Structure Company Log For Free

Structured logging takes the contents of a log and puts them into a structured format. A structured log has a clearly identified event number for reference, attributes, and values that comprise records and additional contextual data.

Examples of semi-structured data include emails, XML files, JSON files, social media posts, and log files. These types of data contain both structured and unstructured information, such as a mixture of predefined fields & free-form text.

The problem with log files is they are unstructured text data. This makes it hard to query them for any sort of useful information. As a developer, it would be nice to be able to filter all logs by a certain customer # or transaction #.

Structured logs are structured in a format like JSON or XML and usually contain well-defined and contextual information needed for diagnosis, including error messages and other properties like event number, hostname, timestamp, and request.

Best Practices for Structured Logging? Some of the best practices are: Always use a consistent format if you choose JSON, for example. You should stick to that one format across your application. This makes it easier to parse the collected data, analyze logs and provide timely feedback.

To summarize, the best practices for log formatting include using a consistent format, including timestamps, using descriptive log levels, avoiding cluttering logs with irrelevant information, using structured logging, including relevant context information, and using log rotation.

JSON format JSON is a lightweight data exchange format that is easy for both humans and machines to read and write. It represents data as key-value pairs and arrays, making it an excellent choice for structured logging due to its simplicity and widespread support.