Jaeger is a popular open-source tool used for distributed tracing in a microservice architecture. In a microservice architecture, a user request or transaction can travel across hundreds of services before serving what a user wants. Distributed tracing helps to track the performance of a transaction across multiple services. Before we deep dive into how Jaeger accomplishes distributed tracing for microservices-based architecture, let's take a short detour to understand distributed tracing.

Both Grafana Tempo and Jaeger are tools aimed at distributed tracing for microservice architecture. Jaeger was released as an open-source project by Uber in 2015, while Tempo is a newer product announced in October 2020. Jaeger is a popular open-source tool that graduated as a project from Cloud Native Computing Foundation. Grafana Tempo is a high-volume distributed tracing tool deeply integrated with other open-source tools like Prometheus and Loki.

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.

Both AWS X-Ray and Jaeger are distributed tracing tools used for performance monitoring in a microservices architecture. Jaeger was originally built by teams at Uber and then open-sourced in 2015. On the other hand, AWS X-Ray is a distributed tracing tool provided by AWS specifically focused on distributed tracing for applications using Amazon Cloud Services. Jaeger is a popular open-source tool that graduated as a project from Cloud Native Computing Foundation.

Distributed tracing is becoming a critical component of any application's performance monitoring stack. Setting it up in-house is a hearculean task, and that's why many companies prefer outside tools. Jaeger and Zipkin are two popular open-source projects used for end-to-end distributed tracing. Let us explore their key differences in this article.

Jaeger is an open-source end-to-end distributed tracing tool for microservices architecture. On the other hand, Elastic APM is an application performance monitoring system that is built on top of the ELK Stack (Elasticsearch, Logstash, Kibana, Beats). In this article, let's explore their key features, differences, and alternatives. 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.

Jaeger and New Relic are tools used in the application monitoring and observability domain. While Jaeger is an open source tool under Cloud Native Computing Foundation, New Relic is a SaaS vendor in the observability domain. Let us explore the key differences between Jaeger and New Relic in this article. New Relic is an extensive SaaS tool and provides application performance as well as infrastructure monitoring. Jaeger provides an open-source solution for end-to-end distributed tracing.

Jaeger and OpenTracing are both open-source projects. Jaeger was originally built by teams at Uber and then open-sourced. The OpenTracing project was also started by teams at Uber, and hence they are compatible with each other. While Jaeger is an end-to-end distributed tracing tool, OpenTracing is a set of APIs and libraries that can be used to instrument your application.

Folks! Great to have you over for our monthly product update aka Signal #04. This month we made great strides in both our frontend and backend pods. Metrics ingestion, testing frameworks, improved tracking features for gRPC calls and much more! We also crossed 200+ members on our slack community 🎉🎉🎉 Let's dive in to see what humans at SigNoz have been upto!

Setting up observability and robust monitoring for distributed systems is a challenging task. Engineering teams need access to different pieces of information to understand what's happening with their application. Is OpenTelemetry a step in the right direction for distributed tracing? Let's find out. Nothing can guarantee how your systems will behave in production. Things will go wrong, and it's critical to monitor your application for any signs that need troubleshooting.