Operations | Monitoring | ITSM | DevOps | Cloud

Your OTel spans, our errors: A Sentry love story in one trace

You can already send OTel traces to Sentry. Point your OTLP exporter at Sentry’s endpoint, set environment variables, and your spans show up in the trace explorer. Our OTLP setup guide and “You Don’t Need to Pick One” walk you through that. But those spans are islands. You get a trace waterfall in Sentry, sure.

VM Migration - What Happens to Your NSX Segments in Kubernetes?

Planning a migration off NSX usually starts with a networking conversation. Segments, VLANs, routing topology and BGP peering are not things that map cleanly to Kubernetes-native constructs the way the NSX distributed firewall maps to Calico’s tiered microsegmentation. NSX virtualizes the network layer in ways that Kubernetes doesn’t replicate by default. There is no native concept of a Layer 2 segment or VLAN, for instance.

Why Staying Current Makes Modernization Easier

Most organizations don’t experience modernization as a single initiative. It unfolds over months and years, through a series of decisions made as technology shifts, business needs change, and operational demands grow. Teams adopt new capabilities, automate manual work, sharpen visibility, and strengthen security. These efforts look independent, but they share one requirement: a platform foundation that can keep up with continuous change.

Bring Your Backstage Context Into Every PagerDuty Incident

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how Custom Field Mapping for PagerDuty’s plugin for both Spotify for Backstage and Spotify Portal for Backstage now generally available builds towards this vision. It’s 2am. A Sev-1 fires, and your on-call responder opens the incident in PagerDuty. What’s waiting for them? A service name, and not much else. No tier.

SRE Agent Enhancements: Faster Triage, Greater Access Controls, Deeper System Connectivity

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how recent SRE Agent Enhancements build towards this vision. During an incident, everything is competing for attention at once. Responders lose time swiveling between tools, insights gathered by AI stay siloed instead of feeding into the next decision, and the pressure to move fast means learnings rarely stick.

Get the Context Your Alerts Are Missing with Event Enrichment

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how Event Enrichment builds towards this vision. Every on-call engineer knows the drill. An alert fires. It tells you something is wrong, but not what it means. Is this asset in maintenance? Which team owns it? Is it customer-facing?

The Industrial Mobile Browser Built for Supply Chain Work

Warehouse workers don’t think about whether their mobile interface runs on a browser. They’re focused on getting the job done. But for operations and IT teams evaluating or upgrading mobile technology in supply chain environments, platform choice matters more than most people realize. Consumer mobile browsers such as Safari, Edge and Chrome are useful tools designed for everyday web use. They help people search, shop, read, collaborate and access web applications from almost anywhere.

Open 360 AI's chat is now powered by OrionIQ

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.

How to measure AI ROI: metrics and a framework finance can actually run

To measure AI ROI, compare attributable value (revenue lift, cost savings, engineering time recovered, risk reduction) against fully loaded AI spend (API usage, subscriptions, infrastructure, people time) at the unit level: per initiative, per team, per task. The formula is simple. The instrumentation is the hard part, and it's where most organizations are failing: in CloudZero's 2026 survey, 34% of finance leaders couldn't produce a credible ROI number at all.