Operations | Monitoring | ITSM | DevOps | Cloud

AI agents are only as effective as the context they can access. The problem is that most of that context lives outside your observability platform.

OrionIQ’s agentic investigation is now built into Logz.io Open 360 AI. Ask a question and OrionIQ investigates across your telemetry, shows its work as it goes, links every finding back to the exact query behind it, and tells you how much to trust the answer. Today we’re bringing OrionIQ Chat into Open 360 AI. This is the first OrionIQ product to ship inside the Logz.io platform, and it’s the same agent that powers the standalone OrionIQ app, now available right where you already work.

When an alert fires at 2 a.m., responders need context more than another dashboard. A suspicious authentication event may begin in an identity provider, touch a cloud control plane, appear in an application log, and end with an unusual data transfer. If each signal lives in a separate tool, analysts spend the first part of the incident rebuilding a timeline instead of containing the threat.

Ask ten engineering leaders how far their organization has actually gotten with autonomous AI, and most will admit the same thing once the marketing language drops away: not nearly as far as it looks from the outside. That was the undercurrent of a roundtable Logz.io and Twingate hosted on July 22, 2026, bringing together VPs of engineering, CTOs, senior security directors, and several product leaders across different industries and company stages.

TL;DR: Prometheus’s biggest structural weakness has always been cardinality. A stable feature years in the making is finally addressing it, and the rest of the observability market is already responding. Native histograms allow for more efficient metrics storage, reducing cardinality strain and enabling faster, more cost-effective AI-powered observability. Ready to see how AI-powered observability can simplify your monitoring? Book a demo of the Open 360 platform.

TL;DR: This is the engineering companion to our announcement post, Upgraded Alert AI Analysis: Automated Incident Investigation, read that one for what the new generation does for your team; read on for how it works under the hood. Interested in hearing more? Book a demo to see the Alert AI Analysis Agent live. Root cause analysis is one of the harshest tests you can give an AI.

TL;DR: OrionIQ has launched the next generation of its Alert AI Analysis agent within the Open 360 AI platform, designed to automate and accelerate incident investigation. Key features of this evolution include: Agent-Based Investigation: Instead of relying on a single prompt, the system coordinates specialized AI agents to correlate data across diverse sources like logs, metrics, deployments, and tickets.

TL;DR: Modern monitoring platforms face a “workflow problem”: engineers are drowning in telemetry but lack tools that connect detection to resolution, often leading to fragmented, manual incident investigations. Most organizations have mastered data collection but fail at incident response. Engineers waste precious time manually stitching together logs, metrics, and traces across siloed tools. The Solution: Workflow-driven monitoring acts as a guide, not just a dashboard.

TL;DR Agentic observability uses AI agents to autonomously investigate incidents, identify root causes, and take action in production environments. Unlike traditional monitoring (which alerts and waits) or AIOps (which assists human analysis), agentic platforms conduct the investigation themselves. Key capabilities include autonomous incident triage, evidence-backed root cause analysis, alert noise reduction, and governed remediation.