"""
Comprehensive logging and telemetry system for MorphGuard.

This module provides centralized logging, performance metrics tracking,
and telemetry data collection for monitoring and analysis.
"""

import logging
import time
import json
import os
import sys
import socket
import uuid
import threading
import platform
import psutil
import queue
from typing import Dict, Any, Optional, List, Callable, Union
from datetime import datetime
import traceback
import atexit
from contextlib import contextmanager
from enum import Enum

# Import local error handling module
from error_handling import MGError, ErrorCode, ErrorSeverity, ErrorCategory

class LogLevel(Enum):
    """Log levels for telemetry events."""
    DEBUG = "debug"
    INFO = "info"
    WARNING = "warning"
    ERROR = "error"
    CRITICAL = "critical"

class MetricType(Enum):
    """Types of metrics that can be tracked."""
    COUNTER = "counter"
    GAUGE = "gauge"
    HISTOGRAM = "histogram"
    SUMMARY = "summary"
    TIMER = "timer"

class EventCategory(Enum):
    """Categories of telemetry events."""
    API = "api"
    AUTHENTICATION = "authentication"
    DETECTION = "detection"
    DEMORPHING = "demorphing"
    DATABASE = "database"
    FILE = "file"
    MODEL = "model"
    PERFORMANCE = "performance"
    SECURITY = "security"
    USER = "user"
    SYSTEM = "system"
    ERROR = "error"

class TelemetryManager:
    """
    Central manager for logging, metrics, and telemetry.
    
    This class provides:
    - Structured logging with context
    - Performance metrics tracking
    - System resource monitoring
    - Telemetry event collection
    - Integration with external monitoring systems
    """
    
    def __init__(
        self,
        app_name: str = "morphguard",
        log_dir: Optional[str] = None,
        telemetry_dir: Optional[str] = None,
        log_level: int = logging.INFO,
        console_logging: bool = True,
        file_logging: bool = True,
        json_logging: bool = False,
        system_metrics_interval: int = 60,
        enable_telemetry: bool = True,
        max_queue_size: int = 1000,
        flush_interval: int = 5,
        export_metrics: bool = False,
        metrics_exporter: Optional[str] = None
    ):
        """
        Initialize the telemetry manager.
        
        Args:
            app_name: Application name for logs and metrics
            log_dir: Directory to store log files
            telemetry_dir: Directory to store telemetry data
            log_level: Default log level
            console_logging: Whether to log to console
            file_logging: Whether to log to file
            json_logging: Whether to use JSON format for logs
            system_metrics_interval: Interval for system metrics collection in seconds
            enable_telemetry: Whether to collect telemetry data
            max_queue_size: Maximum size of telemetry event queue
            flush_interval: Interval to flush telemetry queue in seconds
            export_metrics: Whether to export metrics to external systems
            metrics_exporter: Type of metrics exporter (prometheus, influxdb, etc.)
        """
        self.app_name = app_name
        self.log_dir = log_dir
        self.telemetry_dir = telemetry_dir
        self.console_logging = console_logging
        self.file_logging = file_logging
        self.json_logging = json_logging
        self.enable_telemetry = enable_telemetry
        self.export_metrics = export_metrics
        self.metrics_exporter = metrics_exporter
        self.max_queue_size = max_queue_size
        self.flush_interval = flush_interval
        
        # Create directories if needed
        if log_dir and not os.path.exists(log_dir):
            os.makedirs(log_dir)
        
        if telemetry_dir and not os.path.exists(telemetry_dir):
            os.makedirs(telemetry_dir)
        
        # Setup main logger
        self.logger = self._setup_logger(log_level)
        
        # Metrics storage
        self.metrics: Dict[str, Dict[str, Any]] = {
            "counters": {},
            "gauges": {},
            "histograms": {},
            "summaries": {},
            "timers": {}
        }
        
