Operations | Monitoring | ITSM | DevOps | Cloud

Demo - Selector Platform CoPilot Diagnosis

Apr 28, 2026 By Selector In Selector
See how Selector’s AI Copilot accelerates issue diagnosis in real time. In this demo, watch how natural language queries and AI-driven insights help teams quickly analyze incidents, surface root cause, and understand impact - without digging through multiple tools. Instead of manual investigation, Selector guides operators to answers faster, reducing noise and speeding up resolution. Built for network and operations teams who need clarity, speed, and smarter troubleshooting.
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Introducing the Cortex AI Assistant (now in Slack)!

Apr 28, 2026 By Cortex | Engineering Operations Platform In Cortex
Mention @Cortex in any Slack channel the Assistant has been invited to, public or private, and get grounded answers pulled from your Cortex data. Questions can be as simple as "who owns payments-api?" or as analytical as "what's driving our incident trends this quarter?" The Assistant pulls context from all across Cortex, including ownership, Scorecards, Initiatives, on-call, dependencies, and Eng Intelligence metrics, and holds context across a threaded conversation.
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jfrog

Accelerating AI Agent Development on Google Cloud with JFrog MCP Registry

Apr 28, 2026 By Guy Eshet In JFrog
Developers building agentic AI on Google Cloud have powerful infrastructure at their fingertips: Gemini 3 for reasoning, Google’s Agent Development Kit (ADK) for orchestration, and a rapidly expanding ecosystem of Model Context Protocol (MCP) servers that connect agents to data and tools. So why are so many teams still waiting weeks to ship their first agent to production?
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coralogix

What "AI-Ready Data" actually means for observability teams

Apr 28, 2026 By Micha Duman In Coralogix
Many organizations deploying AI are learning similar lessons right now: the challenge isn’t this or that AI model, it’s the data. According to Gartner, 60% of AI projects will be abandoned by organizations because of failures to support these projects with AI-ready data. Also, 63% of organizations either lack or aren’t sure they have the right data management practices to get there.
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Incident.io

Who's on call? How Claude helped us calculate this 2,500x faster

Apr 28, 2026 By Article In Incident.io
Schedules are a core part of any on-call system. In ours, they define who to page and when. But people use them in lots of other ways too: checking their next shift, asking for cover while at the gym, keeping a Slack user group up to date, or updating a Linear triage responsibility. For many of our customers, they’re one of the main ways they interact with our product, and as they’re such a foundational part of On-call, it’s very important they work well.
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sentry

Introducing Seer Agent: The answer is already in Sentry. Now you can ask for it.

Apr 28, 2026 By Rahul Chhabria In Sentry
This is a story about an engineer’s night that could have been bad, but ended up… not so bad. A few weeks ago, on a Saturday, our AI debugger, Seer, started failing. Note the big scary spike on the right. The errors were generic failures from the LLM calls, nothing that pointed at a root cause. Most of the team wasn’t scheduled to be on this weekend, and it just so happened Indragie, our Head of AI, was online. He started paging engineers.
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logicmonitor

Context-Driven AI You Can Trust: How Edwin AI Earns Confidence in Production

Apr 28, 2026 By Andrew Keating In LogicMonitor
Most legacy AIOps investments underdeliver because the AI lacks context, not capability. LogicMonitor’s latest innovations expand Edwin AI’s contextual intelligence across every dimension, so recommendations are accurate, explainable, and trusted by the teams that need to act on them. Reduce incident resolution time with AI that understands your environment—not just your alerts.
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logicmonitor

LogicMonitor Advances Autonomous IT with No Blind Spots, Trusted AI, and Closed-Loop Action

Apr 28, 2026 By Garth Fort In LogicMonitor
LogicMonitor’s latest innovations span the entire platform to deliver the operational foundation enterprises need for Autonomous IT—complete visibility from infrastructure to end user, AI that reasons in full context, and closed-loop automation that moves from detection to resolution. Over 90% of organizations rely on at least two to three monitoring solutions—and many enterprises operate five or more.
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