Operations | Monitoring | ITSM | DevOps | Cloud

AI Search Technologies and the Future of Intelligent Information Retrieval

The transformative power of artificial intelligence (AI) is evident across a multitude of sectors, none more so than in AI search technologies, a pivotal advancement reshaping the future of internet navigation and information retrieval.

AI Is Forcing A Return To Hybrid And Multi-Cloud (Here's What To Do Now)

For most of the last decade, the direction of cloud strategy was clear: standardize, consolidate, and reduce sprawl. Engineering teams worked to pick a primary cloud, reduce vendor dependencies, and simplify their stacks. FinOps teams unwound years of fragmentation. Platform teams built guardrails to make sure it didn’t happen again. Then AI arrived, and it’s a fundamentally different class of workload. AI demands specialized hardware and, increasingly, diverging providers.

My AI Agent Stole My Crypto #speedscale #openclaw #aicoding #codingagent #security

I thought I found the ultimate coding shortcut: an autonomous AI agent. Turns out, I just bought a one-way ticket to a digital nightmare. A friendly reminder to my fellow devs: Validation isn't optional—it's survival. Your laptop shouldn't have a higher calling than your production environment. Validate now: speedscale.com.

How we built Grafana Assistant - a conversation about AI development for observability

This conversation with Grafana Labs engineers, Mat Ryer, Cyril Tovena and Sven Großmann, dives deep into the engineering behind Grafana Assistant, exploring how agentic AI is transforming the observability landscape. From hackathon origins to sophisticated backend agents, the team shares candid lessons on building, scaling, and refining AI tools for engineers.

How AI is democratizing video and what it means for your brand

Video stopped being optional years ago. In 2026, 95% of marketers say video increases brand awareness, and 60% report it directly drives sales. But for small businesses and solo entrepreneurs, there's always been a gap between knowing video matters and actually making it. The costs, the learning curve, the time-it adds up fast.

Operational Risks and Controls When Deploying Legal AI

A law firm recently found that its AI tool had misread "limitation of liability" clauses for 6 months. No one noticed the mistake. The error only came to light when a client faced a huge insurance claim that the firm had promised was capped. The cost? That firm is now dealing with a malpractice lawsuit and a damaged reputation. Using AI in a law office poses risks beyond simple computer bugs. These tools mix technical errors with professional responsibility. As AI becomes a standard part of the job, firms without strict rules will face quality issues and legal trouble.

From Blueprint to Production: Building a Kubernetes MCP Server

As Large Language Models (LLMs) evolve from simple chatbots into agentic workflows, the need for a standardized way to connect them to external data and infrastructure has become critical. In a recent workshop hosted by Nir Adler, Innovation Engineer at Komodor, we explored how to bridge this gap using the Model Context Protocol (MCP).

Why MCP is becoming part of your product surface

AI assistants are quickly becoming a primary interface for how people interact with software. Developers ask them how to integrate APIs. Users ask them how products work. Buyers ask them how tools compare. Increasingly, the first explanation someone receives about your product does not come from your website, your documentation, or your sales team. It comes from an AI assistant. That shift has an important consequence that many organizations are only starting to notice.