JSON Logging Patterns

Introduction

JSON logging patterns are essential for observability in modern applications. They provide a structured way to log information that can be easily parsed and analyzed, making debugging and monitoring more efficient.

Key Concepts

• JSON (JavaScript Object Notation): A lightweight data-interchange format that is easy for humans to read and write and easy for machines to parse and generate.
• Structured Logging: A logging approach that uses a consistent structure or format for log entries, making it easier to analyze and query logs.
• Observability: The ability to measure the internal state of a system by examining its outputs, often through logging, metrics, and tracing.

Logging Patterns

1. Basic JSON Structure

A typical JSON log entry might look like this:

{
    "timestamp": "2023-10-01T12:00:00Z",
    "level": "INFO",
    "message": "User logged in",
    "userId": "12345",
    "sessionId": "abcde12345"
}

2. Error Logging

Logging errors with detailed context can help in troubleshooting:

{
    "timestamp": "2023-10-01T12:05:00Z",
    "level": "ERROR",
    "message": "Database connection failed",
    "error": {
        "code": "DB_CONN_ERR",
        "details": "Connection timed out",
        "stackTrace": "at connect(...)\nat dbQuery(...)"
    }
}

3. Performance Metrics

Logging performance-related metrics can be instrumental:

{
    "timestamp": "2023-10-01T12:10:00Z",
    "level": "INFO",
    "message": "API response time",
    "api": "/users",
    "responseTimeMs": 150
}

4. User Activity Logging

Tracking user activities provides insights into usage patterns:

{
    "timestamp": "2023-10-01T12:15:00Z",
    "level": "INFO",
    "message": "User performed action",
    "userId": "12345",
    "action": "Viewed profile",
    "details": {
        "profileId": "67890"
    }
}

Best Practices

• Always include a timestamp in your logs.
• Use appropriate log levels (e.g., INFO, WARN, ERROR) to filter logs easily.
• Ensure JSON structure is consistent across all log entries.
• Log contextual information to aid in debugging.
• Use a centralized logging solution to aggregate and analyze logs.

FAQ