Operations | Monitoring | ITSM | DevOps | Cloud

Loaf and behold, this retrospective covers nearly 20 years of the Baker’s Dozen style annual ranking of the biggest ASes of the internet. In it we discuss the DFZ, de-peerings, and partitions. It was the yeast we could do.

Any company still running their own CI/CD, such as Jenkins, is paying a price. The question is which one: Each of these is extremely costly, and yet many software teams still host and run their own CI/CD for two reasons: tools like Jenkins are cheap or free, and hosting Jenkins on an AWS EC2 instance is often cheaper per minute than SaaS CI/CD services like Bitbucket Pipelines. Both reasons are true, but they’re also a trap.

An essential part of software development, testing helps catch bugs and errors early, improves software quality, and ultimately prevents costly issues from being deployed to production. The effectiveness of software testing will remain uncertain until it can be measured and that is where code coverage comes in. Code coverage is a metric that tells developers what portion of their codebase is executed when specific tests are run.

Effective monitoring catches problems before users do, and with Promtail, Loki, and LogQL, it’s a lightweight, approachable option for any DevOps team. This guide shows how to monitor Docker itself (pull failures, restarts, health flaps) so you’ve got a baseline on container runtime health.

Whether it’s streaming video, powering remote work, or supporting smart technologies, the ability to connect local users to the global internet is essential. But behind the scenes, a key infrastructure layer ensures that this digital experience runs smoothly: the middle mile. Middle mile networks serve as the critical bridge between the internet’s backbone and the local networks that deliver service to homes, businesses, and institutions.

When your Linux system feels sluggish, one of the first things to investigate is the CPU usage. The CPU (Central Processing Unit) is the brain of your machine, and if it’s overloaded, everything else slows down. In this guide, you’ll learn different ways to Linux check CPU usage with command-line tools, how to interpret the metrics, and why automatic monitoring with Icinga ensures long-term system stability.

An incident’s in progress. Services are slow, customers are frustrated, and your dashboards… look fine. At least, until you search for payment metrics and get 47 different names for the same signal. Suddenly, the real issue isn’t latency — it’s inconsistency. The OpenTelemetry project recently published a three-part series on naming conventions to solve exactly this problem.

Do you create reports yourself or rely on others to provide them? Regardless of your role at the IT support desk, reports play a crucial role. They help teams monitor performance, identify trends, and improve service quality. Let’s take a look at the reports you’ll need in 2025.

The BigQuery Sink connector is a critical piece of Kafka infrastructure that allows you to offload your Kafka topic data into BigQuery in real time. It is the third most-used connector among Kafka users (after the Google Cloud Managed Service for Apache Kafka and the original WePay sink connector), but it's not without its fair share of plot twists. Here's the story of how this connector switched hands three times and we ultimately ended up helping to re-build it.