        # Context for logs and telemetry
        self.global_context: Dict[str, Any] = {
            "host": socket.gethostname(),
            "app_name": app_name,
            "instance_id": str(uuid.uuid4()),
            "platform": platform.system(),
            "python_version": platform.python_version(),
            "start_time": datetime.utcnow().isoformat()
        }
        
        # Thread-local storage for context
        self.context = threading.local()
        self.context.values = {}
        
        # Telemetry queue and worker thread
        self.telemetry_queue: queue.Queue = queue.Queue(maxsize=max_queue_size)
        self.telemetry_thread: Optional[threading.Thread] = None
        
        # System metrics thread
        self.system_metrics_interval = system_metrics_interval
        self.system_metrics_thread: Optional[threading.Thread] = None
        
        # Locks
        self.metrics_lock = threading.RLock()
        
        # Start telemetry worker if enabled
        if enable_telemetry:
            self._start_telemetry_worker()
            self._start_system_metrics_collector()
        
        # Register cleanup on exit
        atexit.register(self.shutdown)
        
        # Log startup
        self.info("Telemetry system initialized", 
                 category=EventCategory.SYSTEM, 
                 context={"telemetry_enabled": enable_telemetry})
    
    def _setup_logger(self, log_level: int) -> logging.Logger:
        """
        Set up the main logger.
        
        Args:
            log_level: Default log level
            
        Returns:
            Configured logger
        """
        logger = logging.getLogger(self.app_name)
        logger.setLevel(log_level)
        logger.propagate = False
        
        # Clear existing handlers
        if logger.handlers:
            for handler in logger.handlers:
                logger.removeHandler(handler)
        
        # Formatter
        if self.json_logging:
            formatter = self._json_formatter
        else:
            formatter = logging.Formatter(
                '%(asctime)s [%(levelname)s] [%(name)s] %(message)s',
                datefmt='%Y-%m-%d %H:%M:%S'
            )
        
        # Console handler
        if self.console_logging:
            console_handler = logging.StreamHandler(sys.stdout)
            console_handler.setFormatter(formatter)
            logger.addHandler(console_handler)
        
        # File handler
        if self.file_logging and self.log_dir:
            log_file = os.path.join(self.log_dir, f"{self.app_name}.log")
            file_handler = logging.FileHandler(log_file)
            file_handler.setFormatter(formatter)
            logger.addHandler(file_handler)
            
            # Also create error log
            error_log_file = os.path.join(self.log_dir, f"{self.app_name}_error.log")
            error_handler = logging.FileHandler(error_log_file)
            error_handler.setLevel(logging.ERROR)
            error_handler.setFormatter(formatter)
            logger.addHandler(error_handler)
        
        return logger
    
    def _json_formatter(self, record: logging.LogRecord) -> str:
        """
        Format log record as JSON.
        
        Args:
            record: Log record to format
            
        Returns:
            JSON string
        """
        timestamp = datetime.fromtimestamp(record.created).isoformat()
        
        # Basic log data
        log_data = {
            "timestamp": timestamp,
            "level": record.levelname,
            "logger": record.name,
            "message": record.getMessage(),
            "module": record.module,
            "function": record.funcName,
            "line": record.lineno
        }
        
        # Add context if available
        context = getattr(record, 'context', None)
        if context:
            log_data["context"] = context
        
        # Add exception info if available
        if record.exc_info:
            log_data["exception"] = {
                "type": record.exc_info[0].__name__,
                "message": str(record.exc_info[1]),
                "traceback": traceback.format_exception(*record.exc_info)
            }
        
        return json.dumps(log_data)
    
    def _start_telemetry_worker(self) -> None:
        """Start the background telemetry worker thread."""
        self.telemetry_thread = threading.Thread(
            target=self._telemetry_worker,
            daemon=True,
            name="telemetry_worker"
        )
        self.telemetry_thread.start()
    
    def _telemetry_worker(self) -> None:
        """Background worker to process and export telemetry events."""
        while True:
            try:
                # Wait for the flush interval
                time.sleep(self.flush_interval)
                
                # Process all events in the queue
                events = []
                while not self.telemetry_queue.empty():
                    try:
                        event = self.telemetry_queue.get_nowait()
                        events.append(event)
                        self.telemetry_queue.task_done()
                    except queue.Empty:
                        break
                
                if events:
                    self._export_events(events)
            
            except Exception as e:
                # Log the error but keep the thread running
                self.logger.error(f"Error in telemetry worker: {e}", exc_info=True)
    
    def _export_events(self, events: List[Dict[str, Any]]) -> None:
        """
        Export telemetry events to storage or external systems.
        
