v1.0.25 - App deployment fix

Fix app.yaml formatting and ensure latest code is deployed.

• Proper YAML formatting in app.yaml
• Removed duplicate command from bundle config
• Ensures app deploys and starts correctly on Databricks

v1.0.24 - Fix app.yaml formatting and app deployment

Changes in v1.0.24

App Deployment Fix

• Fixed app.yaml file formatting with proper YAML syntax
• Removed duplicate command definition from bundle configuration
• Resolved conflict between bundle config and app.yaml file

Technical Details

• Added proper quotes around string values in app.yaml
• Removed command from resources/app.yml to avoid conflicts
• App command now properly defined in src/app/app.yaml
• Should resolve 'Error reading app.yaml file' deployment issue

Expected Behavior

• App should now deploy successfully without YAML parsing errors
• Streamlit app should start properly on the existing cluster
• No more app deployment failures due to configuration conflicts

v1.0.23 - Add cluster tags to improve existing cluster detection

Changes in v1.0.23

Cluster Configuration Enhancement

• Added tags to cluster configuration to help bundle identify existing clusters
• Tags include: bundle name, environment, and purpose
• Should improve bundle's ability to detect and reuse existing 'hello-world-cluster'

Expected Behavior

• Bundle should now better identify existing clusters with matching tags
• Reduced likelihood of creating duplicate clusters
• More reliable cluster reuse across deployments

Technical Details

• Added tags: bundle=hello-world-app-bundle, environment=prod, purpose=app-cluster
• Tags help with resource identification and management
• Improved resource tracking and lifecycle management

v1.0.22 - Fix bundle configuration to properly handle existing clusters

Changes in v1.0.22

Bundle Configuration Fix

• Removed duplicate cluster configuration from databricks.yml
• Ensured bundle properly handles existing clusters with name 'hello-world-cluster'
• Bundle should now reuse existing clusters instead of creating new ones each time

Expected Behavior

• If cluster 'hello-world-cluster' exists: reuse it
• If cluster doesn't exist: create new one with that name
• No more duplicate clusters on each deployment

Technical Details

• Cluster configuration now properly defined in resources/clusters.yml
• Bundle will detect existing clusters by name
• Improved resource management for production deployments

v1.0.21 - Latest Bundle with Simplified Cluster Management

What's Changed

🚀 Latest Bundle Configuration

• Simplified cluster management: Let bundle handle cluster creation and naming
• Fixed app startup: Added app.yaml and improved Streamlit app
• Enhanced debugging: Better cluster visibility and status checks

📋 Current Bundle Features

• Cluster configuration: Spark 16.3, m5d.large, On-Demand instances
• App configuration: Streamlit app with proper command and error handling
• Job integration: Databricks job that can be triggered from the app
• Bundle deployment: Automated deployment with proper resource management

🔧 Technical Details

• Uses Warning: unknown field: apps
  at targets.dev.resources
  in databricks.yml:20:7

Warning: unknown field: apps
at resources
in resources/app.yml:2:3

Warning: unknown field: clusters
at resources
in resources/clusters.yml:2:3

Error: cannot resolve bundle auth configuration: validate: more than one authorization method configured: oauth and pat. Config: host=https://ias-dataplatform-dev.cloud.databricks.com/, token=, client_id=your-client-id, client_secret=. Env: DATABRICKS_HOST, DATABRICKS_TOKEN, DATABRICKS_CLIENT_ID, DATABRICKS_CLIENT_SECRET for cluster lifecycle

• 120-second wait for cluster readiness
• Proper app.yaml configuration for Streamlit
• Enhanced error handling in app.py
• OAuth authentication throughout

💡 Expected Results

This release should:

1. ✅ Create cluster with correct name - hello-world-cluster
2. ✅ Start Streamlit app properly - No more python app.py errors
3. ✅ Provide clear debugging - Better visibility into deployment process
4. ✅ Handle all edge cases - Robust error handling and recovery

Monitor the deployment in GitHub Actions and Databricks UI for the hello-world-cluster.

v1.0.20 - Let Bundle Handle Cluster Creation and Naming

What's Changed

🐛 Bug Fixes

• Simplified cluster management: Removed manual cluster creation to let bundle handle it properly
• Fixed cluster naming: Bundle should now apply the name from clusters.yml correctly
• Reduced complexity: Eliminated manual cluster detection and creation logic

📋 Technical Details

• Removed manual cluster creation commands from workflow
• Let Warning: unknown field: apps
  at targets.dev.resources
  in databricks.yml:20:7

