







CNCF is the vendor-neutral hub of cloud native computing, dedicated to making cloud native ubiquitous.
CNCF Platform Working Group Launched Platform Engineering Maturity Model
In April 2023, in time for Kubecon Amsterdam, CNCF Platforms WG (working group) released a Platforms Definition white paper, defining…

CNCF Platforms White Paper
This paper intends to support enterprise leaders, enterprise architects and platform team leaders to advocate for, investigate and plan internal platforms for cloud computing. We believe platforms significantly impact enterprises' actual value streams, but only indirectly, so leadership consensus and support is vital to the long-term sustainability and success of platform teams. In this paper we'll enable that support by discussing what the value of platforms is, how to measure it, and how to implement platform teams that maximize it.

Why cloud native belongs at the heart of agentic AI: Lessons from building a multi-agent security platform on Kubernetes
In March, I gave a talk at KubeCon + CloudNativeCon Europe 2026 in Amsterdam. After the session, the same questions kept coming up on the CNCF Slack and in person: why build agentic AI on cloud native…

CloudNativeSecurityCon North America | LF Events
CloudNativeSecurityCon is a two-day event designed to foster collaboration, discussion and knowledge sharing of developer-first cloud native security practices.

Together AI | The AI Native Cloud
Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research.

eBPF and Kubernetes: Little Helper Minions for Scaling Microservices - Daniel Borkmann, Cilium
Bluefin
The next generation cloud-native Linux workstation, designed for reliability, performance, and sustainability.

Cloud without Kubernetes
I think it’s safe to say Kubernetes has “won” the cloud mindshare game. If you look at the CNCF Cloud Native landscape (and manage to not…

AI-Native Cloud | DigitalOcean
Run AI products in production with a unified stack for agents, inference, and cloud—built for control, performance, and economics at scale.
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The latest news and resources on cloud native technologies, distributed systems and data architectures with emphasis on DevOps and open source projects.

Astera Partnering with the National Science Foundation to Support Open Science
Today, the National Science Foundation (NSF) announced a partnership with the Astera Institute related to the first round of investment in building a national network of automated laboratory infrastructure, known as the Programmable Cloud Laboratories (PCL) Test Bed Initiative. The NSF will spend $380 million spread across 20 awardees to advance AI and automated instrumentation […]
National Data Platform Receives NSF Category I Award to Expand AI-Ready Data Infrastructure for U.S.
UC San Diego researchers will lead a collaborative project to expand a national platform connecting data, computing and AI resources to empower nationwide researchers and educators.

Google for Developers Blog - News about Web, Mobile, AI and Cloud
LiteRT is the universal framework for on-device AI. The production stack delivers 1.4x faster cross-platform GPU performance, streamlined NPU acceleration, and superior GenAI support for open models like Gemma.

A low-carbon computing platform from your retired phones
Jennifer Switzer, Visiting Postdoctoral Researcher, and David Patterson, Fellow, Google

Exploring the idea of self-hosting a Bluesky PDS alongside my Indiekit instance — turning it into a dual-protocol server that federates over both ActivityPub and AT Protocol simultaneously. Inspired by Wafrn’s approach, adapted to Indiekit’s plugin architecture and Cloudron deployment. The goal: ow…
Ricardo Mendes
rmendes.netCloudflare Workers, Deno Deploy, Netlify Edge, and Vercel Edge all have (partial) native Node.js support. But how much? Made a test suite to check this live! > github.com/pi0/platform-node-compat
GitHub - pi0/platform-node-compat: Display Node.js compatibility of edge runtimes
github.com