Group your logs to analyze processes with Log Transaction Queries

Modern applications generate large volumes of logs daily, providing valuable insights into system states and service performance. However, effectively analyzing root causes requires viewing these logs within the context of complex, distributed systems. To address this challenge, Datadog has developed Transaction Queries, which simplify log aggregation based on shared attributes to expose context and calculate key metrics for specific processes or user journeys. This feature enables users to create end-to-end context from their logs, harnessing them for efficient troubleshooting across various use cases such as e-commerce data, web user activity, financial transactions, authentication sessions, and CI/CD pipelines. By grouping logs by primary identifier values and optional boundary conditions, users can quickly identify problematic areas and investigate the root causes of issues within their applications.