pipy VS k3s

Pipy is an open-source, lightweight, high-performance, modular, programmable, cloud-native network stream processor that is ideal for a variety of use cases ranging from (but not limited to) edge routers, load balancers & proxy solutions, API gateways, static HTTP servers, service mesh sidecars, and other applications. Previously we have covered several use cases, and in this blog post will continue our learning of Pipy by implementing an HTTP Tunnel functionality by only using the PipyJS scripting language.

If you are interested in learning more about SMI-compatible Service Mesh, FSM, and Programmable Proxy, visit our website Flomesh.io for more detailed documentation, tutorials, and use cases.

But as the complexity of your apps and architecture grows, you might require more fine–grain control over your services. And if your organization requires Zero Trust and has a need for end–to–end encryption like mTLS, you should consider a service mesh like osm-edge a light weight, ultra fast, low resources, highly extensible, Service Mesh Interface (SMI) compatible, built for edge and cloud computing service mesh. When you have communication between services (east–west traffic), a service mesh allows you to control traffic at that level.

Below we list the most remarkable changes in the Core API and PipyJS. For a detailed change log, refer to Pipy Release Page

Flomesh Service Mesh(FSM) from Flomesh is Kubernetes North-South traffic manager, provides Ingress controllers, Gateway API, Load Balancer, and cross-cluster service registration and service discovery. FSM uses Pipy - a programmable network proxy, as its data plane and is suitable for cloud, edge, and IoT.

FSM is another open-source product from Flomesh for Kubernetes north-south traffic, gateway api contoller, and multi-cluster management. FSM uses Pipy, a programmable proxy at its core, and provides an Ingress controller, Gateway API controller, load balancer, cross-cluster service registration discovery, and more.

osm-edge is built on top of Open Service Mesh (OSM) v1.1.0 codebase and is a lightweight service mesh for resource-sensitive cloud environments and edge computing scenarios. It uses osm as the control plane and Pipy as the data plane and features high performance, low resources, simplicity, ease of use, scalability, and compatibility (x86/arm64 support).

We're very happy to announce the release of osm-edge 1.1. This release is the culmination of months of effort from the flomesh.io team and we are very excited to unveil it today. osm-edge is built on top of Open Service Mesh v1.1.0 codebase and is built purposely for edge computing and uses lightweight, high-performant, cloud native, and programmable proxy Pipy as its data plane and sidecar proxy.

Below we list the most remarkable changes in the Core API and PipyJS. For detailed change log refer to Pipy Release Page

Opinionated meaning it picks, install, patches your CNI/Ingress/Load Balancer/DNS Server/Metrics Server/Monitoring Setup.

k3s is probably most well known as it ships with bunch of preinstall software: https://github.com/k3s-io/k3s so you can just start throwing yaml files at cluster and handling workloads. It's what I use for my homelab.

Paid things I've heard of include OpenStack and SideroLabs. Haven't used personally by SRE coworkers say good things about them.

For self-hosting I've found https://k3s.io to be really good from the SUSE people. Works on basically any Linux distro and makes self-hosting k8s not miserable.

Yes it’s going to depend on which k8s distribution you’re using. We have work in-progress for k3s to natively support nix-snapshotter: https://github.com/k3s-io/k3s/pull/9319

For other distributions, nix-snapshotter works with official containerd releases so it’s just a matter of toml configuration and a systemd unit for nix-snapshotter.

We run Kubernetes outside of NixOS, but yes the NixOS modules provided by the nix-snapshotter certainly make it simple.

K3S: is a lightweight distribution of Kubernetes that is designed for resource-constrained environments. It is an excellent option for running Kubernetes on a virtual machine or cloud server.

I recently purchased a used Lenovo M900 Think Centre (i7 with 32GB RAM) from eBay to expand my mini-homelab, which was just a single Synology DS218+ plugged into my ISP's router (yuck!). Since I've been spending a big chunk of time at work playing around with Kubernetes, I figured that I'd put my skills to the test and run a k3s node on the new server. While I was familiar with k3s before starting this project, I'd never actually run it before, opting for tools like kind (and minikube before that) to run small test clusters for my local development work.

Kubernetes - k3s distribution

I’ve created a local cluster with K3S and installing Windmill could not be simpler with just one chart to configure, which already has sane defaults to get started. For this demo we will also configure workers to passthrough environment variables to our scripts so that they have access to the Kubernetes API server for later.

You should be familiar with Kubernetes and have set up a Kubernetes cluster. I recommend k3s.