        Args:
            events: List of telemetry events to export
        """
        if not events:
            return
        
        # Save to file if telemetry directory is configured
        if self.telemetry_dir:
            timestamp = datetime.utcnow().strftime("%Y%m%d_%H%M%S")
            file_path = os.path.join(self.telemetry_dir, f"telemetry_{timestamp}.json")
            
            try:
                with open(file_path, "w") as f:
                    json.dump(events, f)
            except Exception as e:
                self.logger.error(f"Failed to save telemetry events: {e}", exc_info=True)
        
        # Add exporters for other systems here (e.g. Prometheus, InfluxDB, etc.)
        if self.export_metrics and self.metrics_exporter:
            if self.metrics_exporter.lower() == "prometheus":
                self._export_to_prometheus(events)
            elif self.metrics_exporter.lower() == "influxdb":
                self._export_to_influxdb(events)
    
    def _export_to_prometheus(self, events: List[Dict[str, Any]]) -> None:
        """
        Export metrics to Prometheus.
        
        Args:
            events: List of telemetry events to export
        """
        # Placeholder for Prometheus export
        pass
    
    def _export_to_influxdb(self, events: List[Dict[str, Any]]) -> None:
        """
        Export metrics to InfluxDB.
        
        Args:
            events: List of telemetry events to export
        """
        # Placeholder for InfluxDB export
        pass
    
    def _start_system_metrics_collector(self) -> None:
        """Start the background system metrics collector thread."""
        self.system_metrics_thread = threading.Thread(
            target=self._system_metrics_collector,
            daemon=True,
            name="system_metrics_collector"
        )
        self.system_metrics_thread.start()
    
    def _system_metrics_collector(self) -> None:
        """Background worker to collect system metrics periodically."""
        while True:
            try:
                # Collect system metrics
                self._collect_system_metrics()
                
                # Wait for the next collection interval
                time.sleep(self.system_metrics_interval)
            
            except Exception as e:
                # Log the error but keep the thread running
                self.logger.error(f"Error in system metrics collector: {e}", exc_info=True)
                time.sleep(self.system_metrics_interval)
    
    def _collect_system_metrics(self) -> None:
        """Collect system metrics and record them."""
        try:
            # CPU usage
            cpu_percent = psutil.cpu_percent(interval=1)
            self.gauge("system.cpu.percent", cpu_percent)
            
            # Memory usage
            memory = psutil.virtual_memory()
            self.gauge("system.memory.total", memory.total)
            self.gauge("system.memory.available", memory.available)
            self.gauge("system.memory.used", memory.used)
            self.gauge("system.memory.percent", memory.percent)
            
            # Disk usage
            disk = psutil.disk_usage('/')
            self.gauge("system.disk.total", disk.total)
            self.gauge("system.disk.used", disk.used)
            self.gauge("system.disk.free", disk.free)
            self.gauge("system.disk.percent", disk.percent)
            
            # Network IO
            net_io = psutil.net_io_counters()
            self.gauge("system.network.bytes_sent", net_io.bytes_sent)
            self.gauge("system.network.bytes_recv", net_io.bytes_recv)
            
            # Process metrics
            process = psutil.Process()
            self.gauge("process.cpu_percent", process.cpu_percent(interval=1))
            self.gauge("process.memory.rss", process.memory_info().rss)
            self.gauge("process.memory.vms", process.memory_info().vms)
            self.gauge("process.threads", process.num_threads())
            self.gauge("process.open_files", len(process.open_files()))
            
