Operations | Monitoring | ITSM | DevOps | Cloud

Front‑end bugs are notoriously hard to reproduce. By the time an error shows up in your monitoring tool, the most important context is already gone: what the user actually did. Session replay helps—but only if someone has the time and patience to scrub through recordings, correlate events, and form a hypothesis. That’s where Rollbar’s MCP server, paired with an AI agent like Github Copilot, changes the game.

We launched agent monitoring earlier this year, allowing our users to instrument LLM usage and tool calls in their applications. However, we only had Agent Monitoring support for Python and JavaScript. We’ve been working on creating an Agent Monitoring SDK for.NET — specifically for Microsoft.Extensions.AI.Abstractions.

For our last episode of 2025, we’re focusing on Datadog releases announced at AWS re:Invent. Join Jeremy to see how you can manage logs at petabyte scale in your infrastructure, eliminate unneeded costs in Amazon S3 buckets, build agentic workflows, and detect credential leaks. Later in the episode, Scott spotlights how you can connect your AI agents to Datadog tools and context with our MCP Server.

After four days of AWS re:Invent—a 65,000-step marathon that included 60,000 attendees spread across five Las Vegas campuses—and navigating the latest installment of this 13-year-old cloud pilgrimage, we’re all a little dehydrated but significantly wiser. The volume of announcements felt less like a single flood and more like a river branching into three powerful currents. Making sense of this massive technological convergence requires zooming out.

Kentik AI Runbooks are machine-readable instructions that codify tribal knowledge into specific diagnostic workflows. By guiding AI Advisor’s reasoning and tool selection, Runbooks turn alerts into actionable, automated investigations, dramatically accelerating MTTR.

We’ve all been there. It’s 2 AM, your phone is buzzing with alerts, and you’re suddenly thrust into an incident war room with a dozen other bleary-eyed engineers. The production environment is on fire, customers are affected, and everyone’s trying to piece together what went wrong. But here’s what makes these moments fascinating from a systems perspective – it’s rarely just one person silently fixing the issue in isolation.

Organizations see AI’s transformative potential, but success requires more than technology – it demands a clear strategy led by IT. A structured AI implementation roadmap aligns initiatives with business goals, establishes governance, and enables measurable ROI, while improving employee and customer experiences. Yet, 66% of organizations view AI as critical, but only 38% report meaningful competitive advantage, highlighting the need for disciplined adoption.