# Phase 3 Implementation Plan - Service Grouping and Scalability

## Overview
Implemented service grouping with composite health reporting and UI scalability enhancements to support up to 30 services.

## Key Features
1. **Service Grouping**: Services are grouped by name into single rows
2. **Composite Health**: Overall service health based on all instances
3. **Scalability**: UI optimizations to support 30+ services

## Implementation Details

### Backend Modifications
1. **Service Grouping Logic** (database.py)
   - Added `get_all_services_grouped()` function
   - Implemented composite health calculation per service
   - Returns aggregated service data with instance lists

2. **Database Queries**
   - Created optimized query to group services by name
   - Added composite status calculation in SQL
   - Maintained instance details within service groups

3. **API Endpoint Updates** (app.py)
   - Modified `/api/services` to return service groups
   - Added service-based instance grouping in responses

### Frontend Changes
1. **Table Redesign** (index.html)
   - Converted to service-based table structure
   - Added expandable rows for instance details
   - Implemented service health indicators

2. **Health Reporting UI**
   - Added composite status indicators per service
   - Maintained instance-level health details
   - Preserved history chart functionality

3. **Scalability Features**
   - Added expand/collapse functionality
   - Optimized UI for 30+ services
   - Efficient data loading with grouping

### Health Calculation
1. **Status Algorithm**
   - Critical if any instance critical
   - Warning if any instance warning (no criticals)
   - Passing if all instances passing

## Implementation Sequence
1. Updated database.py for service grouping
2. Modified app.py endpoints to use service groups
3. Redesigned frontend to display service groups
4. Added expand/collapse functionality for instances
5. Maintained URL generation for instances
6. Added error handling for new data model

## Testing Considerations
- Verify service grouping by name
- Test composite health calculation logic
- Validate expand/collapse functionality
- Test with 30+ services to ensure scalability
- Verify history charts still function properly
- Test error handling for Consul unavailability

## Estimated Implementation Time
**Total: 4-5 hours**

## Next Steps
- Implement pagination for large service sets
- Add search/filter functionality
- Optimize database queries for large datasets
- Implement service-level history charts