ThundraPythonLayerVersion}
​
    Environment:
      Variables:
          thundra_apiKey: <your_api_key>
​
Resources:
  HelloWorldFunction1:
    Type: AWS::Serverless::Function
    Properties:
      Environment:
          Variables:
              thundra_agent_lambda_handler: hello_world_1.app.lambda_handler
​
Step 2: Test application 
To build & run your functions locally:
sam build && sam local invoke
Step 3: Monitor your function with Thundra
Upon your first invocation ever, the Next button shall appear in the Invocation Monitor bar below and clicking it shall allow you to see monitoring data from your invocation.


AWS CDK
AWS CDK
Step 1: Apply configuration changes on your function properties.
Add thundra_apiKey environment variable with your thundra api key. 
from aws_cdk import (core,
                     aws_lambda as lambda_)
​
class YourConstructClass(core.Construct):
​
    def __init__(self, scope: core.Construct, id: str):
        super().__init__(scope, id)
​
        thundraApiKey = <your_api_key>
      
        handler = lambda_.Function(self, "YourHandler",
                           ..., # other function properties
                           environment=dict(
                               ..., # other environment variables
                               thundra_apiKey=thundraApiKey)
Define Thundra layer and add it to your function properties. 
Latest layer version of thundra python layer:​
from aws_cdk import (core,
                     aws_lambda as lambda_)
​
​
class YourConstructClass(core.Construct):
​
    def __init__(self, scope: core.Construct, id: str):
        super().__init__(scope, id)
​
        thundraApiKey = <your_api_key>
        thundraAWSAccountNo = 269863060030
        thundraPythonLayerVersion = 31 # or any other version
        thundraPythonLayer = lambda_.LayerVersion.from_layer_version_arn(self, "ThundraLayer",
            "arn:aws:lambda:{}:{}:layer:thundra-lambda-python-layer:{}".format(
                core.Aws.REGION, thundraAWSAccountNo, thundraPythonLayerVersion)),
      
        handler = lambda_.Function(self, "YourHandler",
                           ..., # other function properties
                           environment=dict(
                               ..., # other environment variables
                               thundra_apiKey=thundraApiKey),
                           layers=[
                               thundraPythonLayer,
                               ... # other layers
                               ]
                           )
Aws.REGION is a pseudo parameter which is bootstrapped from your stack's environment configuration
Change Handler of your function to thundra.handler.wrapper and add the environment variable thundra_agent_lambda_handler with your handler 
from aws_cdk import (core,
                     aws_lambda as lambda_)
​
class YourConstructClass(core.Construct):
​
    def __init__(self, scope: core.Construct, id: str):
        super().__init__(scope, id)
​
        thundraApiKey = <your_api_key>
        thundraAWSAccountNo = 269863060030
        thundraPythonLayerVersion = 31 # or any other version
        thundraPythonLayer = lambda_.LayerVersion.from_layer_version_arn(self, "ThundraLayer",
            "arn:aws:lambda:{}:{}:layer:thundra-lambda-python-layer:{}".format(
                core.Aws.REGION, thundraAWSAccountNo, thundraPythonLayerVersion)),
      
        handler = lambda_.Function(self, "YourHandler",
                           ..., # other function properties
                           handler=thundra.handler.wrapper
                           environment=dict(
                               ..., # other environment variables
                               thundra_apiKey=thundraApiKey,
                               thundra_agent_lambda_handler=<your_handler>),
                           layers=[
                               thundraPythonLayer,
                               ... # other layers
                               ]
                           )
An example configuration:
from aws_cdk import (core,
                     aws_lambda as lambda_)
​
class YourConstructClass(core.Construct):
​
    def __init__(self, scope: core.Construct, id: str):
        super().__init__(scope, id)
​
        thundraApiKey = <your_api_key>
        thundraAWSAccountNo = 269863060030
        thundraPythonLayerVersion = 31
        thundraPythonLayer = lambda_.LayerVersion.from_layer_version_arn(self, "ThundraLayer",
                             "arn:aws:lambda:{}:{}:layer:thundra-lambda-python-layer:{}".format(
                                 core.Aws.REGION, thundraAWSAccountNo,
                                 thundraPythonLayerVersion))
                                     
        with open("your-lambda-handler.py", encoding="utf8") as fp:
            handler_code = fp.read()
        
        handler = lambda_.Function(self, "YourHandler",
                               runtime=lambda_.Runtime.PYTHON_3_8,
                               code=lambda_.InlineCode(handler_code),
                               handler="thundra.handler.wrapper",
                               environment=dict(
                                   thundra_apiKey2=thundraApiKey,
                                   thundra_agent_lambda_handler="your.handler"),
                               layers=[
                                   thundraPythonLayer]
                               )
Step 2: Build / Deploy
cdk deploy
Step 3: Invoke your function!
Now you can try to invoke your Lambda function and see the details of your invocation in the Thundra console!
​
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