log/doc/logging-guide.md

Logging Guide

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Best practices and patterns for effective logging with the lixenwraith/log package.

Table of Contents

• Log Levels
• Structured Logging
• Output Formats
• Function Tracing
• Error Handling
• Performance Considerations
• Logging Patterns

Log Levels

Understanding Log Levels

The logger uses numeric levels for efficient filtering:

Level	Name	Value	Use Case
Debug	LevelDebug	-4	Detailed information for debugging
Info	LevelInfo	0	General informational messages
Warn	LevelWarn	4	Warning conditions
Error	LevelError	8	Error conditions

Level Selection Guidelines

// Debug: Detailed execution flow
logger.Debug("Cache lookup", "key", cacheKey, "found", found)

// Info: Important business events
logger.Info("Order processed", "order_id", orderID, "amount", 99.99)

// Warn: Recoverable issues
logger.Warn("Retry attempt", "service", "payment", "attempt", 3)

// Error: Failures requiring attention
logger.Error("Database query failed", "query", query, "error", err)

Setting Log Level

// Development: See everything
logger.InitWithDefaults("level=-4")  // Debug and above

// Production: Reduce noise
logger.InitWithDefaults("level=0")   // Info and above

// Critical systems: Errors only
logger.InitWithDefaults("level=8")   // Error only

Structured Logging

Key-Value Pairs

Always use structured key-value pairs for machine-parseable logs:

// Good: Structured data
logger.Info("User login",
    "user_id", user.ID,
    "email", user.Email,
    "ip", request.RemoteAddr,
    "timestamp", time.Now(),
)

// Avoid: Unstructured strings
logger.Info(fmt.Sprintf("User %s logged in from %s", user.Email, request.RemoteAddr))

Consistent Field Names

Use consistent field names across your application:

// Define common fields
const (
    FieldUserID    = "user_id"
    FieldRequestID = "request_id"
    FieldDuration  = "duration_ms"
    FieldError     = "error"
)

// Use consistently
logger.Info("API call",
    FieldRequestID, reqID,
    FieldUserID, userID,
    FieldDuration, elapsed.Milliseconds(),
)

Context Propagation

type contextKey string

const requestIDKey contextKey = "request_id"

func logWithContext(ctx context.Context, logger *log.Logger, level string, msg string, fields ...any) {
    // Extract common fields from context
    if reqID := ctx.Value(requestIDKey); reqID != nil {
        fields = append([]any{"request_id", reqID}, fields...)
    }
    
    switch level {
    case "info":
        logger.Info(msg, fields...)
    case "error":
        logger.Error(msg, fields...)
    }
}

Output Formats

Text Format (Human-Readable)

Default format for development and debugging:

2024-01-15T10:30:45.123456789Z INFO User login user_id=42 email="user@example.com" ip="192.168.1.100"
2024-01-15T10:30:45.234567890Z WARN Rate limit approaching user_id=42 requests=95 limit=100

Configuration:

logger.InitWithDefaults(
    "format=txt",
    "show_timestamp=true",
    "show_level=true",
)

JSON Format (Machine-Parseable)

Ideal for log aggregation and analysis:

{"time":"2024-01-15T10:30:45.123456789Z","level":"INFO","fields":["User login","user_id",42,"email","user@example.com","ip","192.168.1.100"]}
{"time":"2024-01-15T10:30:45.234567890Z","level":"WARN","fields":["Rate limit approaching","user_id",42,"requests",95,"limit",100]}

Configuration:

logger.InitWithDefaults(
    "format=json",
    "show_timestamp=true",
    "show_level=true",
)

Function Tracing

Using Trace Methods

Include call stack information for debugging:

func processPayment(amount float64) error {
    logger.InfoTrace(1, "Processing payment", "amount", amount)
    
    if err := validateAmount(amount); err != nil {
        logger.ErrorTrace(3, "Payment validation failed", 
            "amount", amount, 
            "error", err,
        )
        return err
    }
    
    return nil
}

Output includes function names:

2024-01-15T10:30:45.123456789Z INFO processPayment Processing payment amount=99.99
2024-01-15T10:30:45.234567890Z ERROR validateAmount -> processPayment -> main Payment validation failed amount=-10 error="negative amount"

Trace Depth Guidelines

• 1: Current function only
• 2-3: Typical for error paths
• 4-5: Deep debugging
• 10: Maximum supported depth

Error Handling

Logging Errors

Always include error details in structured fields:

if err := db.Query(sql); err != nil {
    logger.Error("Database query failed",
        "query", sql,
        "error", err.Error(),  // Convert to string
        "error_type", fmt.Sprintf("%T", err),
    )
    return fmt.Errorf("query failed: %w", err)
}

