Distributed tracing is a powerful technique that allows you to track the flow and timing of requests as they navigate through a system. By linking operations and requests between multiple services, distributed tracing provides valuable insights into system performance and helps identify bottlenecks. In this blog post, we will delve into the benefits of distributed tracing, explore its relevance for various application architectures, and uncover how it operates behind the scenes.

OpenTelemetry vs. Prometheus - Difference in architecture, and metrics.

OpenTelemetry is a popular open-source project that provides a standardized way of collecting, processing, and exporting telemetry data from distributed systems. It is designed to be vendor-neutral and supports multiple programming languages and platforms. OpenTelemetry consists of several components that work together to enable telemetry collection and processing.

As an SRE, have you ever had a situation where you were working on an application that was written with non-standard frameworks, or you wanted to get some interesting business data from an application (number of orders processed for example) but you didn’t have access to the source code?

OpenMetrics and OpenTelemetry are two popular frameworks that provide metrics-driven insight into complex software environments. Understanding the differences between these two options is critical for organizations looking to optimize their monitoring capabilities. In this article, we will explore the key features, benefits, and considerations of OpenMetrics and OpenTelemetry to help you make an informed decision when choosing the right solution for your organization.

OpenTelemetry and Prometheus are both powerful observability tools, each with its own strengths. OpenTelemetry provides a standardized way to collect, instrument, and export telemetry data, while Prometheus excels at time-series monitoring and alerting. In this blog post, we will delve into the similarities and differences between OpenTelemetry and Prometheus, exploring the benefits and advantages of each.

In the previous article, we talked about Distributed Tracing with MuleSoft APIs using OpenTelemetry. In this post, we’ll go through the process of integrating Distributed Tracing with MuleSoft APIs using OpenTelemetry via a proxy server. The purpose of this article is to demonstrate how we can instrument a legacy mule app with open telemetry without making changes to the existing app. Here, we’re showing an example of getting data from a header as well as a query parameter.

What is OpenTelemetry Collector, Architecture, Deployment and Getting started.

Core Web Vitals (CWV) are Google's preferred metrics for measuring the quality of the user experience for browser web apps. Currently, Core Web Vitals measure loading performance, interactivity, and visual stability. These are the main indicators of what a user’s experience will be while using a web page.

Elastic APM supports OpenTelemetry on multiple levels. One easy-to understand scenario, which we previously blogged about, is the direct OpenTelemetry Protocol (OTLP) support in APM Server. This means that you can connect any OpenTelemetry agent to an Elastic APM Server and the APM Server will happily take that data, ingest it into Elasticsearch®, and you can view that OpenTelemetry data in the APM app in Kibana®.