Terraform Automation for WAF Assessment Tool Deployment

[AbhiDatabricks]

Overview

Build a Terraform module to automate the deployment of the WAF Assessment Tool on Databricks, replacing (or complementing) the manual install.ipynb notebook approach.

Motivation

• Enable repeatable, version-controlled, CI/CD-friendly deployments
• Remove the need to manually run a Databricks notebook to stand up the stack
• Support multi-workspace and multi-environment (dev/staging/prod) deployments

Scope

Resources to provision via Terraform

• Unity Catalog: catalog + schema creation (if not exists)
• Lakeview Dashboard: deploy from WAF_ASSESSMENTv1.7.1.lvdash.json template
• Genie AI Space: create space and link to dashboard via uiSettings.genieSpace.overrideId
• Databricks App (Streamlit): deploy streamlit-waf-automation/ as a Databricks App
• WAF Reload Job: create job that runs waf_reload.py on schedule
• waf_cache tables: populate via job run or SQL init scripts

Variables / inputs

• workspace_url
• catalog, schema
• cluster_policy_id (optional)
• job_schedule (cron)
• genie_space_title

Outputs

• Dashboard URL
• Genie Space URL
• Streamlit App URL
• Job ID

Acceptance Criteria

• terraform apply deploys the full stack on a clean workspace
• terraform destroy cleanly removes all created resources
• Module is parameterized for multi-workspace use
• State can be stored remotely (e.g., S3/GCS/Azure Blob)

Open Questions

• Which Terraform provider version supports databricks_dashboard and databricks_app?
• Should this live in a /terraform directory or a separate repo?
• Do we wrap this in a Terraform Cloud workspace or keep it CLI-only?

[albertwangnz]

I strongly agree with this suggestion 👍

Moving the WAF Assessment Tool deployment into a Terraform module would be a significant improvement over the current manual install.ipynb approach.