Updates and recent posts about k3d..

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News FAUN.dev() Team

@kaptain shared an update, 2 months, 2 weeks ago

FAUN.dev()

Argo CD 3.2.2 Improves Secret Management, Retry Safety, and Auth Checks

#Securit... #gitops #argocd #Argo CD #kuberne...

ArgoCD v3.2.2 has been released, featuring a new addition, two enhancements, and a bug fix. This update aims to improve the overall functionality and reliability of the platform.

Argo CD 3.2.2 Improves Secret Management, Retry Safety, and Auth Checks

News FAUN.dev() Team

@devopslinks shared an update, 2 months, 2 weeks ago

FAUN.dev()

Rust Confirmed for Linux Kernel: Experiment Concludes Successfully

#Rust #linux #unix #Linux k... #The Rus...

The Rust experiment in the Linux kernel concludes, confirming its suitability and permanence in kernel development, with Rust now used in production and supported by major Linux distributions.

Rust Confirmed for Linux Kernel: Experiment Concludes Successfully

Course

@eon01 published a course, 2 months, 2 weeks ago

Founder, FAUN.dev

Generative AI For The Rest Of US

#AI #Generat... #LLM #Large L... #gpt

Your Future, Decoded

News FAUN.dev() Team

@kaptain shared an update, 2 months, 2 weeks ago

FAUN.dev()

Kubernetes v1.35 Timbernetes Release: 60 Enhancements

#k8s #Timbern... #cgroups #docker #kuberne...

Kubernetes v1.35, the Timbernetes Release, debuts with 60 enhancements, including stable in-place Pod updates and beta features for workload identity and certificate rotation.

Kubernetes v1.35 Timbernetes Release: 60 Enhancements

Activity

@kaptain added a new tool Kubernetes Gateway API , 2 months, 2 weeks ago.

News FAUN.dev() Team

@kala shared an update, 2 months, 2 weeks ago

FAUN.dev()

Google Releases Magika 1.0: AI File Detection in Rust

#Rust #Generat... #file ty... #Magika #AI

Google releases Magika 1.0, an AI file detection system rebuilt in Rust for improved performance and security.

Google Releases Magika 1.0: AI File Detection in Rust

Activity

@kala added a new tool Magika , 2 months, 2 weeks ago.

News FAUN.dev() Team

@kala shared an update, 2 months, 2 weeks ago

FAUN.dev()

Google’s Cloud APIs Become Agent-Ready with Official MCP Support

#Model C... #Apigee #Google ... #AI #MCP

Google supports the Model Context Protocol to enhance AI interactions across its services, introducing managed servers and enterprise capabilities through Apigee.

Activity

@devopslinks added a new tool BigQuery , 2 months, 2 weeks ago.

News FAUN.dev() Team

@devopslinks shared an update, 2 months, 2 weeks ago

FAUN.dev()

AWS Previews DevOps Agent to Automate Incident Investigation Across Cloud Environments

#DevOps #inciden... #GenAI #DevOps ... #aws

AWS introduces an autonomous AI DevOps Agent to enhance incident response and system reliability, integrating with tools like Amazon CloudWatch and ServiceNow for proactive recommendations.

AWS Previews DevOps Agent to Automate Incident Investigation Across Cloud Environments

k3d is an open-source utility designed to simplify running Kubernetes locally by wrapping K3s (Rancher’s lightweight Kubernetes distribution) inside Docker containers. Instead of creating virtual machines, k3d uses Docker as the execution layer, allowing developers to spin up multi-node Kubernetes clusters in seconds using minimal system resources.

k3d is especially popular for local development, CI pipelines, demos, and testing Kubernetes-native applications. It supports advanced setups such as multi-node clusters, load balancers, custom container registries, port mappings, and volume mounts, while remaining easy to tear down and recreate.

Because it uses K3s, k3d inherits a simplified control plane, bundled components, and reduced memory footprint compared to full Kubernetes distributions. This makes it ideal for developers who want a realistic Kubernetes environment without the overhead of tools like Minikube or full VM-based clusters.

k3d integrates cleanly with common Kubernetes workflows and tools such as kubectl, Helm, Skaffold, and Argo CD. It is frequently used to validate manifests, test Helm charts, and simulate production-like environments locally before deploying to cloud or on-prem clusters.