Error Context Pattern

func (s *Service) ProcessOrder(orderID string) error {
    logger := s.logger  // Use service logger
    
    logger.Info("Processing order", "order_id", orderID)
    
    order, err := s.db.GetOrder(orderID)
    if err != nil {
        logger.Error("Failed to fetch order",
            "order_id", orderID,
            "error", err,
            "step", "fetch",
        )
        return fmt.Errorf("fetch order %s: %w", orderID, err)
    }
    
    if err := s.validateOrder(order); err != nil {
        logger.Warn("Order validation failed",
            "order_id", orderID,
            "error", err,
            "step", "validate",
        )
        return fmt.Errorf("validate order %s: %w", orderID, err)
    }
    
    // ... more processing
    
    logger.Info("Order processed successfully", "order_id", orderID)
    return nil
}

Performance Considerations

Minimize Allocations

// Avoid: String concatenation
logger.Info("User " + user.Name + " logged in")

// Good: Structured fields
logger.Info("User logged in", "username", user.Name)

// Avoid: Sprintf in hot path
logger.Debug(fmt.Sprintf("Processing item %d of %d", i, total))

// Good: Direct fields
logger.Debug("Processing item", "current", i, "total", total)

Conditional Expensive Operations

// Only compute expensive values if they'll be logged
if logger.IsEnabled(log.LevelDebug) {
    stats := computeExpensiveStats()
    logger.Debug("Detailed statistics", "stats", stats)
}

Batch Related Logs

// Instead of logging each item
for _, item := range items {
    logger.Debug("Processing", "item", item)  // Noisy
}

// Log summary information
logger.Info("Batch processing",
    "count", len(items),
    "first_id", items[0].ID,
    "last_id", items[len(items)-1].ID,
)

Internal Error Handling

The logger may encounter internal errors during operation (e.g., file rotation failures, disk space issues). By default, writing these errors to stderr is disabled, but can be enabled in configuration for diagnostic purposes.

Controlling Internal Error Output

For applications requiring clean stderr output, keep internal error messages disabled:

logger.InitWithDefaults(
    "internal_errors_to_stderr=false",  // Suppress internal diagnostics
)

When to Keep Internal Errors Disabled

Consider disabling internal error output for:

• CLI tools producing structured output
• Daemons with strict stderr requirements
• Applications with custom error monitoring
• Container environments with log aggregation

Monitoring Without stderr

When internal errors are disabled, monitor logger health using:

1. Heartbeat monitoring: Detect issues via heartbeat logs

   logger.InitWithDefaults(
       "internal_errors_to_stderr=false",
       "heartbeat_level=2",  // Include disk stats
       "heartbeat_interval_s=60",
   )
   

2. Check for dropped logs: The logger tracks dropped messages

   // Dropped logs appear in regular log output when possible
   // Look for: "Logs were dropped" messages
   

3. External monitoring: Monitor disk space and file system health independently

Logging Patterns

Request Lifecycle

func handleRequest(w http.ResponseWriter, r *http.Request) {
    start := time.Now()
    reqID := generateRequestID()
    
    logger.Info("Request started",
        "request_id", reqID,
        "method", r.Method,
        "path", r.URL.Path,
        "remote_addr", r.RemoteAddr,
    )
    
    defer func() {
        duration := time.Since(start)
        logger.Info("Request completed",
            "request_id", reqID,
            "duration_ms", duration.Milliseconds(),
        )
    }()
    
    // Handle request...
}

Background Job Pattern

func (w *Worker) processJob(job Job) {
    logger := w.logger
    
    logger.Info("Job started",
        "job_id", job.ID,
        "type", job.Type,
        "scheduled_at", job.ScheduledAt,
    )
    
    ctx, cancel := context.WithTimeout(context.Background(), 5*time.Minute)
    defer cancel()
    
    if err := w.execute(ctx, job); err != nil {
        logger.Error("Job failed",
            "job_id", job.ID,
            "error", err,
            "duration_ms", time.Since(job.StartedAt).Milliseconds(),
        )
        return
    }
    
    logger.Info("Job completed",
        "job_id", job.ID,
        "duration_ms", time.Since(job.StartedAt).Milliseconds(),
    )
}

Audit Logging

func (s *Service) auditAction(userID string, action string, resource string, result string) {
    s.auditLogger.Info("Audit event",
        "timestamp", time.Now().UTC(),
        "user_id", userID,
        "action", action,
        "resource", resource,
        "result", result,
        "ip", getCurrentIP(),
        "session_id", getSessionID(),
    )
}

// Usage
s.auditAction(user.ID, "DELETE", "post:123", "success")

Metrics Logging

func (m *MetricsCollector) logMetrics() {
    ticker := time.NewTicker(1 * time.Minute)
    defer ticker.Stop()
    
    for range ticker.C {
        stats := m.collect()
        
        m.logger.Info("Metrics snapshot",
            "requests_per_sec", stats.RequestRate,
            "error_rate", stats.ErrorRate,
            "p50_latency_ms", stats.P50Latency,
            "p99_latency_ms", stats.P99Latency,
            "active_connections", stats.ActiveConns,
            "memory_mb", stats.MemoryMB,
        )
    }
}

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