Docker Model Runner makes running AI models on your local machine a breeze. Thanks to GPU acceleration on Apple silicon and seamless hookup with Docker Desktop, it’s like giving your machine a caffeine boost. No more juggling fragmented tools. Models run as OCI Artifacts straight from Docker Hub, boosting performance and slashing cloud costs—minus the setup circus.

VMware Tanzu just upped its game. It's infused with generative AI magic and has kicked Kubernetes to the curb. Now it taps into Anthropic's Model Context Protocol for a swift, almost cheeky, app creation rollercoaster. Ditch the config files—just throw code into the wild with Spring AI. Its data services and observability are slicker than a greased lightning bolt, cranking productivity up fivefold.

Docker containers give PID 1 the spotlight, but it's a diva. It needs to manage zombie processes or play nice with an init system like Tini. When Tini stepped in, the container kicked those undead resource hogs to the curb. Suddenly, the server ran like a dream, and those annoying Redis errors bit the dust. All in a day's work.

Craft a miniature powerhouse with three Raspberry Pi 5s, each kitted out with NVMe drives. It's your ticket to an eye-opening, hands-on Kubernetes adventure. Start by installing K3s—the featherweight Kubernetes hero. Then, unleash the Altinity Operator to deftly manage your ClickHouse cluster. Say goodbye to cloud lag and enjoy the thrill of lightning-fast local testing.

Headlamp shakes up Kubernetes management with a GUI that catapults you from setup to active use in seconds. Whether you're cloud-bound or grounded on-prem, it slides right in. Its flexible architecture lets you stretch as needed, while detailed application maps and handy extras like port forwarding flip the script for beginners or Windows admins wondering what sorcery got them here.

Kelsey Hightower tips his hat to Nix. It holds promise for sharpening Docker by taming the chaos of reproducible builds. But don't get it twisted—Docker's not going anywhere. Its ecosystem brims with tools and ease of use that Nix has yet to match. Hightower challenges the Nix crowd: craft a sustainable ecosystem, embrace extensions. Take a page from the nimble-minded folks who shaped Linux.

NVIDIA's KAI Scheduler and Exostellar's SDG showcase the nerd ballet of fractional GPU scheduling. KAI slices GPU time like a master chef carving a roast, yet can't keep its focus solo—leading to app skirmishes. In contrast, Exostellar SDG nails resource control, quarantines workloads like a germaphobe, and mingles with various GPUs. It even sports vLLM dual deployments without breaking a sweat.

Google Cloud Next swings open the curtains on GKE’s latest tricks for inference. Imagine serving costs dropping by 30%, tail latency by 60%, and a whopping 40% leap in throughput. Talk about upgrades with attitude!

OpenTelemetry barges into Crunchy Postgres for Kubernetes v5.8, tossing away those Prometheus sidecars in favor of OpenTelemetry collectors. It's a bold move: observability without chains. No more vendor handcuffs. Just pure, unfettered insights, delivered fast.

Meet the Rust-infused lifesaver sweeping away Kubernetes port-forwarding mayhem. It tames connections by routing everything through one neat hub. TCP and UDP? Handled effortlessly. Picture a pod bridging UDP traffic over TCP with precision, serving up a swanky GUI or a no-nonsense terminal view. Add a dash of Git magic for slick config syncing, and voilà—chaos controlled.

Unveiling weak spots in Kubernetes starts with sniffing out missteps—exposed API endpoints being the usual suspects. These often blab sensitive cluster secrets. Tools like Shodan and Censys—or just some crafty Google-fu—can flag data, tipping you off to shaky K8s configurations. Who knew hacking could be this fun?

Kro sprang into existence powered by the unlikely trio: Google, Amazon, and Microsoft. This tool seeks to untangle Kubernetes orchestration while wearing a stylish, cloud-agnostic hat. It's defying the conventional walls of competition by making things play nicely across platforms. Just seven months in the game, with zero marketing fanfare, it's already roped in 57 active contributors. It's quickly morphing into the open-source glue holding multicloud dreams together.

ClickHouse Cloud decided to shake up the status quo with a gutsy Make-Before-Break approach. They chopped vertical scaling delays by dynamically adding capacity without sending your data to the void. This ballet involves managing multiple StatefulSets with the grace of a lion tamer, maintaining both agility and toughness. They orchestrated this grand performance with Temporal workflows, conducting thousands of live migrations in perfect synchrony. Meanwhile, backup and connection management systems stood guard, ensuring no data dared step out of line. It's a kinetic leap forward for the world of cloud scaling.

A Raspberry Pi 5 nestled in a shoebox rack, spinning its wheels with "real" Kubernetes. It sips a dainty 10W but stumbles over hiccups like ARM64 chart voids and single-lane PCIe NVMe antics. Though NVMe drives rocket from 90MB/s to 350MB/s, reeling in those image pulls, thermal throttling and x86-exclusive charts throw a wrench in the works. If silent efficiency, modularity, and a chance to roll up your sleeves matter more than sheer speed, it's a tinkerer's paradise.

The video is a comprehensive workshop on building AI agents with Dagger, featuring Solomon Hykes. It explains the concept of AI agents, the shift from simple language models to actionable AI with environments and tools, and demonstrates how to create a coding AI agent that can write, build, and validate Go programs. 

The Docker Language Server taps into Buildx for its secret sauce. Shines a light on Dockerfile vulnerabilities with Docker Scout. Running Go 1.23+? Perfect. Snag the source, unleash tests straight from Docker, and watch the magic unfold.

KubeBoard dishes out a stylish Python/Flask GUI to reveal Kubernetes ingresses in all their glory. It comes loaded with customizations and dynamic updates to keep your dashboard snappy and alive.

Forget the CLI headaches. This Kubernetes MCP server does the heavy lifting. It auto-updates configurations, juggles CRUD operations with grace, and doesn't demand Node or Python. Who knew efficiency could be so charming?

This repository contains the infrastructure code and configuration for deploying open-source Cloud Native Tools like database, cache, message broker, gateway, monitoring, logging, and more to multiple environments (development, staging, and production) using Docker, Kubernetes, and Skaffold.

KubeStellar - a flexible solution for multi-cluster configuration management for edge, multi-cloud, and hybrid cloud

KubeVPN turns your local Docker setup into a mirror of your Kubernetes playground. It syncs the two worlds seamlessly, no magic wands required. Just snag incoming traffic with a service mesh. Then, connect using service names or Pod IPs. Easy as pie, minus the sticky fingers.