# PRD: Real-time Downscale Pattern Detection

This PRD focuses on implementing real-time detection of predefined downscale patterns within the AIVA system. It builds upon the previously defined downscale patterns (GPM-066) and allows the system to react proactively to these patterns.

### GPM-067: Implement Downscale Pattern Detection Engine
**Goal:** To create a core engine capable of identifying downscale patterns based on incoming trigger events.
**Acceptance Criteria:**
- The engine can ingest a stream of trigger events (simulated or real).
- The engine can be configured with a list of defined downscale patterns (loaded from a configuration file).
- For each incoming event, the engine evaluates if a currently active pattern matches the event.
- If a pattern is detected, the engine logs a notification with details of the pattern and the triggering events.
**Files:** `aiva/downscale_detection/pattern_engine.py`, `aiva/downscale_detection/config.py`
**Spawns:** Integrate the detection engine with a real-time data stream.

### GPM-068: Integrate with Real-Time Metric Stream
**Goal:** To connect the downscale detection engine to a real-time stream of performance metrics (simulated or from a monitoring system).
**Acceptance Criteria:**
- The engine can receive trigger events generated from a simulated metric stream.
- The engine can be configured to subscribe to specific metrics from a test monitoring system (e.g., Prometheus, Grafana).
- Trigger events are generated based on pre-defined thresholds for the metrics.
**Files:** `aiva/data_integration/metric_stream.py`, `aiva/data_integration/trigger_generator.py`
**Spawns:** Define actions to take when a downscale pattern is detected.

### GPM-069: Define Default Downscale Actions
**Goal:** To define a set of default actions that can be triggered when a downscale pattern is detected.
**Acceptance Criteria:**
- A configuration file allows defining actions to be associated with specific downscale patterns.
- Supported actions include: logging, sending alerts (e.g., email, Slack), and triggering scaling policies (simulated).
- Default actions are defined for a few common downscale patterns.
**Files:** `aiva/actions/downscale_actions.py`, `aiva/downscale_detection/config.py` (updates)
**Spawns:** Implement the execution of the defined downscale actions.

### GPM-070: Implement Downscale Action Execution
**Goal:** To implement the execution of the defined downscale actions when a pattern is detected.
**Acceptance Criteria:**
- When a downscale pattern is detected, the associated actions are executed.
- Actions are executed asynchronously to avoid blocking the detection engine.
- The system logs the successful or failed execution of each action.
- Simulated scaling policies can be triggered.
**Files:** `aiva/actions/action_executor.py`, `aiva/actions/scaling_policy_simulator.py`
**Spawns:** Implement a user interface to configure downscale patterns and actions.

### GPM-071: Add Basic UI for Configuration
**Goal:** To provide a basic user interface for configuring downscale patterns and associated actions.
**Acceptance Criteria:**
- A simple web interface allows users to view, add, edit, and delete downscale patterns.
- The UI allows users to associate actions with each downscale pattern.
- The UI is secured with basic authentication.
**Files:** `aiva/ui/downscale_config.html`, `aiva/ui/app.py` (Flask app)
**Spawns:** Implement more advanced action types, such as interacting with cloud provider APIs to trigger actual scaling events.

### GPM-072: Implement Alerting Mechanism
**Goal:** To implement a robust alerting mechanism to notify relevant stakeholders when downscale patterns are detected.
**Acceptance Criteria:**
- Support for sending alerts via email and Slack.
- Configurable alert thresholds and escalation policies.
- Alert messages include relevant details about the detected pattern and triggering events.
- Alerts can be suppressed based on configurable rules (e.g., during maintenance windows).
**Files:** `aiva/alerts/alert_manager.py`, `aiva/alerts/email_sender.py`, `aiva/alerts/slack_sender.py`
**Spawns:** Implement more sophisticated pattern matching techniques, such as fuzzy matching and machine learning-based pattern recognition.
