Advanced Log Techniques | Logs | Dynatrace Tutorial

Introduction

Logging is a critical aspect of application performance monitoring. Advanced log techniques enhance the capability to analyze and troubleshoot applications effectively. In this tutorial, we will explore various advanced logging techniques specifically within the context of Dynatrace.

1. Structured Logging

Structured logging involves creating logs that are easily readable by machines. This technique allows for better querying and analysis of logs. Instead of logging plain text, structured logs use formats like JSON or XML.

Example of structured logging in JSON:

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

In Dynatrace, ensure your application is configured to output logs in a structured format to leverage advanced analysis features.

2. Correlation IDs

Correlation IDs help trace requests across distributed systems. By including a unique identifier in every log entry associated with a single request, you can easily track its journey through your services.

Example of logging with a correlation ID:

{ "timestamp": "2023-10-01T12:01:00Z", "correlationId": "abc123", "level": "ERROR", "message": "Failed to process payment" }

In Dynatrace, you can filter logs by correlation IDs to quickly diagnose issues related to specific transactions.

3. Log Enrichment

Log enrichment involves adding additional context to your logs. This can include user context, environment details, or application state. Enriched logs provide deeper insights during analysis.

Example of enriched logging:

{ "timestamp": "2023-10-01T12:02:00Z", "level": "INFO", "message": "Data processed", "userId": 12345, "sessionId": "xyz789", "environment": "production" }

Dynatrace allows you to visualize this enriched data, making it easier to identify performance bottlenecks and user impacts.

4. Centralized Logging

Centralized logging is the practice of aggregating logs from multiple services or instances into a single location. This approach simplifies log management and analysis.

Using a centralized logging service:

# Using Fluentd to send logs to Elasticsearch fluentd -c /etc/fluent.conf

In Dynatrace, you can integrate with various logging frameworks and services to centralize your logs, enabling comprehensive search and analytics capabilities.

5. Log Rotation and Retention

Log rotation is the process of managing log files by regularly archiving and deleting older logs. Proper log retention policies ensure that logs are available for analysis without consuming excessive storage.

Example configuration for log rotation in Linux:

/var/log/myapp.log { daily rotate 7 compress missingok notifempty create 0640 myuser mygroup }

In Dynatrace, configure log retention settings to balance the need for historical data with storage constraints.

Conclusion

Employing advanced log techniques in Dynatrace significantly enhances your ability to troubleshoot and monitor applications. By using structured logging, correlation IDs, log enrichment, centralized logging, and proper log rotation, you can gain valuable insights into your application's performance and health.

Advanced Log Techniques in Dynatrace