Needed files

How to create the Canary

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The service principal used by LHO requires permissions to be granted to it in order to access Databricks Workspaces and those assets managed by workspaces. These access rights can be granted via the python_provisiong.py script which requires an admin Databricks account in order to grant permisions.

If new assets (workflows, notebooks, clusters) are added in a workspace, then the LHO service principal need to be granted permission to those assets as well. This can be done automatically by adding the previous as script as an AWS Canary that runs recurrently every 15 min.

How to create the AWS Canary

Step 1. Create a python virtualenv
On your local machine create a virtual env in order to prepare the canary archive.

mkdir lhm-grant
cd lhm-grant
python3 -m venv .venv
source .venv/bin/activate

Step 2. Download the requirements.txt into the created lhm-grant folder

Step 3. Install required packages

pip install -r requirements.txt

Step 4. Copy all the installed libraries into a folder called python

mkdir python
cp -rfv .venv/lib/python3.7/site-packages/* python/

Step 5. Download aws_main.py and python_provisioning.py into the python directory

Step 6. Modify

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aws_main.py script and provide the needed information for the grant code in the section marked for change

Step 7. Create an archive with the python folder

zip -r9 lhm-grant.zip python

Step 8. Upload the archive to s3

Step 9. Create CloudWatch canary from s3 bucket artifact

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• name you canary as lhm-grant (or any other name that you want to use)

• select the S3 location for the archive

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Notes:

• set the lambda handler (your entry point for the script) to aws_main.handler

• set the schedule to continuously with intervals of 15 mins

  • recommended configuration

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Step 10. Check logs of the python_provisioning.py script run

Open the list of Synthetic Canaries and select the canary configured previously (e.g. lhm-grant) in order to select a particular run and view the logs.

To check the logs of a run you will download the artifacts archive from that run, unzip it and there should be a file called python_provisioning.log

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