At Grafana Labs, we love tracing, which is why we’ve been hard at work on Grafana Tempo, an open source, highly scalable distributed tracing backend. Tempo just had its 2.0 release. In conjunction with that release, we are excited to show off TraceQL — a powerful new query language designed for distributed tracing. In this blog, we’ll provide an overview of why we created TraceQL, how it works, how you can put it to use today, and what we have planned for future iterations.

OpenTelemetry (OTel) is an open source, vendor-neutral observability framework that supplies APIs, SDKs, and tools for the instrumentation of cloud-native applications and services. OTel enables you to collect metrics, logs, and traces from a variety of sources and route them to various backends. By itself, however, it can’t help you analyze this data or correlate telemetry from different parts of your stack.

In the previous article, we learned what distributed tracing is, why it is necessary, how to do tracing, encountered challenges with existing tracing tools, and finally discovered that there is a more mature option available for the industry to adopt in terms of telemetry and observability. In this article, we will be trying to understand OpenTelemetry in more depth. To begin, we will examine how OpenTelemetry addresses some of the issues confronting the observability ecosystem.

The OpenTelemetry (OTel) project is an open source initiative with the goal of providing vendor-neutral standards and tools that enable users to collect telemetry from any source in their environment and send it to any backend. A core tenet of Datadog is to provide a single, unified platform for customers to easily collect and monitor all of their observability data, regardless of where it comes from.

Have you heard about traces? Most likely, yes! Do you confuse it with auditing? Hope not. Today, we're going to talk about tracing, specifically “Distributed Tracing,” and do a deep dive into it. Once we’re familiar with distributed tracing, we will show you how to implement it with OpenTelemetry - a new-age observability framework.

Kubernetes makes it easier for businesses to automate software deployment and manage applications in the cloud at scale. However, if you’ve ever deployed a cloud native app, you know how difficult it can be to keep it healthy and predictable. DevOps teams and SREs often use distributed tracing to get the insights they need to learn about application health and performance.

OpenTelemetry has gained significant adoption in the past year. This blog is about the common Otel demo application, but you can refer to this primer about OTel in general. Although it has gained recognition in the industry, there are still many people who haven’t started using OpenTelemetry. If you are interested in exploring its capabilities but you’re unsure where to start, keep reading.

Unlock the full potential of your observability stack with continuous profiling Identifying performance bottlenecks and wasteful computations can be a complex and challenging task, particularly in modern cloud-native environments. As the complexity of cloud-native environments increases, so does the need for effective observability solutions.

How is Grafana like an invisibility cloak? At Adobe, it’s one of just four tools they’re using to build observability directly into their CI/CD pipeline, making it essentially invisible — but nonetheless impactful — to thousands of developers across the organization who use it in their day-to-day lives.