Operations | Monitoring | ITSM | DevOps | Cloud

Observability for GenAI Applications (Grafana OpenTelemetry Community Call)

Jan 22, 2026 By Grafana In Grafana
In this episode, we’re diving into observability for Generative AI apps. AI helps us write code and monitor applications in production - but how do we observe the AI itself? And how do we make sense of complex, non-deterministic AI systems? We’re joined by two great guests: Ishan Jain, working on GenAI observability and Luccas Quadros, working on Grafana Assistant. Together, they bring both platform-level insights and real-world perspectives.
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From idea to agent: Building AI workflows with relaxAI and n8n

Jan 22, 2026 By Civo In Civo
Join us for this live online webinar as we explore how to design, build, and deploy practical AI agents using n8n’s workflow automation platform powered by relaxAI’s UK sovereign infrastructure. Our speaker, Ben Norris, AI Engineer at Civo, will guide you through the real-world process of creating intelligent agents that automate tasks across tools and services, all without deep coding expertise.
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[Webinar] Building Quality-Driven Agentic AI in Noisy Big Data Environments

Jan 22, 2026 By Komodor In Komodor
Watch as Itiel Shwartz, Komodor CTO and Co-Founder as he shares hard-won lessons from developing an AI agent that processes millions of K8s events daily to deliver autonomous troubleshooting that reached 95%+ accuracy in benchmarking. This webinar covers: Building production ready systems that maintain reliability when 90% of your data is noise. How Komodor developed an AI SRE agent that processes millions of K8s events daily to deliver autonomous troubleshooting that reached 95%+ accuracy in benchmarking.
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civo

An introduction to GPU time-slicing

Jan 22, 2026 By Jubril Oyetunji In Civo
GPUs are no longer a niche component. Gamers know them for immersive graphics, workstation users rely on them for balanced performance, and in the age of AI, GPUs have become one of the most in-demand resources in modern infrastructure. They are also expensive. That reality creates two immediate constraints, for individuals and enterprises alike: GPU-backed instances should be provisioned deliberately, and once provisioned, they should be used efficiently.
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cloudzero

AI Anomaly Detection: Catch AI Cost Surprises Before They Kill Margins

Jan 22, 2026 By Lyne Carolyne In CloudZero
Consider this: traditional cloud cost monitoring was like checking your fuel gauge once a month — after the trip was already over. That model worked when infrastructure scaled slowly. You provisioned resources predictably and paid for stable, linear usage. AI breaks that model. Today, AI costs behave like a high-performance engine with a hypersensitive throttle. A small input, like a prompt change or a single power user, can dramatically increase your fuel burn in seconds.
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honeycomb

Measuring Claude Code ROI and Adoption in Honeycomb

Jan 22, 2026 By Mae Capozzi In Honeycomb
At Honeycomb, we’ve been using Claude Code across our engineering team for a while. Anecdotally, I had a sense of who the power users were, and I had seen some examples of complex usage. But I wanted to be able to confidently answer questions, like: Claude Code supports OpenTelemetry out of the box, which means sending telemetry to Honeycomb takes just a few minutes of configuration.
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devart

How to Use PostgreSQL AI for Query Writing and Optimization

Jan 21, 2026 By Rosemary Asufi In Devart
PostgreSQL AI is gaining attention as SQL complexity increases in production environments. It addresses a common problem: extended queries that accumulate joins, nested logic, and edge cases. Without AI assistance, these queries are often harder to write and review, driving 20–40% of developer time into debugging. In practice, these challenges affect PostgreSQL users in different ways.
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gitkraken

How GitKraken's AI-Powered Commit Composer Eliminates Git Cleanup Headaches

Jan 21, 2026 By Iva Dobreva In GitKraken
As developers, we’ve all been there: a frantic coding session, a few hasty commits, and suddenly our Git history looks like a patchwork quilt of “fix,” “oops,” and “stuff.” While git rebase -i is a powerful tool for cleaning up, it’s also a source of anxiety for many, often leading to more headaches than it solves. What if you could achieve a pristine, meaningful commit history without the fear of breaking things or hours spent squashing and rewriting?
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