Operations | Monitoring | ITSM | DevOps | Cloud

In our Go projects, we rely on a consistent and battle-tested stack of libraries that help us build reliable, maintainable, and scalable systems. We started using Go in our stack many years ago (before Go v1) and therefore many of our choices have changed over the years. Here in this post, I wanted to share some of the libraries we use regularly to power our Go apps.

In a recent presentation, Verizon’s Steve Ownes discussed their strategic initiative to accelerate the decomissioning (decom) of TDM switches, underlining the significance of repurposing legacy infrastructures in favor of modern architectures. Ribbon’s guest Steve Owens kicks things off with a light-hearted reference to "Sanford and Son” showing how relics can be transformed into gold through effective management and innovation.

In recent months, my conversations with fellow technology leaders have consistently revolved around two key themes: how we leverage AI to drive innovation and efficiency, and how we mitigate the inherent risks associated with AI. However, I’ve noticed a concerning gap – while enterprises are busy strategizing the adoption of AI to enhance productivity, reduce costs, and outpace competitors, very few are addressing how AI is being actively used today by their own teams.

Collecting logs in Kubernetes often starts as a simple goal, and quickly turns into a game of “where did that log line go?” Between sidecars, DaemonSets, and countless config options, it’s easy to get lost. Fluent Bit helps cut through the noise. It's fast, lightweight, and plays well with Kubernetes. And when you deploy it using Helm charts? The setup becomes way more manageable. This guide covers the how and the why, without overcomplicating the what.

We are exploring how we can help on-call engineers troubleshoot incidents more effectively by providing the OpenAI Codex agent with access to real-time observability data in terminals. We've developed an integration and new tool visualizations that connect OpenAI's Codex CLI to the new Datadog MCP server. In this post, we'll share what we've been experimenting with: enabling an AI agent to retrieve production metrics, logs, and incidents from Datadog in real time and act on that context.

There’s a common misconception in IT operations that mastering DevOps, AIOps, or MLOps means you’re “fully modern.” But these aren’t checkpoints on a single journey to automation. DevOps, MLOps, and AIOps solve different problems for different teams—and they operate on different layers of the technology stack. They’re not stages of maturity. They’re parallel areas that sometimes interact, but serve separate needs.