This is a CDK Python project for logging API calls to Amazon Kinesis Data Firehose.
The cdk.json
file tells the CDK Toolkit how to execute your app.
This project is set up like a standard Python project. The initialization
process also creates a virtualenv within this project, stored under the .venv
directory. To create the virtualenv it assumes that there is a python3
(or python
for Windows) executable in your path with access to the venv
package. If for any reason the automatic creation of the virtualenv fails,
you can create the virtualenv manually.
To manually create a virtualenv on MacOS and Linux:
$ 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
If you are a Windows platform, you would activate the virtualenv like this:
% .venv\Scripts\activate.bat
Once the virtualenv is activated, you can install the required dependencies.
(.venv) $ pip install -r requirements.txt
At this point you can now synthesize the CloudFormation template for this code.
(.venv) $ export CDK_DEFAULT_ACCOUNT=$(aws sts get-caller-identity --query Account --output text) (.venv) $ export CDK_DEFAULT_REGION=$(aws configure get region) (.venv) $ cdk synth -c firehose_name=amazon-apigateway-{your-delivery-stream-name}
Use cdk deploy
command to create the stack shown above,
(.venv) $ cdk deploy -c firehose_name=amazon-apigateway-{your-delivery-stream-name}
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.
Delete the CloudFormation stack by running the below command.
(.venv) $ cdk destroy
cdk ls
list all stacks in the appcdk synth
emits the synthesized CloudFormation templatecdk deploy
deploy this stack to your default AWS account/regioncdk diff
compare deployed stack with current statecdk docs
open CDK documentation
Enjoy!
-
Invoke REST API method
$ curl -X GET 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?len=7'
The response is:
["weBJDKv"]
-
Generate test requests and run them.
$ cat <<EOF > run_test.sh > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?len=7' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?chars=letters' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?chars=letters&len=15' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?chars=lowercase&len=15' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?chars=uppercase&len=5' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?chars=digits&len=7' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?chars=digits&len=17' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?len=3' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?chars=letters&len=9' > curl 'https://{your-api-gateway-id}.execute-api.{region}.amazonaws.com/prod/random/strings?len=17' > EOF $ bash ./run_test.sh
-
Check the access logs in S3
After 5~10 minutes, you can see that the access logs have been delivered by Kinesis Data Firehose to S3 and stored in a folder structure by year, month, day, and hour.