Part7: Getting Started with Grafana Tempo and Opentelemetry Instrumentation

Hello everyone. In the seventh part of the Grafana LGTM Stack course, we will start by discussing the concepts of trace and span and then talk about the role of tracing in the monitoring stack. After that, you will get familiar with Grafana Tempo, its architecture, and its components. Next, we will proceed with the installation and deployment of Tempo on a Kubernetes cluster and configure its components. The first part of the tracing pipeline is instrumenting the application, so we will learn about the concept of instrumentation. Finally, we will write a simple application using Python Flask and add instrumentation points to it. To enable auto-instrumentation for our application, we will use the OpenTelemetry Operator and install it on the Kubernetes cluster to take advantage of auto-instrumentation. 00:00:00 Tracing Concepts 00:03:00 What is Grafana Tempo 00:05:16 Tracing Is One Of the Pillars Of Observability 00:07:49 Tempo Architecture 00:10:50 Installing Tempo Distributed and Configuring Its Components Using Tempo Helm Chart 00:17:22 Tracing Pipeline Overview 00:20:08 Concepts Of OpenTelemetry Instrumentation 00:24:00 Getting Familiar With The Tracing Demo Application 00:34:03 Working With Opentelemetry Kubernetes Operator To Auto-Instrument Our Application You can find all the resources from here https://github.com/devopshobbies/grafana_lgtm ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ You can Follow Mohammad from on other platforms: Linkedin : https://www.linkedin.com/in/mohammad-madanipour-87149bb3 Github: https://github.com/mohammadll ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ You can follow our Channel on other platforms: Github: https://github.com/devopshobbies Linkedin: https://www.linkedin.com/company/devopshobbies