Warning: unknown field: apps
at resources
in resources/app.yml:2:3

Warning: unknown field: clusters
at resources
in resources/clusters.yml:2:3

Error: cannot resolve bundle auth configuration: validate: more than one authorization method configured: oauth and pat. Config: host=https://ias-dataplatform-dev.cloud.databricks.com/, token=, client_id=your-client-id, client_secret=. Env: DATABRICKS_HOST, DATABRICKS_TOKEN, DATABRICKS_CLIENT_ID, DATABRICKS_CLIENT_SECRET handle cluster lifecycle

• Maintained 120-second wait for cluster readiness
• Kept debugging cluster list for visibility

💡 Why This Should Fix the Naming Issue

The previous approach was creating clusters manually, which bypassed the bundle's cluster configuration. Now:

1. ✅ Bundle creates cluster - Uses the name from
2. ✅ Proper configuration - All settings from the bundle resource are applied
3. ✅ Simplified workflow - Less complexity, fewer failure points
4. ✅ Correct naming - The should now be applied

This release should ensure the cluster is created with the correct name as specified in the bundle configuration.

v1.0.19 - Fix Cluster Recognition and Add Debugging

What's Changed

🐛 Bug Fixes

• Fixed cluster recognition: Improved JSON parsing to properly detect existing clusters
• Enhanced debugging: Added detailed logging to show all available clusters
• Better error handling: More robust cluster detection logic

📋 Technical Details

• Added step for debugging
• Improved jq query with fallback for better null handling
• Added visual indicators (✅🔄⚠️❌) for better log readability
• Shows all available clusters when target cluster is not found

💡 Why This Should Fix the Issue

The previous cluster detection was failing due to JSON parsing issues. This release:

1. ✅ Shows all clusters - Displays what clusters actually exist
2. ✅ Better JSON parsing - Uses more robust jq queries
3. ✅ Clear debugging - Shows exactly why cluster detection succeeds or fails
4. ✅ Prevents unnecessary creation - Should recognize existing clusters properly

This release should prevent the creation of duplicate clusters and properly use existing ones.

v1.0.18 - Fix App Startup and Streamlit Command

What's Changed

🐛 Bug Fixes

• Fixed app startup: Added to ensure Databricks uses the correct command
• Improved Streamlit app: Added title, error handling, and better feedback in
• Centralized configuration: Ensured all app settings are in the right place for Databricks to pick up

📋 Technical Details

• Added with the correct command to the app source directory
• Improved for robustness and better user experience
• Maintained all previous cluster and deployment improvements

💡 Why This Should Fix the Issue

The previous error was caused by Databricks running instead of . This release:

1. ✅ Forces the correct command via
2. ✅ Improves app robustness and error feedback
3. ✅ Should allow the app to start and run as a Streamlit app

Monitor the deployment in GitHub Actions and Databricks. If the error persists, the new logs will be more informative for further debugging.

v1.0.17 - Comprehensive Cluster Management

What's Changed

🚀 New Features

• Comprehensive cluster management: Automatically start existing cluster or create new one if needed
• Smart cluster state detection: Checks if cluster is TERMINATED, RUNNING, or in other states
• Enhanced debugging: Detailed logging of cluster operations and states

📋 Technical Details

• Cluster existence check: Uses to find existing cluster
• State-aware management:
  • If TERMINATED → Starts the cluster
  • If RUNNING → Leaves it running
  • If doesn't exist → Creates new cluster with full configuration
• Automatic cluster creation: Uses with JSON configuration
• Extended wait time: 90 seconds for cluster readiness

💡 Why This Solves the Issue

The previous approach only tried to start existing clusters. This new approach:

1. ✅ Checks if cluster exists - Uses proper JSON parsing
2. ✅ Handles all cluster states - TERMINATED, RUNNING, etc.
3. ✅ Creates cluster if missing - Full configuration with On-Demand instances
4. ✅ Provides detailed logging - Shows exactly what's happening

This release should ensure a cluster is always available and running for the app deployment.

v1.0.16 - Fix app.yaml Parsing Error

What's Changed

🐛 Bug Fixes

• Fixed app.yaml parsing error: Moved app command configuration to bundle resource
• Removed problematic app.yaml file: Eliminated the file that was causing parsing errors
• Improved app configuration: Centralized app settings in the bundle resource

📋 Technical Details

• Added to
• Deleted file that was causing parsing errors
• Maintained all other configurations (cluster, job, etc.)

💡 Why This Fixes the Issue

The persistent 'Error reading app.yaml file' was caused by the separate file format. By moving the command configuration directly into the bundle resource:

1. ✅ Eliminates parsing errors - No separate YAML file to parse
2. ✅ Centralizes configuration - All app settings in one place
3. ✅ Uses bundle-native approach - Leverages Databricks Asset Bundle features

This release should resolve the app deployment issues and allow the app to start properly.