Modern software development is evolving rapidly, and while the latest innovations allow companies to grow through greater efficiency, there is a cost. Modern architectures are incredibly complex, which can make it challenging to diagnose and rectify performance issues. Once these issues affect customer experience, the consequences can be costly. So, what is the solution? Observability — which provides a visible overview of the big picture.

I’ve spent most of my career working with tech in various forms, and for the last ten years or so, I’ve focused a lot on building, maintaining, and operating robust, reliable systems. This has led me to put a lot of time into researching, evaluating, and implementing different solutions for automatic failure detection, monitoring, and more recently, observability. Before we get started: What is observability?

In this blog series, we are covering application instrumentation steps for distributed tracing with OpenTelemetry standards across multiple languages. Earlier, we covered Java Application Manual Instrumentation for Distributed Traces, Golang Application Instrumentation for Distributed Traces, and DotNet Application Instrumentation for Distributed Traces. Here we are going to cover the instrumentation for NodeJS.

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.

We're excited to help our customers further leverage the benefits of OpenTelemetry via integration with AWS Distro for OpenTelemetry (ADOT) for traces 1.0.

Modern application architectures are complex, typically consisting of hundreds of distributed microservices implemented in different languages and by different teams. As a developer, SRE, or DevOps engineer, you are responsible for the reliability and performance of these complex systems. But while you might have metrics that will help you debug when there’s an issue, metrics alone can’t help you narrow down and ultimately identify the root cause.

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.