            # Add telemetry event
            self.telemetry(
                EventCategory.SYSTEM, 
                "system_metrics_collected",
                level=LogLevel.DEBUG,
                data={
                    "cpu_percent": cpu_percent,
                    "memory_percent": memory.percent,
                    "disk_percent": disk.percent,
                    "process_cpu_percent": process.cpu_percent(interval=0)
                }
            )
        
        except Exception as e:
            self.logger.error(f"Failed to collect system metrics: {e}", exc_info=True)
    
    def set_context(self, **kwargs) -> None:
        """
        Set context values for the current thread.
        
        Args:
            **kwargs: Key-value pairs to add to the context
        """
        if not hasattr(self.context, 'values'):
            self.context.values = {}
        
        for key, value in kwargs.items():
            self.context.values[key] = value
    
    def clear_context(self, *keys) -> None:
        """
        Clear context values for the current thread.
        
        Args:
            *keys: Keys to clear. If none provided, clears all context.
        """
        if not hasattr(self.context, 'values'):
            return
        
        if not keys:
            # Clear all context
            self.context.values = {}
        else:
            # Clear specific keys
            for key in keys:
                if key in self.context.values:
                    del self.context.values[key]
    
    def get_context(self) -> Dict[str, Any]:
        """
        Get the current thread's context combined with global context.
        
        Returns:
            Combined context dictionary
        """
        context = self.global_context.copy()
        
        # Add thread local context if available
        if hasattr(self.context, 'values'):
            context.update(self.context.values)
        
        return context
    
    def _add_log_context(self, extra: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
        """
        Prepare log record extra with context.
        
        Args:
            extra: Additional extra data for the log record
            
        Returns:
            Combined extra dictionary with context
        """
        result = {'context': self.get_context()}
        
        if extra:
            # If context is provided in extra, merge it with the existing context
            if 'context' in extra:
                result['context'].update(extra.pop('context'))
            
            # Add remaining extra fields
            result.update(extra)
        
        return result
    
    def debug(self, message: str, category: Optional[EventCategory] = None, 
              context: Optional[Dict[str, Any]] = None, **kwargs) -> None:
        """
        Log a debug message.
        
        Args:
            message: Log message
            category: Event category
            context: Additional context for this log
            **kwargs: Additional data for the log record
        """
        extra = self._add_log_context(kwargs)
        
        if context:
            extra['context'].update(context)
        
        if category:
            extra['context']['category'] = category.value
        
        self.logger.debug(message, extra=extra)
    
    def info(self, message: str, category: Optional[EventCategory] = None, 
             context: Optional[Dict[str, Any]] = None, **kwargs) -> None:
        """
        Log an info message.
        
        Args:
            message: Log message
            category: Event category
            context: Additional context for this log
            **kwargs: Additional data for the log record
        """
        extra = self._add_log_context(kwargs)
        
        if context:
            extra['context'].update(context)
        
        if category:
            extra['context']['category'] = category.value
        
        self.logger.info(message, extra=extra)
    
    def warning(self, message: str, category: Optional[EventCategory] = None, 
                context: Optional[Dict[str, Any]] = None, **kwargs) -> None:
        """
        Log a warning message.
        
        Args:
            message: Log message
            category: Event category
            context: Additional context for this log
            **kwargs: Additional data for the log record
        """
        extra = self._add_log_context(kwargs)
        
        if context:
            extra['context'].update(context)
        
        if category:
            extra['context']['category'] = category.value
        
        self.logger.warning(message, extra=extra)
    
    def error(self, message: str, category: Optional[EventCategory] = None, 
              context: Optional[Dict[str, Any]] = None, exc_info: bool = True, **kwargs) -> None:
        """
        Log an error message.
        
