Observability through Distributed Tracing

Distributed tracing is a modern observability technique that monitors and records the journey of individual requests as they navigate the services and components within a distributed system. As systems become more complex, it gets harder for operations teams to keep up. Distributed tracing helps by automatically showing request paths, making it easier to maintain visibility and control.

Tip

To learn more about exploring and navigating the Traces app, please refer to the ITRS Analytics Traces app documentation or watch the product demo tour.

Understanding Distributed Tracing Copied

Distributed tracing is a method for tracking how a single user request moves through various connected IT systems and services. It’s similar to following a package through each stop on its delivery route. This approach helps teams quickly identify where things go wrong by showing exactly which part of the system caused a slowdown or failure, making it easier to resolve issues.

While some organizations may hesitate to adopt tracing because not every part of a transaction can be instrumented, this hesitation should not be a barrier to implementation. Even a small amount of instrumentation can give valuable insights and benefits, encouraging other teams to get on board. Distributed tracing simplifies this task through several key capabilities.

Detailed end-to-end insights Copied

Distributed tracing offers a complete view of a request’s lifecycle as it moves through the system. This makes it significantly easier to identify where and why a failure occurs. By tracing the exact path of a request, distributed tracing helps narrow down the root cause of issues, enabling teams to focus their efforts on fixing the specific service.

Performance analysis Copied

Distributed tracing captures the latency of each service that a request interacts with, allowing teams to identify underperforming components. This visibility helps link performance with specific services or dependencies.

Discovering dependencies Copied

Distributed tracing reveals interactions between services, making it easier to uncover hidden or undocumented dependencies. This is essential for understanding and identifying the root cause of issues.

These valuable insights come from collecting many request traces and analyzing them for patterns. By following the full path of each request and comparing it with others, teams can have a clearer understanding of what’s happening in the system and identify problems more efficiently.

Key terms in Distributed Tracing Copied

Span Copied

A Span represents a single unit of work within a system, such as a function call or database query, and includes metadata like duration, status, and context.

Spans can be nested to show parent-child relationships, enabling detailed insight into sub-operations of a request.

Trace Copied

A Trace provides a complete view of a transaction or workflow as it moves through multiple services, composed of one or more Spans connected by context propagation.

Traces illustrate the end-to-end journey of a request, using the relationships between Spans to map the full execution path across systems.

Span Statistics Copied

Each individual Span ingested into the system is grouped into common namespace, service, instance, and operation.

Statistics are maintained on the number of spans, error count, and latency. These metrics and histograms can be used by other applications.

Trace Sampling Copied

Efficient storage of traces means that not every trace observed by the system can be stored.

The ITRS trace sampling strategy ensures that all traces containing errors and traces considered slow are stored, along with a representative 1% sample of the remaining traces.