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Maximize your observability with tracing tools to track requests, identify bottlenecks, and optimize system performance across services.

OpenTelemetry and OpenTracing are two closely connected open-source projects that enhance observability in modern distributed systems. They are designed to instrument application code for generating telemetry data. OpenTelemetry is a comprehensive, vendor-neutral framework that helps capture various types of telemetry data, while OpenTracing focuses specifically on tracing and provides a way to instrument applications for that purpose.

Learn how to implement OpenTelemetry in Rust for effective observability, including tracing, metrics, and debugging in your applications.

Over the past year, a lot of work has gone into making Prometheus work better with OpenTelemetry—a move that reflects the growing number of engineers and developers that rely on both open source projects. Historically, Prometheus users have faced a number of challenges when trying to work with OpenTelemetry (and vice versa).

In the software space, we spend a lot of time defining the terminology that describes our roles, implementations, and ways of working. These terms help us share fundamental concepts that improve our software and let us better manage our software solutions. To optimize your software solutions and help you implement system observability, this blog post will share the key differences between logs vs traces.

Earlier this year, we introduced relational fields. Relational fields enable you to query spans based on their relationship to one other within a trace, rather than only in isolation. We’ve now expanded this feature and introduced four new prefixes: child., none., any2., and any3.. Previously, you could use root., parent., and any. to query on the root span of your target span’s trace, the parent span of your target span, and any other span in the same trace as your target span.

Learn to monitor host metrics with OpenTelemetry. Discover setup tips, common pitfalls, and best practices for effective observability.

Jaeger has emerged as a crucial tool in the modern distributed systems landscape, offering powerful tracing capabilities that help organizations understand and optimize their microservices architectures. This comprehensive guide explores everything from basic concepts to advanced implementations, providing you with the knowledge needed to effectively implement and utilize Jaeger in your environment.

As teams adopt OpenTelemetry (OTel) to instrument their systems in a vendor-neutral way, they often face a challenge in effectively tracing activity throughout their entire stack, from frontend user interactions to backend services and databases. While OTel enables basic tracing, teams still need a way to access advanced capabilities like continuous profiling to adequately optimize performance and troubleshoot issues in their applications.