        Args:
            message: Log message
            category: Event category
            context: Additional context for this log
            exc_info: Whether to include exception info
            **kwargs: Additional data for the log record
        """
        extra = self._add_log_context(kwargs)
        
        if context:
            extra['context'].update(context)
        
        if category:
            extra['context']['category'] = category.value
        
        self.logger.error(message, exc_info=exc_info, extra=extra)
        
        # Also send an error telemetry event
        if self.enable_telemetry:
            error_data = {
                "message": message,
                "context": extra.get('context', {})
            }
            
            if exc_info and sys.exc_info()[0] is not None:
                error_type = sys.exc_info()[0].__name__
                error_message = str(sys.exc_info()[1])
                error_data["exception"] = {
                    "type": error_type,
                    "message": error_message
                }
            
            self.telemetry(
                EventCategory.ERROR if not category else category,
                "error",
                level=LogLevel.ERROR,
                data=error_data
            )
    
    def critical(self, message: str, category: Optional[EventCategory] = None, 
                context: Optional[Dict[str, Any]] = None, exc_info: bool = True, **kwargs) -> None:
        """
        Log a critical message.
        
        Args:
            message: Log message
            category: Event category
            context: Additional context for this log
            exc_info: Whether to include exception info
            **kwargs: Additional data for the log record
        """
        extra = self._add_log_context(kwargs)
        
        if context:
            extra['context'].update(context)
        
        if category:
            extra['context']['category'] = category.value
        
        self.logger.critical(message, exc_info=exc_info, extra=extra)
        
        # Also send a critical telemetry event
        if self.enable_telemetry:
            error_data = {
                "message": message,
                "context": extra.get('context', {})
            }
            
            if exc_info and sys.exc_info()[0] is not None:
                error_type = sys.exc_info()[0].__name__
                error_message = str(sys.exc_info()[1])
                error_data["exception"] = {
                    "type": error_type,
                    "message": error_message
                }
            
            self.telemetry(
                EventCategory.ERROR if not category else category,
                "critical_error",
                level=LogLevel.CRITICAL,
                data=error_data
            )
    
    def log_error(self, error: Union[MGError, Exception], category: Optional[EventCategory] = None,
                 context: Optional[Dict[str, Any]] = None) -> None:
        """
        Log an error object.
        
        Args:
            error: Error object to log
            category: Event category
            context: Additional context for this log
        """
        if isinstance(error, MGError):
            # Use the error's severity to determine log level
            if error.severity == ErrorSeverity.DEBUG:
                log_func = self.debug
            elif error.severity == ErrorSeverity.INFO:
                log_func = self.info
            elif error.severity == ErrorSeverity.WARNING:
                log_func = self.warning
            elif error.severity == ErrorSeverity.CRITICAL:
                log_func = self.critical
            else:
                log_func = self.error
            
            # Determine category
            if not category:
                # Map error category to event category
                if error.category == ErrorCategory.API:
                    event_category = EventCategory.API
                elif error.category == ErrorCategory.AUTHENTICATION:
                    event_category = EventCategory.AUTHENTICATION
                elif error.category == ErrorCategory.FILE:
                    event_category = EventCategory.FILE
                elif error.category == ErrorCategory.MODEL:
                    event_category = EventCategory.MODEL
                elif error.category == ErrorCategory.DATABASE:
                    event_category = EventCategory.DATABASE
                else:
                    event_category = EventCategory.ERROR
            else:
                event_category = category
            
            # Prepare context
            error_context = {}
            if context:
                error_context.update(context)
            
            error_context.update({
                "error_code": error.code,
                "error_category": error.category
            })
            
            if error.details:
                error_context["error_details"] = error.details
            
            # Log the error
            log_func(
                f"[{error.code}] {error.message}",
                category=event_category,
                context=error_context,
                exc_info=True
            )
        else:
            # Regular exception
            self.error(
                str(error),
                category=category or EventCategory.ERROR,
                context=context,
                exc_info=True
            )
    
    def counter(self, name: str, value: int = 1, tags: Optional[Dict[str, str]] = None) -> None:
        """
        Increment a counter metric.
        
