## PRD: Dynamic Resource Threshold Adjustment

This PRD focuses on enabling dynamic adjustment of resource monitoring thresholds without requiring a restart of the monitoring loop. This will allow for more responsive and adaptive resource management.

### GPM-070: Implement Threshold Update Mechanism
**Goal:** Implement a mechanism to update resource thresholds in memory without restarting the monitoring loop.
**Acceptance Criteria:**
- A new function `update_thresholds(threshold_config)` is implemented in `resource_monitor.py`.
- This function takes a dictionary representing the new thresholds for CPU, memory, disk, and network.
- The function updates the internal threshold variables used by the monitoring loop.
- Calling `update_thresholds` does not interrupt the monitoring loop.
**Files:** `resource_monitor.py`
**Spawns:** Create an API endpoint to trigger the threshold update mechanism.

### GPM-071: Create API Endpoint for Threshold Updates
**Goal:** Expose an API endpoint to allow external systems to update resource thresholds.
**Acceptance Criteria:**
- A new API endpoint `/thresholds` is created using Flask.
- The endpoint accepts POST requests with a JSON payload containing the new threshold values.
- The endpoint validates the incoming JSON payload to ensure it contains valid threshold values for CPU, memory, disk, and network.
- The endpoint calls `update_thresholds` with the validated threshold values.
- The endpoint returns a 200 OK status code upon successful update.  It returns a 400 Bad Request if the payload is invalid.
**Files:** `api.py`, `requirements.txt` (if new dependencies are added)
**Spawns:** Implement authentication and authorization for the threshold update API endpoint.

### GPM-072: Input Validation for API Endpoint
**Goal:** Robustly validate the input received at the `/thresholds` API endpoint.
**Acceptance Criteria:**
- The API endpoint validates that all required fields (CPU, Memory, Disk, Network) are present in the JSON payload.
- The API endpoint validates that the values for CPU, Memory, Disk, and Network are numeric.
- The API endpoint validates that the values for CPU, Memory, Disk, and Network are within a reasonable range (e.g., 0-100 for CPU, 0-MAX_MEMORY for Memory).  Define reasonable ranges for Disk and Network.
- The API endpoint returns a 400 Bad Request status code with a descriptive error message if any validation fails.
**Files:** `api.py`
**Spawns:** Add logging to the threshold update API endpoint.

### GPM-073: Logging for Threshold Updates
**Goal:** Implement logging for successful and unsuccessful threshold updates.
**Acceptance Criteria:**
- Log messages are generated for each successful threshold update, including the old and new threshold values.
- Log messages are generated for each failed threshold update, including the reason for the failure (e.g., invalid input).
- Log messages are written to a dedicated log file (e.g., `threshold_updates.log`).
- Log messages include timestamps and relevant metadata (e.g., originating IP address of the API request).
**Files:** `api.py`, `logging_config.py` (if a centralized logging configuration is used)
**Spawns:** Implement persistence of threshold configurations.

### GPM-074: Persist Threshold Configurations
**Goal:** Store the current threshold configuration to disk, so it survives restarts.
**Acceptance Criteria:**
- Upon a successful threshold update via the API, the new threshold configuration is written to a file (e.g., `thresholds.json`).
- When the `resource_monitor` starts, it loads the threshold configuration from the file.
- If the file does not exist or is invalid, default thresholds are used.
- The file is written atomically to prevent data corruption.
**Files:** `resource_monitor.py`, `api.py`
**Spawns:** Add a command-line interface (CLI) tool to update thresholds.

### GPM-075: Implement CLI Threshold Update Tool
**Goal:** Provide a CLI tool for updating resource thresholds.
**Acceptance Criteria:**
- A new CLI tool (e.g., `aiva-thresholds`) is created.
- The CLI tool accepts arguments for setting CPU, memory, disk, and network thresholds.
- The CLI tool calls the API endpoint to update the thresholds.
- The CLI tool displays a success or error message based on the API response.
**Files:** `aiva-thresholds.py` (or similar), `setup.py` (to make it installable)
**Spawns:** Implement alerting based on dynamically configured thresholds.

### GPM-076: Extend Alerting to Use Dynamic Thresholds
**Goal:** Make alerting logic use the dynamically configured thresholds.
**Acceptance Criteria:**
- The alerting logic in `resource_monitor.py` uses the thresholds obtained via the `update_thresholds` function.
- Alerting is triggered based on the dynamically configured thresholds.
- Existing alerting mechanisms (e.g., email, logging) continue to function as expected.
**Files:** `resource_monitor.py`, `alerting.py` (or similar)
**Spawns:** Add unit tests for threshold update functionality.
