Operations | Monitoring | ITSM | DevOps | Cloud

sentry

AI agent observability: The developer's guide to agent monitoring

Apr 7, 2026 By Sergiy Dybskiy In Sentry
Most "agent observability best practices" content reads like a compliance checklist from 2019 with "AI" pasted over "microservices." Implement comprehensive logging. Establish evaluation metrics. Create governance frameworks. Not a single line of code. No mention of what happens when your agent silently picks the wrong tool on turn 3 and you need to figure out why.
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datadog

Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA

Apr 7, 2026 By Tohn Furutani In Datadog
This guest blog post is by Tohn Furutani, SRE Engineer at NTT DATA. Over the past year, the conversation around generative AI has shifted from single-shot use cases—such as summarization, Q&A, and chat interfaces—to agentic AI systems that can make decisions based on context, plan multistep actions, invoke tools, and adapt as conditions change.
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digitate

The Next Phase of Agentic AI

Apr 7, 2026 By Digitate In Digitate
The Enterprise AI Survey conducted by Digitate in collaboration with Sapio Research states that the journey of enterprise automation and AI adoption has evolved significantly. The initial waves focused primarily on improving accuracy, efficiency, and reducing costs. Now, the next phase, Agentic AI, is transforming this shift from mere automation to dynamic collaboration.
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IREX Enhances FireTrack AI Module for Faster, More Accurate Fire Detection

IREX Enhances FireTrack AI Module for Faster, More Accurate Fire Detection

Apr 7, 2026 By OpsMatters In OpsMatters
WASHINGTON, DC - IREX, a global developer of ethical AI and intelligent video analytics, has announced a significant upgrade to its FireTrack fire and smoke detection module, expanding its capabilities across a wide range of environments. As outlined in an article on TNW, the updated solution is designed to work seamlessly with existing camera infrastructure, eliminating the need for additional hardware while extending its use to critical infrastructure, public institutions, residential and commercial properties, and natural environments such as parks and forests.
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From AI Idea to Real System: What Changes Along the Way

From AI Idea to Real System: What Changes Along the Way

Apr 7, 2026 By OpsMatters In OpsMatters
Most companies don't struggle with the idea of AI. They struggle with what to do with it. The potential is clear-automation, predictions, better decisions. But translating that into something useful inside a business is where things become less obvious. That's usually when ai ml consulting services start to make sense.
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cloudzero

How Will We Hold AI Accountable For Risky Investments?

Apr 6, 2026 By Erik Peterson In CloudZero
The word “Trillion” never fails to set the tech world on fire. Foundation Capital’s Jaya Gupta and Ashu Garg are two of the most recent firestarters. Late in December, they co-wrote “AI’s trillion-dollar opportunity: Context graphs,” outlining how AI will transition from organizational knowledge to organizational comprehension.
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honeycomb

AI Working for You: MCP, Canvas, and Agentic Workflows - Part 2

Apr 6, 2026 By Ken Rimple In Honeycomb
In our previous post in our series on observability for the agent era, we looked at how Honeycomb provides unique visibility into LLMs operating in your production environment. Now, let’s flip it around and explore how Honeycomb provides observability insights uniquely suited to helping your AI agents rapidly diagnose and fix production issues, and build production feedback into the next round of development.
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honeycomb

The Fundamentals: Fast, Deep, and Ready for What Comes Next - Part 3

Apr 6, 2026 By Ken Rimple In Honeycomb
The previous two posts in this series have looked at some of the use cases Honeycomb customers are implementing to observe LLMs in production and power agentic observability workflows. In this third and final post, we’ll take it back to basics and look at how the fundamental capabilities and infrastructure of Honeycomb provide the comprehensive data and fast performance that makes these use cases work at production scale. AI capabilities built on a weak observability foundation fall apart fast.
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harness

AI Demos Are Easy. Enterprise AI Is Not. | Harness Blog

Apr 6, 2026 By Shubham Jindal In Harness
‍Why 90% of AI prototypes never make it to production, and what to do about it. Every week, someone on my team shows me a demo that looks incredible. An agent that writes deployment pipelines. A chatbot that triages incidents. A copilot that generates test cases from Jira tickets. The demo takes 20 minutes. The audience claps. Everyone leaves convinced we're six weeks from shipping it. We're not.
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