        Args:
            name: Metric name
            value: Value to increment by
            tags: Tags for the metric
        """
        with self.metrics_lock:
            if name not in self.metrics["counters"]:
                self.metrics["counters"][name] = {
                    "value": 0,
                    "created_at": time.time(),
                    "tags": tags or {}
                }
            
            # Increment counter
            self.metrics["counters"][name]["value"] += value
            self.metrics["counters"][name]["updated_at"] = time.time()
            
            # Update tags if provided
            if tags:
                self.metrics["counters"][name]["tags"].update(tags)
    
    def gauge(self, name: str, value: float, tags: Optional[Dict[str, str]] = None) -> None:
        """
        Set a gauge metric.
        
        Args:
            name: Metric name
            value: Gauge value
            tags: Tags for the metric
        """
        with self.metrics_lock:
            # Update or create gauge
            self.metrics["gauges"][name] = {
                "value": value,
                "updated_at": time.time(),
                "tags": tags or {}
            }
            
            if "created_at" not in self.metrics["gauges"][name]:
                self.metrics["gauges"][name]["created_at"] = time.time()
    
    def histogram(self, name: str, value: float, tags: Optional[Dict[str, str]] = None) -> None:
        """
        Add a value to a histogram metric.
        
        Args:
            name: Metric name
            value: Value to add
            tags: Tags for the metric
        """
        with self.metrics_lock:
            if name not in self.metrics["histograms"]:
                self.metrics["histograms"][name] = {
                    "count": 0,
                    "sum": 0,
                    "min": float('inf'),
                    "max": float('-inf'),
                    "values": [],
                    "created_at": time.time(),
                    "tags": tags or {}
                }
            
            # Update histogram
            self.metrics["histograms"][name]["count"] += 1
            self.metrics["histograms"][name]["sum"] += value
            self.metrics["histograms"][name]["min"] = min(
                self.metrics["histograms"][name]["min"], value
            )
            self.metrics["histograms"][name]["max"] = max(
                self.metrics["histograms"][name]["max"], value
            )
            self.metrics["histograms"][name]["values"].append(value)
            self.metrics["histograms"][name]["updated_at"] = time.time()
            
            # Keep only the last 1000 values to limit memory usage
            if len(self.metrics["histograms"][name]["values"]) > 1000:
                self.metrics["histograms"][name]["values"].pop(0)
            
            # Update tags if provided
            if tags:
                self.metrics["histograms"][name]["tags"].update(tags)
    
    def timer(self, name: str, duration: float, tags: Optional[Dict[str, str]] = None) -> None:
        """
        Record a timing metric.
        
        Args:
            name: Metric name
            duration: Duration in seconds
            tags: Tags for the metric
        """
        # Timers are implemented as histograms
        self.histogram(name, duration, tags)
    
    @contextmanager
    def timing(self, name: str, tags: Optional[Dict[str, str]] = None) -> None:
        """
        Context manager for timing a block of code.
        
        Args:
            name: Metric name
            tags: Tags for the metric
            
        Yields:
            None
        """
        start_time = time.time()
        try:
            yield
        finally:
            duration = time.time() - start_time
            self.timer(name, duration, tags)
    
    def summary(self, name: str, value: float, tags: Optional[Dict[str, str]] = None) -> None:
        """
        Update a summary metric.
        
        Args:
            name: Metric name
            value: Value to add
            tags: Tags for the metric
        """
        with self.metrics_lock:
            if name not in self.metrics["summaries"]:
                self.metrics["summaries"][name] = {
                    "count": 0,
                    "sum": 0,
                    "created_at": time.time(),
                    "tags": tags or {}
                }
            
            # Update summary
            self.metrics["summaries"][name]["count"] += 1
            self.metrics["summaries"][name]["sum"] += value
            self.metrics["summaries"][name]["updated_at"] = time.time()
            
            # Update tags if provided
            if tags:
                self.metrics["summaries"][name]["tags"].update(tags)
    
    def get_metrics(self) -> Dict[str, Any]:
        """
        Get all metrics.
        
