The latest News and Information on Distributed Tracing and related technologies.


Top 11 distributed tracing tools in 2021

Choosing the right distributed tracing tool is critical. How do you know which is the right one for you? Here are the top 11 distributed tracing tools that can solve your monitoring and observability needs. Distributed tracing tools have become a critical component in a distributed and microservices-based architecture. So why is distributed software so popular? There are three major reasons for the popularity of distributed software: scalability, reliability, and maintainability.


observIQ Cloud and the OpenTelemetry Collector

Our log agent is powerful, efficient, and highly adaptable. Now, with OpenTelemetry setting new standards in the observability space, we wanted to incorporate that collaboration into our log agent and offer our users the ability to take advantage of the OpenTelemetry ecosystem. Starting today, you can upgrade the log agents in your observIQ account to the new Open Telemetry-based observIQ log agent with a single click.


Jaeger vs Tempo - key features, differences, and alternatives

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.


How Refinery Helps With Sampling Complex Event Data

Sampling is the practice of extracting a subset of data from a dataset to make conclusions about that larger dataset. It’s far from a perfect solution, but when it’s implemented with Refinery, Honeycomb’s trace-aware sampling proxy, sampling can help you manage very high volumes of complex event data.


What Is Distributed Tracing and Why You Need It

It is no surprise that monitoring workloads are top of mind for many organizations to ensure a successful customer experience. As our applications become more distributed and cloud-native, we find that monitoring can become more complex. A single user transaction fans out to interact with tens or hundreds of microservices, each one requesting data from backend data stores or otherwise interacting with each other and other parts of your infrastructure.


DataDog vs Jaeger - key features, differences and alternatives

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.


AWS X-Ray vs Jaeger - key features, differences and alternatives

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.

Auto-Instrumenting Ruby Apps with OpenTelemetry

In this tutorial, we will go through a working example of a Ruby application auto-instrumented with OpenTelemetry. To keep things simple, we will create a basic “Hello World” application, instrument it with OpenTelemetry’s Ruby client library to generate trace data and send it to an OpenTelemetry Collector. The Collector will then export the trace data to an external distributed tracing analytics tool of our choice.


Jaeger vs Zipkin - Key architecture components, differences and alternatives

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.