Operations | Monitoring | ITSM | DevOps | Cloud

One of the most powerful capabilities in K8s is the ability to autoscale resources to meet demands, scaling resources up during peak periods to ensure performance, and down again during lower periods to save money. In this joint session, Lucidity and Kubex walk through what end-to-end K8s optimization looks like when you address both layers together. We cover: Expect real examples, not slides full of theory. You’ll leave with a clear picture of where waste is hiding in your environment and a prioritized approach to addressing it.

What is Ubuntu Core? Ubuntu Core is a minimal and strictly confined variant of Ubuntu powering devices around the world. Ubuntu Core 26 now integrates with the Canonical Observability Stack, streaming device logs and metrics to centralized Grafana, Loki, and Prometheus infrastructure, deployable in the cloud or on-premise, without burdening the device's primary workloads.

Most cloud providers think AI is just a hardware problem. They focus on the GPUs, the racks, and the raw compute, but they leave the strategy up to you. At Civo, we do AI differently. We don't just provide the hardware; we guide you through the full life cycle of AI adoption, from initial planning to scaling production workloads. By leveraging best-in-class NVIDIA models and GPUs, we give you the performance to unlock AI at scale without the fear of being bogged down by complexity. It's more than infrastructure, it’s cloud freedom with AI built-in.

Spin up a GPU workload cluster using Konstruct's new GPU cluster templates, deploy a self-hosted LLM, and use it in your organization — all live on stream. This hands-on session shows how shipping AI workloads to GPU clusters is just as easy as deploying to Konstruct physical or virtual clusters, and how open source apps in the GitOps Catalog make it even faster. Walk away knowing how to cut your token spend by running models privately on your own infrastructure.