Operations | Monitoring | ITSM | DevOps | Cloud

Kibana and Grafana are the leading options when selecting a tool for observability and monitoring in cloud environments. This guide extensively explores their variances to assist you in selecting the most suitable option for your requirements. Understanding these tools is crucial for effective system monitoring, whether managing a small startup or a large enterprise.

Learn about OTLP’s key features, and how it simplifies telemetry data handling, and get practical tips for implementation.

Tracealyzer is a popular tool for visualizing and analyzing the execution of real-time systems, but its price tag can be a barrier for some developers. This guide explores powerful open-source alternatives that provide similar functionality for free, helping you choose the right tool for your embedded systems projects.

If The Notorious BIG – the artist behind the iconic song "Mo Money Mo Problems" – had been an IT operations engineer, he might instead have labeled his hit "Mo Clouds Mo Problems." Why? Because the more clouds you have to manage and monitor, the more problems you're likely to run into.

Managing Docker container logs is essential for debugging and monitoring application performance. Tailoring Docker logs allows for real-time insights, quick issue resolution, and optimized performance. This guide focuses on efficient methods for tailing Docker logs, with clear examples and command options to streamline log management.

In 2016, we at Honeycomb first borrowed the term “observability” from the wikipedia entry for control systems observability, where it is a measure of your ability to understand internal system states just by observing its outputs. We then spent a couple of years trying to work out how that definition might apply to software systems. Many twitter threads, podcasts, blog posts, and lengthy laundry lists of technical criteria emerged from that work, including a whole ass book.