log2rbac Operator

Kubernetes operator that helps you to set up the RBAC rules for your application. If requested, it scans the application's log files for authorization errors and adds them as exceptions/rights to the associated {Cluster}Role. It is like having a sudo command for your service accounts. However, with great power comes great responsibility. The goal of the tool is to find the minimum set of rights that is needed for your workload to run instead of using the cluster admin for everything.

rbac kubernetes kubernetes-operator controller

Spark Operator

Operator for managing the Spark clusters on Kubernetes and OpenShift.

spark kubernetes openshift kubernetes-operator controller

Abstract Operator

Library for creating the operators for Kubernetes and Openshift.

kubernetes kubernetes-operator openshift

Bitcoin Insights

Analysis of Blockchain transaction captured in a project that uses Jupyter notebook with GraphFrames and NetworkX, spark-notebook with GrapX. Notebooks attaches to a Spark cluster deployed in a standalone mode, everything containerized and running in Kubernetes or OpenShift.

Spark Bitcoin data jupyter kubernetes

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

Autoscaling Generative AI Workloads

at KCD Praha 24

Short lightning talk about KEDA being used as autoscaler for AI/ML workload. Stable diffusion model was used as an example that generates images based on the text input. Demo application was scaling the worker pods based on the length of message queue. I also briefly talks about pitfalls of GPU intensive workloads on K8s.

( recording )

KEDA AI/ML KCD kubernetes 2024

Multi-Cloud Global Content Distribution at Cloud Native Speeds

at OpenSourceSummit EU 24 @ Vienna

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 2024

k8gb meets Cluster API

at FOSDEM 24

In this talk we will be talking about an open-source way to fully automated K8s clusters that can host workloads that can survive any failure, using pure DNS as the underlying tool for switching the communication among available Kubernetes clusters. No single vendor lock-in. Workloads can be deployed in AWS, Azure, GCP, on-prem. The only common denominators are Kubernetes and Cluster-API.

( recording , slides )

k8gb FOSDEM Cluster-API kubernetes 2024

CRUDing Kubernetes Clusters with Cluster API @ KCD Bratislava 23

These days k8s namespaces don't provide enough isolation for our cloud native experiments. It's much easier to give a user the whole cluster to play with. Let them to break it; repeat. However, this assumes the cluster creation and deletion is an easy thing to do. Also there should be a nice API for that, not just some 5 years old web. Have you ever heard about clusterctl? If not, then come to this talk to learn how easy it is to start using it. If yes, then come to this talk to learn how hard it is to use it in production. Cluster API (CAPI) is a unique standardization effort among multiple cloud providers such as GCP, AWS, Azure but can also work with on-prem solutions such as OpenStack, KVM or vSphere. It allows you to dedicate one cluster in your infra as a control plane for creating the workload clusters. If you are into self-replicating robots, you are going to love this API!

Cluster-API KCD kubernetes 2023