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.

Code in production will break. Maybe a request takes too long, maybe it fails quietly, or maybe it works fine one minute and falls over the next. Logs can help, sure—but they don’t always show the full picture, especially when performance issues are involved. Elastic APM gives you a clearer view. It traces what your application is doing from incoming requests to database queries and everything in between.

Running workloads on Google Kubernetes Engine (GKE) delivers impressive scalability and flexibility. Yet, it can also introduce a tricky challenge: tracking GKE costs accurately. Remember, GKE costs rarely scale linearly. Overprovisioned nodes, idle autoscalers, and orphaned workloads can quietly balloon your bill in the background. And while GKE’s native tools offer some visibility, they often miss the full picture.