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The latest News and Information on Containers, Kubernetes, Docker and related technologies.

The rise of the agentic future: scaling AI workflows with relaxAI and n8n

This blog is based on the webinar, “From idea to agent: Building AI workflows with relaxAI and n8n”. You can watch the full recording by clicking here! AI isn’t slowing down. We’re moving from “ask a chatbot” to agents that run the multi-step workflows, use tools, and are built for real business processes. Most teams aren’t blocked by ideas. They’re blocked by three things: complexity, cost, and control.

Why leaders are reassessing the role of big tech in 2026

This session highlights a major strategic shift where sovereignty has moved from a technical detail to a top boardroom priority. The data reveals that 84% of leaders are concerned about geopolitical threats to their data access. 82% of respondents are ready to reassess their big tech partnerships specifically to regain data control. This shift is further evidenced by the 71% of decision-makers who now place sovereignty at the heart of their tech partner choices moving forward. The era of "sovereign-by-design" infrastructure is here. Are you ready to build for a more resilient future?

Beyond boundaries: How global collaboration defines AI in 2026

As we move through 2026, the global conversation around AI is shifting from simple adoption to a deeper focus on true openness and sovereignty. In this session from Civo Navigate India 2025, OpenUK CEO Amanda Brock explores the evolving state of AI openness and shares a significant milestone: India is now the world’s number one open-source contributing community.

AI SRE in Practice: Tracing Policy Changes to Widespread Pod Failures

Policy changes in Kubernetes are supposed to improve security, enforce standards, or optimize resource usage. But when a policy change triggers cascading pod failures across multiple namespaces, the investigation becomes a race to identify what changed before more workloads are affected.

Kubex and Tangoe Partner to Deliver Unified Cloud, Kubernetes, and FinOps Optimization

Enterprises operating at cloud scale today face a growing reality: managing infrastructure performance and cost in silos no longer works. Kubernetes, multi cloud environments, and GPU accelerated workloads deliver immense agility and capability, but they also introduce complexity that outpaces traditional monitoring and cost governance approaches.

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).

We Built an MCP Server

When I joined Kubex last year, the company was already well aware of the growing power of Large Language Models. As a company focused on intelligent resource optimization for Kubernetes, GPUs, and cloud infrastructure, generative AI didn’t feel like a threat so much as a natural extension of where the industry was heading. Kubex had already invested heavily in machine learning, but it was becoming clear that foundation models could unlock an entirely new class of capabilities for our customers.