Operations | Monitoring | ITSM | DevOps | Cloud

Life is pretty good. I’ve shipped a mobile app and I’m (happily) drowning in telemetry. Battery impact, time in foreground/background per screen, crash rates, slow frames, network retries – the works. The data is brilliant; the challenge is turning signals into reliable alerts that catch real issues which are relevant to my app’s functions. So… what should I actually listen for, and where should I set the thresholds?

Everyone wants to move faster with AI, but few are truly ready for it. This is where organizations can position themselves better as AI readiness isn’t just about algorithms, it’s about whether your data, systems, and teams are prepared to support intelligent automation safely and effectively.

For a long time, robotic process automation (RPA) was the fastest way to scale repetitive digital work. Bots copied, clicked, and executed rule-based tasks faster than any human. They reduced error rates and delivered early wins for efficiency. Sounds just fine, right? Prepare for a Matrix moment, because the truth is that IT teams built RPA only for predictability. It could follow instructions, but it couldn’t adapt when something unexpected happened.

Production errors can feel overwhelming. Your Rollbar dashboard is filling up with alerts, your team is scrambling to understand what needs immediate attention, and critical revenue-impacting issues might be buried among less urgent problems. Sound familiar? In this post, I'll walk you through a workflow that transforms production error chaos into organized, prioritized action items. We'll cover everything from analyzing Rollbar errors to creating properly linked Linear tickets.

‍ Like many developers, I’ve spent the last year adjusting to a world where I’m spending more keystrokes arguing, or, “explaining” to an agent the code I’d like to be written. No longer must we toil, writing every line code by hand like our great grandparents probably did.

Introducing Kentik AI Advisor, a powerful new AI designed to deeply understand your network, reason through complex issues, and deliver clear, actionable guidance for designing, operating, and protecting your networks. By autonomously querying Kentik’s rich telemetry and tools, it explains what’s happening, why it matters, and what to do next — from troubleshooting and capacity planning to cost optimization and risk mitigation.

Building automated workflows that adapt to real-world complexity can be a challenge. As systems scale and scenarios multiply, teams often end up hardcoding endless logic branches just to handle every potential outcome. That’s why we’re introducing Datadog Agent Builder, a powerful new tool that lets you create custom AI agents that are fully hosted by Datadog.