What is application logging (application logging)?

Purpose and importance of logging

The main purpose of logging is to provide developers, system administrators and support teams with detailed information about what was happening in the application at a specific point in time. Logs are often the first and most important source of information when diagnosing production errors. They allow tracking the flow of execution, identifying the causes of problems, monitoring key business events and analyzing user behavior patterns or potential security incidents. Without proper logging, understanding and troubleshooting complex systems would be extremely difficult or impossible.

What should be logged?

Deciding exactly what to log is crucial to the usability of the logging system. A balance must be struck between logging too little information (which makes diagnosis difficult) and logging too much (which generates information noise and overloads the system). Typical information worth logging is:

• Errors and exceptions: detailed information about error occurrences, including error messages, stack traces and execution context.
• Important business events: Key steps in the business processes executed by the application (e.g., placing an order, making a payment, user login).
• Requests and responses: Information about incoming requests (e.g., HTTP) and responses provided by the application (e.g., status codes, response time).
• State Changes: Logging significant changes in the state of an application or data.
• Diagnostic information: Additional information to aid in debugging (e.g., variable values at key moments), often logged at a lower level of detail (e.g., DEBUG).
• Audit and security information: Events related to authentication, authorization, access attempts or configuration changes.

Log Levels

To manage the amount of logs generated, different levels of logging detail (log levels) are used. The most common levels are (from least to most detailed): FATAL, ERROR, WARN (Warning), INFO (Information), DEBUG, TRACE. This allows you to flexibly configure what messages to log depending on your environment (e.g., in production you log only errors and warnings, and in a development environment you log debug information as well).

Log format and structure

Logs should be saved in a consistent and structured format (e.g. JSON, logfmt), which facilitates their automatic parsing and analysis by log management systems. At a minimum, each log entry should contain: a timestamp (timestamp), logging level, message content and, if possible, additional context (e.g., user ID, request ID, module name).

Log management tools and systems

In modern distributed systems (e.g., microservices-based), logs from multiple instances of applications and services must be centrally aggregated and analyzed. Specialized log management systems, such as:

• ELK Stack / OpenSearch: popular technology stack (Elasticsearch/OpenSearch for storage and search, Logstash/Fluentd for collection and processing, Kibana for visualization).
• Splunk: a commercial platform for analyzing machine data, including logs.
• Graylog: An open source log management platform.
• Loki (Grafana): A log aggregation system optimized for integration with the Prometheus metrics and visualization system in Grafana.
• Cloud services: cloud providers offer their own log management services (e.g. AWS CloudWatch Logs, Azure Monitor Logs, Google Cloud Logging).

Summary

Application logging is an essential engineering practice that provides key information needed to diagnose problems, monitor performance and ensure the security of IT systems. Effective logging requires thoughtful selection of information to be logged, the use of appropriate levels of detail, a structured format, and the use of central log management systems for distributed systems.