        Returns:
            Dictionary with all metrics
        """
        with self.metrics_lock:
            return {
                "counters": self.metrics["counters"].copy(),
                "gauges": self.metrics["gauges"].copy(),
                "histograms": self.metrics["histograms"].copy(),
                "summaries": self.metrics["summaries"].copy()
            }
    
    def get_metric(self, name: str, metric_type: MetricType) -> Optional[Dict[str, Any]]:
        """
        Get a specific metric.
        
        Args:
            name: Metric name
            metric_type: Metric type
            
        Returns:
            Metric data or None if not found
        """
        with self.metrics_lock:
            if metric_type == MetricType.COUNTER:
                return self.metrics["counters"].get(name)
            elif metric_type == MetricType.GAUGE:
                return self.metrics["gauges"].get(name)
            elif metric_type == MetricType.HISTOGRAM:
                return self.metrics["histograms"].get(name)
            elif metric_type == MetricType.SUMMARY:
                return self.metrics["summaries"].get(name)
            elif metric_type == MetricType.TIMER:
                return self.metrics["histograms"].get(name)  # Timers are stored as histograms
            else:
                return None
    
    def reset_metrics(self) -> None:
        """Reset all metrics."""
        with self.metrics_lock:
            self.metrics = {
                "counters": {},
                "gauges": {},
                "histograms": {},
                "summaries": {}
            }
    
    def telemetry(
        self, 
        category: EventCategory, 
        event_type: str, 
        level: LogLevel = LogLevel.INFO,
        data: Optional[Dict[str, Any]] = None
    ) -> None:
        """
        Submit a telemetry event.
        
        Args:
            category: Event category
            event_type: Type of event
            level: Log level for the event
            data: Event data
        """
        if not self.enable_telemetry:
            return
        
        event = {
            "category": category.value,
            "type": event_type,
            "level": level.value,
            "timestamp": datetime.utcnow().isoformat(),
            "context": self.get_context()
        }
        
        if data:
            event["data"] = data
        
        try:
            # Don't block if queue is full
            self.telemetry_queue.put(event, block=False)
        except queue.Full:
            self.logger.warning("Telemetry queue is full, event dropped")
    
    def shutdown(self) -> None:
        """Shutdown the telemetry system and flush pending events."""
        if self.enable_telemetry:
            # Flush telemetry queue
            self.logger.info("Shutting down telemetry system")
            
            try:
                events = []
                while not self.telemetry_queue.empty():
                    try:
                        event = self.telemetry_queue.get_nowait()
                        events.append(event)
                        self.telemetry_queue.task_done()
                    except queue.Empty:
                        break
                
                if events:
                    self._export_events(events)
            except Exception as e:
                self.logger.error(f"Error during telemetry shutdown: {e}", exc_info=True)


# Create a singleton instance
_instance = None

def get_telemetry(
    app_name: str = "morphguard",
    log_dir: Optional[str] = None,
    telemetry_dir: Optional[str] = None,
    log_level: int = logging.INFO,
    console_logging: bool = True,
    file_logging: bool = True,
    enable_telemetry: bool = True
) -> TelemetryManager:
    """
    Get the global telemetry manager instance.
    
    Args:
        app_name: Application name
        log_dir: Directory for log files
        telemetry_dir: Directory for telemetry data
        log_level: Default log level
        console_logging: Whether to log to console
        file_logging: Whether to log to file
        enable_telemetry: Whether to enable telemetry
        
    Returns:
        TelemetryManager instance
    """
    global _instance
    
    if _instance is None:
        _instance = TelemetryManager(
            app_name=app_name,
            log_dir=log_dir,
            telemetry_dir=telemetry_dir,
            log_level=log_level,
            console_logging=console_logging,
            file_logging=file_logging,
            enable_telemetry=enable_telemetry
        )
    
    return _instance