Edge Computing
- redhat.com: Let’s monitor edge computing networks with RHEL!
- cloudflare.com: What Is Edge Computing? Edge computing optimizes internet devices and web applications by bringing computing closer to the source of the data. This minimizes the need for long distance communications between client and server, which reduces latency and bandwidth usage.
- Red Hat’s approach to Edge Computing 🌟
- opensource.com: Why KubeEdge is my favorite open source project of 2020 🌟 KubeEdge is a workload framework for edge computing.
- thenewstack.io: Cloudian CTO: Kubernetes, Standardization Key to Edge
- cncf.io: Hosted Edge vs Cloud: the battle for latency and security 🌟
- developers.redhat.com: Bring your Kubernetes workloads to the edge
- thenewstack.io: A New Kubernetes Edge Architecture
- betterprogramming.pub: I Worked at Microsoft Cloud and Google Mobile for 3 Years — Here Are the Differences in Ecosystems Why working on cloud vs. mobile (Edge) is so different?
WebAssembly
- (2026) How Wasmer used Codex to build Edge.js 🌟 - Wasmer engineers leverage OpenAI Codex to accelerate the deployment of Edge.js, a lightweight Node.js runtime for WebAssembly.
Edge Hardware
- (2026) How Meta Engineered Ultra-Narrow Batteries for AI Glasses 🌟 - Podcast episode exploring Meta’s engineering achievements in developing 7mm steel-can batteries using die-cut stacked electrodes for smart wearables.
Edge Security
- (2026) A revisit of remote Spectre attacks on Cloudflare Workers 🌟 - Cloudflare researchers demonstrate a remote Spectre attack in production and deploy in-process isolation defenses.
- (2026) Secure all your internal vibe-coded applications — in one click 🌟 - Cloudflare Access now attaches directly to Workers, propagating zero-trust authentication across all domains and previews.
Edge AI
- (2026) Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI 🌟 - A massive release of over 200 versioned WebGPU kernels designed to standardize and accelerate local in-browser AI inference.
- (2026) Run AI Models for Edge Application Development with Just a Few Commands 🌟 - How to utilize TensorRT Edge-LLM and the DGX Spark 64GB platform to rapidly prototype and deploy AI models for edge embedded applications.
- (2026) TensorRT Edge-LLM Completes the MLPerf Edge Agentic Benchmark 6.4x Faster on Jetson AGX Thor 🌟 - NVIDIA demonstrates a 6.4x edge inference speedup for long-context conversational AI agents using NVFP4 quantization and KV cache reuse on Jetson AGX Thor.
- (2026) Frontier Reasoning Reaches the Edge: How to Deploy and Optimize Models on NVIDIA Jetson 🌟 - Strategies for deploying and optimizing multi-step reasoning and agentic AI models on resource-constrained NVIDIA Jetson edge devices.