What’s new with Microsoft in open-source and Kubernetes at KubeCon North America 2025
From improving reliability and performance to advancing security and AI-native workloads, our goal remains the same: make Kubernetes better for everyone.
From improving reliability and performance to advancing security and AI-native workloads, our goal remains the same: make Kubernetes better for everyone.
The next major release of Azure Container Storage delivers higher IOPS and less latency compared to previous versions.
Now, with Radius Resource Types, platform engineers can define resource types specific to their organizations.
With this practical guide, you now know how to secure your Kubernetes cluster using the structured-authentication feature, offering flexible integration with any JWT-compliant token provider.
This introductory post will focus on the core concepts of Drasi, and its major components such as Sources.
Microsoft is excited to be able to support and contribute to the cloud-native and open-source communities at KubeCon Europe 2024.
Empowering developers with key improvements and innovations with Microsoft at KubeCon North America.
KEDA reduces the complexity of infrastructure autoscaling, making it simpler to configure, manage, and secure the application auto-scaler.
As the requirements and software surrounding Kubernetes clusters grow along with the required number of clusters, the administrative overhead becomes overwhelming and unsustainable without an appropriate architecture and supportive tooling.
As we come together in Amsterdam, there are significant headwinds and challenges facing us, but I’m confident that open-source and cloud-native computing are critical parts of the solutions.
Welcome to KubeCon 2021 in Los Angeles! Whether you are attending in person or virtually, we’re excited to see you at the conference.
This post was co-authored by Alejandro Saucedo, Director of Machine Learning Engineering at Seldon Technologies. About the co-author: Alejandro leads teams of machine learning engineers focused on the scalability and extensibility of machine learning deployment and monitoring products with over five million installations.
Managing Kubernetes clusters is hard. Managing Kubernetes clusters at scale across a variety of infrastructures is—well—even harder. The Kubernetes community project Cluster API (CAPI) enables users to manage fleets of clusters across multiple infrastructure providers.