k8gb - geoip demo

at KCD Bratislava 25

If you’ve been globally distributing digital content for a while, you’ll understand that merely having numerous datacenters with advanced caching patterns isn’t sufficient. When your users need to retrieve an object that’s available in different locations worldwide, they should ideally be directed automatically to the location that’s nearest and fastest for the best experience. Cloud service providers typically offer services to handle this for you within their own clouds, but what if you are running a multi-cloud or hybrid environment? K8GB is a cloud-native solution that handles GeoDNS across heterogeneous environments and enables you to reach the same level of multiregion service resilience offered by cloud providers.

( recording , slides )

k8gb oss kubernetes 2025

Optimizing Metrics Collection & Serving When Autoscaling LLM Workloads

at Kubecon 25 @ London

Balancing resource provision for LLM workloads is critical for maintaining both cost efficiency and service quality. Kubernetes’s Horizontal Autoscaling offers a cloud-native capability to address these challenges, relying on the metrics to make the autoscaling decisions. However, the efficiency of metrics collection impacts how quickly and accurately Autoscaler responds to the LLM workload demands. This session explores strategies to enhance metrics collection for autoscaling LLM workloads with: 1. The fundamentals of how horizontal autoscaling works in Kubernetes 2. The unique challenges of autoscaling LLM workloads 3. A comparison of existing Kubernetes autoscaling solution for custom metrics with their pros and cons 4. How optimizing metrics collection through push-based approaches can improve scaling responsiveness. It will demonstrate an integrated solution using KServe, OpenTelemetry collector and KEDA to showcase how they can be leveraged to optimize LLM workload autoscaling.

( recording , slides )

k8gb oss kubernetes 2025