Operations | Monitoring | ITSM | DevOps | Cloud

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.

For developers building on iOS and macOS, building the most performant software means having access to the latest Mac resources to quickly build, test, and deploy software. Apple’s newest M4 Pro chip represents yet another significant leap in Apple Silicon performance, delivering unprecedented speed and efficiency for development teams.

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.