Today's environments often present the challenge of collecting data from various sources, such as multi-cloud, hybrid on-premises/cloud, or both. Each cloud provider has its own tools that send data to their respective telemetry platforms. OpenTelemetry can monitor cloud VMs, on-premises VMs, and bare metal systems and send all data to a unified monitoring platform. This applies across multiple operating systems and vendors.

OpenTelemetry has emerged as the go-to open source solution for collecting telemetry data, including traces, metrics, and logs. What’s especially unique about the project is its focus on breaking free from the reliance on proprietary code to offer users greater control and flexibility. As a senior solutions engineer here at Grafana Labs, I’ve spent a lot of time exploring OpenTelemetry, including in my spare time.

Spans are fundamental building blocks of distributed tracing. A single trace in distributed tracing consists of a series of tagged time intervals known as spans. Spans represent a logical unit of work in completing a user request or transaction. Distributed tracing is critical to application performance monitoring in microservice-based architecture. Before we deep dive into spans, let's have a brief overview of distributed tracing.

Fleet management in the broader sense is about managing, organizing, and coordinating assets within an organization to ensure efficiency, reduce costs, and maintain compliance. The term originates from the automotive industry. According to Forbes, Fleet management involves a slew of strategies and procedures required to operate a fleet of 5 or more vehicles punctually, cost-effectively, and at optimal efficiency.

Both DataDog and Jaeger are tools used to monitor application performance. The difference lies in what they monitor and terms of usage. Jaeger is an open-source tool focused on distributed tracing of requests in a microservice architecture. While DataDog is a SaaS APM vendor covering most monitoring needs of an application. Application performance monitoring is the process of keeping your app's health in check. APM tools enable you to be proactive about meeting the demands of your customers.

Modern digital organizations have rapidly adopted microservices-based architecture for their applications. Distributed tracing tools help monitor microservices-based applications. Choosing the right distributed tracing tool is critical. How do you know which is the right one for you? In this post, we will cover the top 13 distributed tracing tools in 2024 that can solve your monitoring and observability needs.

Nextjs is a production-ready React framework for building single-page web applications. It enables you to build fast and user-friendly static websites, as well as web applications using Reactjs. Using OpenTelemetry Nextjs libraries, you can set up end-to-end tracing for your Nextjs applications. Nextjs has its own monitoring feature, but it is only limited to measuring the metrics like core web vitals and real-time analytics of the application.

OpenTelemetry is a Cloud Native Computing Foundation(CNCF) incubating project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). However, OpenTelemetry does not provide storage and visualization for the collected telemetry data. And that’s where an OpenTelemetry backend is needed. Cloud computing and containerization made deploying and scaling applications easier.

OpenTelemetry (OTel) is an open-source framework designed to standardize and automate telemetry data collection, enabling you to collect, process, and distribute telemetry data from your system across vendors. Telemetry data is traditionally in disparate formats, and OTel serves as a universal standard to support data management and portability.