Deployment Inventory
This page lists everything the Lakemeter installer creates in your Databricks workspace. Use this as a reference for auditing or manual cleanup.
Resource Summary
| Resource | Name | Type |
|---|---|---|
| Lakebase project | lakemeter-customer | Lakebase Autoscaling |
| Lakebase branch | production | Copy-on-write PostgreSQL branch |
| Lakebase endpoint | primary | Read-write autoscaling compute |
| Database | lakemeter_pricing | PostgreSQL database |
| Schema | lakemeter | PostgreSQL schema |
| Application tables | users, estimates, line_items, templates, sharing, conversation_messages, decision_records, ref_cloud_tiers, ref_workload_types | PostgreSQL tables |
| Stored functions | 15 cost calculation functions | PostgreSQL functions |
| Pricing sync tables | 10 tables with DBU rates, VM costs, model pricing | PostgreSQL tables |
| Derived reference tables | ref_fmapi_databricks_models, ref_fmapi_proprietary_models, ref_model_serving_gpu_types | PostgreSQL tables |
| SKU mapping | ref_sku_discount_mapping | PostgreSQL table |
| Secret scope | lakemeter-secrets | Databricks secret scope |
| Secrets | 7 key-value pairs | Databricks secrets |
| Databricks App | lakemeter | Databricks App |
| App resources | 7 environment variable bindings | App config |
| Lakebase role | App Service Principal | Database role |
| PostgreSQL role | lakemeter_sync_role | Password-auth role |
Lakebase Autoscaling Project
| Property | Value |
|---|---|
| Project ID | lakemeter-customer (configurable via --project-id) |
| Branch | production |
| Read-write endpoint | primary |
| Type | Lakebase Autoscaling |
| Autoscaling | 1 CU – 16 CU |
| Scale-to-zero | After 5 minutes of inactivity |
| Native login | Enabled for password-auth fallback |
Secret Scope: lakemeter-secrets
| Secret Key | Description |
|---|---|
lakebase-project | Full project resource name |
lakebase-branch | Full production branch resource name |
lakebase-endpoint | Full primary endpoint resource name |
lakebase-host | Primary endpoint DNS host |
lakebase-user | PostgreSQL role name (lakemeter_sync_role) |
lakebase-database | Database name (lakemeter_pricing) |
lakebase-password | Auto-generated password for lakemeter_sync_role |
Databricks App: lakemeter
| Property | Value |
|---|---|
| Name | lakemeter (configurable via --app-name) |
| Compute size | MEDIUM (2 vCPU, 6 GB RAM) |
| Runtime | Ubuntu 22.04, Python 3.11, Node.js 22.16 |
| Source path | /Workspace/Users/{user}/apps/lakemeter |
| URL | https://lakemeter-<workspace-id>.<cloud>.databricksapps.com |
App Resources
These environment variables are injected into the app container at runtime:
| Resource Name | Environment Variable | Type | Source |
|---|---|---|---|
lm-lakebase-project | LAKEBASE_PROJECT | Secret | lakemeter-secrets:lakebase-project |
lm-lakebase-branch | LAKEBASE_BRANCH | Secret | lakemeter-secrets:lakebase-branch |
lm-lakebase-endpoint | LAKEBASE_ENDPOINT | Secret | lakemeter-secrets:lakebase-endpoint |
lm-db-host | DB_HOST | Secret | lakemeter-secrets:lakebase-host |
lm-db-user | DB_USER | Secret | lakemeter-secrets:lakebase-user |
lm-db-name | DB_NAME | Secret | lakemeter-secrets:lakebase-database |
lm-claude-endpoint | CLAUDE_MODEL_ENDPOINT | Serving Endpoint | databricks-claude-opus-4-6 |
Service Principal
The app gets an auto-created Service Principal with:
| Permission | Target | Purpose |
|---|---|---|
| Lakebase OAuth role | production branch | Authenticates the app Service Principal |
| SQL grants | lakemeter schema | CONNECT, USAGE, ALL PRIVILEGES on tables/sequences/functions |
| Secret READ | lakemeter-secrets scope | Read database credentials |
| CAN_QUERY | databricks-claude-opus-4-6 | Query the Claude model endpoint |
Cleanup
To completely remove Lakemeter from your workspace:
# 1. Delete the Databricks App
databricks apps delete lakemeter --profile <profile>
# 2. Delete the Lakebase project (destroys all branches and data)
databricks postgres delete-project projects/lakemeter-customer --profile <profile>
# 3. Delete the secrets scope
databricks secrets delete-scope lakemeter-secrets --profile <profile>
# 4. Remove bundle files (optional)
databricks workspace delete -r /Workspace/Users/{user}/.bundle/lakemeter-installer --profile <profile>
# 5. Remove app source (optional)
databricks workspace delete -r /Workspace/Users/{user}/apps/lakemeter --profile <profile>
Warning: Deleting the Lakebase project permanently destroys all branches, databases, tables, and data within it. This cannot be undone.