Trace Analytics

When a single user action can easily trigger a complicated series of knock-on events across front-end and back-end services, trace analytics allows you to discover any issues that may have happened within this sequence of events.

This series of events can be referred to as traces. A set of traces is called a distributed transaction. As one of the main pillars of observability (logs, metrics, and traces), tracing is vital for monitoring transaction level tracking. Because of the limitations of manual debugging for analyzing traces, it is beneficial to use a robust analytics platform for analyzing what can often be massive amounts of data. Logit.io aims to help you discover patterns versus outliers, establish correlations, and derive insights that would otherwise be buried within individual traces.

Common analytics use cases include service dependency graphs, critical path analysis, error analysis, latency analysis, and anomaly detection. In order to troubleshoot high latency or error requests, trace analytics can be used by engineers. Additionally, trace analytics can determine the root cause of code issues by breaking down time spent on CPU, garbage collection, lock contention, and improving CPU utilization. While logs and metrics remain significant, ultimately it's going to be tracing that will solve the transaction processing issues that your system is encountering.

A trace tells a complete story about a request or transaction, whereas metrics provide a high-level view of whether the system works as expected without explaining why. In contrast, logs provide fine-grained details about events such as timestamps and ordering of events.

Using traces over logs is often said to be more sophisticated because you are often able to work with more added context against your events. Trace data can be filtered and visualized based on application, subsystem, service, and action. By using Logit.io, you can analyze tracing data grouped by service to pinpoint exactly where a problem originated by filtering for traces exceeding a given latency.

With observability traces seamlessly integrated into Logit.io's platform, you gain even deeper insights into the behavior of your system, allowing for more precise troubleshooting and optimization.

With Observability tracing, you're not just monitoring your systems; you're gaining deep, granular insights into every aspect of your applications, infrastructure, and user interactions. Similar to gaining a comprehensive map of your entire system's behavior in real time, allowing you to pinpoint bottlenecks, optimize performance and deliver a seamless user experience like never before.

Observability tracing doesn't just stop at surface-level metrics. It goes beyond traditional monitoring by providing rich, contextual data that connects the dots between different components of your system. From microservices to distributed architectures, Observability Tracing empowers you to understand the intricate relationships between various elements, making troubleshooting a breeze and enabling proactive decision-making.