# PRD: Implement Structured Logging for AIVA

This PRD focuses on implementing structured logging across AIVA to improve log readability, parseability, and overall debuggability. We will begin by migrating existing log statements to a JSON format.

### GPM-080: Configure Logging Library for JSON Output
**Goal:** Configure the Python logging library to output logs in JSON format.
**Acceptance Criteria:**
- The logging library is configured to use a JSON formatter.
- All log output is in valid JSON format.
- The logging configuration is easily adjustable via a configuration file.
**Files:** `config/logging.ini`, `aiva/utils/logging_setup.py`
**Spawns:** Explore adding standardized fields to the JSON log output (e.g., timestamp, log level).

### GPM-081: Standardize Log Levels across AIVA
**Goal:** Ensure consistent use of log levels (DEBUG, INFO, WARNING, ERROR, CRITICAL) throughout AIVA.
**Acceptance Criteria:**
- A document defining the intended use of each log level is created.
- All existing log statements are reviewed and adjusted to use the appropriate log level.
- Code reviewers are trained on the log level usage guidelines.
**Files:** `docs/logging_standards.md`, *all AIVA source files*
**Spawns:** Investigate adding contextual information to log messages based on the specific module or function.

### GPM-082: Add Timestamp and Log Level to JSON Logs
**Goal:** Include the timestamp and log level in each JSON log message.
**Acceptance Criteria:**
- Each JSON log message contains a `timestamp` field in ISO 8601 format.
- Each JSON log message contains a `level` field representing the log level.
- The timestamp and level fields are consistently formatted.
**Files:** `aiva/utils/logging_setup.py`
**Spawns:** Consider adding the module name or function name to the JSON log output.

### GPM-083: Add Module and Function Name to JSON Logs
**Goal:** Include the module and function name in each JSON log message.
**Acceptance Criteria:**
- Each JSON log message contains a `module` field with the name of the module generating the log.
- Each JSON log message contains a `function` field with the name of the function generating the log.
- The module and function fields are populated automatically by the logging framework.
**Files:** `aiva/utils/logging_setup.py`
**Spawns:** Explore adding the current thread ID to the JSON log output for multi-threaded debugging.

### GPM-084: Implement Trace ID Propagation for Structured Logs
**Goal:** Ensure Trace IDs are automatically included in structured logs.
**Acceptance Criteria:**
- The existing Trace ID mechanism is integrated with the structured logging setup.
- Every log statement within a traced operation includes the current Trace ID in the JSON log.
- The Trace ID field is named `trace_id`.
**Files:** `aiva/utils/logging_setup.py`, *relevant AIVA modules using tracing*
**Spawns:** Investigate enriching logs with additional contextual data based on the current request or operation.

### GPM-085: Centralized Log Aggregation and Analysis
**Goal:** Configure a centralized log aggregation system to collect and analyze the structured logs.
**Acceptance Criteria:**
- A logging aggregation system (e.g., Elasticsearch, Splunk) is selected and configured.
- AIVA's logs are shipped to the aggregation system.
- Basic dashboards and queries are set up to analyze log data.
**Files:** `config/logging.ini`, *deployment scripts*
**Spawns:** Explore advanced log analysis techniques, such as anomaly detection and correlation analysis.

### GPM-086: Update Existing Log Statements to Use Structured Logging
**Goal:** Migrate all existing `print` statements and basic logging calls to use the new structured logging format.
**Acceptance Criteria:**
- No `print` statements exist in the codebase except for specific debugging or development purposes (clearly marked).
- All log statements use the configured logging library and JSON format.
- All new log statements adhere to the logging standards.
**Files:** *All AIVA source files*
**Spawns:** Implement automated linting rules to enforce the use of structured logging and prevent the introduction of `print` statements.
