Operations | Monitoring | ITSM | DevOps | Cloud

Komodor

Rightsizing Nightmares: When Your Cloud Cost Tool Degrades Performance

Apr 30, 2026 By Ilan Adler In Komodor
This is what production teams see happening. A vertical pod autoscaler recommendation gets applied automatically. Resource requests come down a notch across a namespace. The cost dashboard registers a small cost savings win. A few minutes later, health checks start failing. Pods enter crash loops.
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coralogix

Your Team is Using Claude Code. Do You Know What It's Costing You?

Apr 30, 2026 By Lily Waldorf In Coralogix
The first two weeks of Claude Code are exciting. The third week is when you realize you don’t have visibility into what it’s doing or what it’s costing you. You would not run a production service without metrics, logs, and dashboards or deploy an API without knowing its latency, error rate, or cost per request.
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bigpanda

Agentic ITOps is here. Here's what early movers are doing.

Apr 30, 2026 By Katie Petrillo In BigPanda
We recently brought together IT operations leaders from across financial services, healthcare, airlines, media, and other industries for BigPanda 26, our annual customer event. The theme that emerged above all others during the event’s conversations is that our industry is no longer debating whether AI belongs in ITOps. The debate now is about how quickly it can be implemented, how to measure it, and who’s accountable when it acts. Here are some key learnings from BigPanda 26.
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DORA Metrics in the AI Era: Why Deployment Isn't Faster

Apr 30, 2026 By GitKraken In GitKraken
DORA metrics in the AI era reveal a paradox: PR volume is climbing, but deployment frequency is staying flat. In this talk, GitKraken's Director of Product Jeff Schinella breaks down why AI-accelerated code generation is creating a review bottleneck that your DORA metrics can't fully explain on their own. Jeff walks through how PR metrics (cycle time, first response time, code churn, and PR size) serve as the leading indicators behind your DORA data. If your deployment frequency is flat while PR counts go up, the bottleneck isn't your devs. It's your review capacity.
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ivanti

Ticket Taker to Team Leader: Managing an Agentic IT Workforce

Apr 30, 2026 By Abhay Kulkarni In Ivanti
The promise of AI in IT service management has been circulating for years. Chatbots that deflect tickets. Virtual agents that answer FAQs. Automation that routes requests. These are useful, but probably not the dream-state you were originally sold. What's different today is the arrival of agentic AI: systems that don't just respond to instructions but reason, act, and adapt across multi-step workflows with real consequences. The question for IT leaders is no longer whether to adopt agentic ITSM.
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upsun

What happens when you delete everything? Three minutes, or thirty hours.

Apr 30, 2026 By Upsun In Upsun
Last year, at the annual conference for an open source framework you've definitely heard of, I walked up to the founder in a room outside the main stage. He was hunched over his laptop, frantic. We've known each other for a few years. "What's going on? Is everything okay?" He looked up with the specific shade of white people only get when they realize they've made a big mistake.
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cortex

Context Engineering: How to Manage AI Context at Scale

Apr 30, 2026 By Ganesh Datta In Cortex
Context engineering is the practice of managing the information an AI model sees (documents, tool outputs, memory, and structured metadata about the systems it reasons over) so it can make accurate decisions inside a real engineering organization. Most engineering teams have access to the same AI coding agents: Claude, GPT, Gemini, the major variants everyone is shipping. The model is no longer the differentiator.
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