Distributed systems, such as modern microservices-based applications, are highly scalable, but also highly complex. Dependencies and unexpected interactions between services are a common cause of incidents, and these incidents are also notoriously hard to test for. xk6-disruptor — an extension that adds fault injection capabilities to Grafana k6, the open source reliability and load testing tool — can help overcome these challenges.

While we all love open source technology and the community that comes with it, we don’t always have the time or resources to stand up, maintain, update, and troubleshoot a self-hosted stack.

Efficient monitoring and visualization of performance metrics are paramount for ensuring seamless user experiences and reliable system operations. Grafana and Graphite, two powerful open-source tools, form an unbeatable combination when it comes to monitoring and analyzing time-series data. Grafana provides a robust and flexible platform for visualizing data, while Graphite acts as a scalable and efficient backend for storing and retrieving metric data.

What is Grafana? How do I change the color of a panel set? Where can I find all public dashboards? Who made the Kessel Run in less than 12 parsecs?

Grafana is one of the most popular dashboarding and visualization tools for metrics. The Grafana Dashboards are a very important part of infrastructure and application instrumentation. In this post, we will deep dive into Grafana dashboards. We will create a Grafana dashboard for a VM’s most important metrics, learn to create advanced dashboards with filters for multiple instance metrics, import and export dashboards, learn to refresh intervals in dashboards and learn about plugins.

AWS’s serverless technologies are popular because they provide cost effective scaling and great separation of concerns. However, observing serverless architectures like Lambda is challenging due to their transient nature and abstracted infrastructure. Unlike traditional systems with consistent hosts, serverless functions are ephemeral, often scaling rapidly and operating in isolation.

In the previous article I covered how to set up auto-instrumented tracing for a Node.js app using OpenTelemetry (OTEL). We then sent the spans directly to the open source tracing tool Jaeger. I recommend you give that a read first before walking through this guide because we're going to re-use the instrumentation we set up last time. Today we're going to take things a step further by introducing the OpenTelemetry Collector.