## Product Requirements Document: AIVA - Adaptive Hysteresis Dashboard

This PRD outlines the requirements for building a dashboard to visualize the adaptive hysteresis mechanism in AIVA, providing insights into its duration and workload characteristics over time. This builds upon GPM-065 by making the logged data actionable.

### GPM-066: Create Basic Dashboard Layout
**Goal:** To establish the foundation for the AIVA adaptive hysteresis dashboard.
**Acceptance Criteria:**
- A basic dashboard structure is created with placeholders for key metrics and visualizations.
- The dashboard is accessible through a defined URL.
- The dashboard framework supports adding new charts and data sources.
**Files:** `aiva/dashboard/hysteresis_dashboard.py`, `aiva/dashboard/templates/hysteresis_dashboard.html`
**Spawns:** Implement basic data retrieval and display for a single hysteresis metric.

### GPM-067: Display Average Hysteresis Duration Chart
**Goal:** To visualize the average hysteresis duration over time.
**Acceptance Criteria:**
- A line chart displays the average hysteresis duration.
- The chart's X-axis represents time.
- The chart's Y-axis represents hysteresis duration in milliseconds.
- The chart data is sourced from the logging system (as implemented in GPM-065).
**Files:** `aiva/dashboard/hysteresis_dashboard.py` (charting logic)
**Spawns:** Add filtering options to the hysteresis duration chart (e.g., by workload type).

### GPM-068: Display Workload Type Distribution Chart
**Goal:** To visualize the distribution of workload types processed during the observed time window.
**Acceptance Criteria:**
- A pie chart displays the distribution of workload types.
- Each slice of the pie chart represents a different workload type.
- The size of each slice corresponds to the proportion of time spent processing that workload type.
- The chart data is sourced from the logging system (as implemented in GPM-065).
**Files:** `aiva/dashboard/hysteresis_dashboard.py` (charting logic)
**Spawns:** Implement drill-down functionality for the workload distribution chart.

### GPM-069: Implement Time Range Selection
**Goal:** To allow users to specify the time range for data displayed on the dashboard.
**Acceptance Criteria:**
- A time range selection component is added to the dashboard.
- Users can select a predefined time range (e.g., last hour, last day, last week).
- Users can define a custom time range using a date and time picker.
- All charts on the dashboard update to reflect the selected time range.
**Files:** `aiva/dashboard/hysteresis_dashboard.py` (time range handling), `aiva/dashboard/templates/hysteresis_dashboard.html` (time range selection component)
**Spawns:** Implement data aggregation and summarization for different time granularities (e.g., hourly, daily).

### GPM-070: Add Hysteresis Duration Percentile Charts
**Goal:** To provide insights into the distribution of hysteresis durations beyond just the average.
**Acceptance Criteria:**
- Add line charts showing the 50th (median), 90th, and 99th percentile hysteresis durations over time.
- The charts' X-axis represents time.
- The charts' Y-axis represents hysteresis duration in milliseconds.
- The charts data is sourced from the logging system (as implemented in GPM-065).
**Files:** `aiva/dashboard/hysteresis_dashboard.py` (charting logic)
**Spawns:** Allow users to customize the percentile values displayed on the chart.

### GPM-071: Implement Workload-Specific Hysteresis Duration Charts
**Goal:** To enable analysis of hysteresis duration characteristics for individual workload types.
**Acceptance Criteria:**
- Users can select a specific workload type from a dropdown menu.
- The average and percentile hysteresis duration charts update to display data only for the selected workload type.
**Files:** `aiva/dashboard/hysteresis_dashboard.py` (filtering logic), `aiva/dashboard/templates/hysteresis_dashboard.html` (workload type selection component)
**Spawns:** Implement anomaly detection for workload-specific hysteresis duration.

### GPM-072: Implement Automatic Dashboard Refresh
**Goal:** To ensure the dashboard displays the most up-to-date data.
**Acceptance Criteria:**
- The dashboard automatically refreshes its data at a configurable interval (e.g., every 5 minutes).
- The refresh interval is configurable via a setting.
**Files:** `aiva/dashboard/hysteresis_dashboard.py` (refresh mechanism), `aiva/config/aiva_config.py` (setting for refresh interval)
**Spawns:** Implement real-time data streaming for the dashboard.
