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rollbar

Using AI + Rollbar's Session Replay to Understand Complex Errors

Dec 12, 2025 By Rollbar In Rollbar
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.
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Agentic AI demands a new data architecture #ai #telemetry

Dec 12, 2025 By Cribl In Cribl
Clint Sharp explains why traditional schema-on-read systems cannot handle the query loads of the future. Agentic telemetry requires a 360-degree view, but structuring data only when you read it is too slow for AI-driven workloads. The solution is using LLMs to drive the cost of building parsers to near zero. Tools like Copilot Editor allow teams to map data to OCSF instantly, effectively building factories of parsers to handle the scale of agentic AI.
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datadog

This Month in Datadog - December 2025

Dec 11, 2025 By Datadog In Datadog
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.
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datadog

Highlights from AWS re:Invent 2025: Making sense of applied AI, trust, and going faster

Dec 11, 2025 By Andrew Krug In Datadog
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.
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Komodor

The War Room of AI Agents: Why the Future of AI SRE is Multi-Agent Orchestration

Dec 11, 2025 By Itiel Shwartz In Komodor
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.
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nexthink

How to Build a Clear AI Implementation Strategy

Dec 11, 2025 By Nexthink In Nexthink
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.
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Capture and Use Network Response Data in AI Powered Testing

Dec 11, 2025 By Harness In Harness
Learn how to capture and use response data from network calls to build smarter and more reliable AI-driven tests. This walkthrough covers the full workflow from configuring user actions to extracting backend responses, validating data, and creating dynamic test flows. You will also see how response data improves debugging visibility and supports data-driven automation. The video includes Ideal for developers, testers, and platform engineers looking to improve the accuracy and resilience of AI-powered test suites.
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cloudzero

The AI Cost Crisis: 'AI Cost Sprawl' Is Crashing Your Innovation (AI Cost Sprawl Explained + How To Fix It)

Dec 11, 2025 By Lyne Carolyne In CloudZero
AI should speed up innovation, not inflate your cloud bill. But today, the biggest GenAI challenge for SaaS teams isn’t model quality; it’s cost. And increasingly, that cost comes from AI cost sprawl. That’s not because anyone is doing something wrong, but because AI operates differently from the cloud services we’ve all spent a decade learning how to manage.
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harness

Accelerating Our Mission to Bring AI to Everything After Code

Dec 11, 2025 By Jyoti Bansal In Harness
Since launching Harness in 2017, we’ve been on a mission to unlock faster innovation by removing the bottlenecks that slow software engineering teams down. From day one, we believed that the biggest obstacles in engineering weren’t in writing code — they were in everything that followed.
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