Microsoft Azure at KubeCon Europe 2026 | Amsterdam, NL - March 23-26

Date: Tues 24 March 2026

Start Time: 10:18 AM CET

Room: Hall 12 

Title: Scaling Platform Ops with AI Agents: Troubleshooting to Remediation

Speakers: Jorge Palma, Natan Yellin (Robusta)

As AI agents increasingly write our code, can they also operate and troubleshoot our infrastructure? More importantly, should they?

This keynote explores the practical reality of deploying AI agents to maintain Kubernetes clusters at scale. We'll demonstrate HolmesGPT, an open-source CNCF sandbox project that connects LLMs to operational and observability data to diagnose production issues. You'll see how agents reduce MTTR by correlating logs, metrics, and cluster state far faster than manual investigation.

Then we'll tackle the harder problem: moving from diagnosis to remediation. We'll show how agents with remediation policies can detect and fix issues autonomously, within strict RBAC boundaries, approval workflows, and audit trails. We'll be honest about challenges: LLM non-determinism, building trust, and why guardrails are non-negotiable.

This isn't about replacing SREs; it's about multiplying their effectiveness so they can focus on creative problem-solving and system design.

Date: Tues 24 March 2026  

Start Time: 9:37 AM CET

Room: Hall 12 

Title: Rules of the road for shared GPUs: AI inference scheduling at Wayve

Speaker: Mukund Muralikrishnan, Wayve Technologies

As AI inference workloads grow in both scale and diversity, predictable access to GPUs becomes as important as raw throughput, especially in large, multi-tenant Kubernetes clusters. At Wayve, Kubernetes underpins a wide range of inference workloads, from latency-sensitive evaluation and validation to large-scale synthetic data generation supporting the development of an end-to-end self-driving system. These workloads run side by side, have very different priorities, and all compete for the same GPU capacity.

In this keynote, we will share how we manage scheduling and resources for multi-tenant AI inference on Kubernetes. We will explain why default Kubernetes scheduling falls short, and how we use Kueue, a Kubernetes-native queueing and admission control solution, to operate shared GPU clusters reliably at scale. This approach gives teams predictable GPU allocations, improves cluster utilisation, and reduces operational noise. We will close by briefly showing how frameworks like Ray fit into this model as Wayve scales its AI Driver platform.

Date: Wed 25 March 2026  

Start Time: 13:15 CET

Room: Hall 1-5 | Solutions Showcase | Demo Theater

Title: Building cross-cloud AI inference on Kubernetes with OSS

Speaker: Anson Qian, Jorge Palma

Operating AI inference under bursty, latency-sensitive workloads is hard enough on a single cluster. It gets harder when GPU capacity is fragmented across regions and cloud providers.

This demo walks through a Kubernetes-native pattern for cross-cloud AI inference, using an incident triage and root cause analysis workflow as the example. The stack is built on open-source capabilities for lifecycle management, inference, autoscaling, and cross-cloud capacity scheduling. We will specifically highlight Karpenter for elastic autoscaling and a GPU flex nodes project for scheduling capacity across multiple cloud providers into a single cluster.

Models, inference endpoints, and GPU resources are treated as first-class Kubernetes objects, enabling elastic scaling, stable routing under traffic spikes, and cross-provider failover without a separate AI control plane.

Speaker

Title

Jorge Palma

Microsoft keynote: Scaling Platform Ops with AI Agents: Troubleshooting to Remediation

Anson Qian, Jorge Palma

Microsoft demo: Building cross-cloud AI inference on Kubernetes with OSS

Will Tsai

Tues 24 March
(11:00 - 18:00)

Wed 25 March 

Thurs 26 March