Manually deploying and managing OpenTelemetry components in a Kubernetes environment can be a complex and time-consuming task. It involves creating various Kubernetes resources, setting up configurations, and ensuring the components are properly integrated with the applications.

The Splunk Add-on for OpenTelemetry Collector is a variation of the Splunk Distribution of the OpenTelemetry Collector that simplifies metrics and traces data collection, configuration and management. Since it is an add-on, users can deploy it alongside Universal Forwarders using tools like Deployment Server to start collecting high-fidelity metrics and traces from 1000s of their hosts easily. We’re happy to announce that the Add-On is now generally available in Splunkbase.

The OpenTelemetry project provides many different components and instrumentations that support different languages and telemetry signals. However, new users often find it hard to pick the right ones and configure them properly for their specific use cases. For this reason, OpenTelemetry defines the concept of a distribution, which is a tailored and customized version of OpenTelemetry components. Here at Grafana Labs, we are all-in on OpenTelemetry.

Open Telemetry (OTel) is an open source observability framework that has garnered significant attention for its powerful capabilities in monitoring metrics, logs and traces.. It is second only to Kubernetes in the CNCF velocity chart with contributions being made from major players in the cloud industry, and has a growing community helping build out a thriving ecosystem.

The Grafana LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics) offers the freedom and flexibility for monitoring application performance. But we’ve also heard from many of our users and customers that you need a solution that makes it easier and faster to get started with application monitoring.

When all your IT systems, your apps and software, and your people are spread out, you need a way to see what’s happening in all these minute and separate interactions. That’s exactly what distributed tracing does. Distributed tracing is a way to tracking requests in applications and how those requests move from users and frontend devices through to backend services and databases.

An Essential Guide to OpenTelemetry In today’s expeditious, highly distributed software landscape, achieving true observability is no simple task. As you strive to understand how your applications and services perform and behave, you face multiple challenges. Moreover, you need to instrument applications and services that generate data effectively, have a reliable means to transmit it, and, most importantly, find a way to visualize and derive insights from it.

What are OpenTelemetry, and OpenCensus and how to migrate from OpenCensus to OpenTelemetry.

In telemetry jargon, a pipeline is a directed acyclic graph (DAG) of nodes that carry emitted signals from an application to a backend. In an OpenTelemetry Collector, a pipeline is a set of receivers that collect signals, runs them through processors, and then emits them through configured exporters. This blog post hopes to simplify both types of pipelines by using an OpenTelemetry extension called the Headers Setter.