kubefed VS zipkin

The project is similar (in spirit) to kubefed.

What Is KubeFed? KubeFed (Kubernetes Cluster Federation) allows you to use a single Kubernetes cluster to coordinate multiple Kubernetes clusters. It can deploy multiple-cluster applications in different regions and design for disaster recovery. To learn more about KubeFed: https://github.com/kubernetes-sigs/kubefed

There's active work on a standard called kubefed [0] that is being worked on.

> I want a scale-to-zero node-pool in every region, and one kube master api for the world.

Personally, I'd generalize this to: "I want to describe the reliability requirements and configuration for my software and have an automated system solve for where, how many, when, and how to route to it"

I want to have something where I can say "I need to have high availability, lowest latency, and X GB of RAM and Y cores" and have a system automatically schedule me wherever compute is cheapest while also intelligently routing traffic to my servers based on client origins.

[0] - https://github.com/kubernetes-sigs/kubefed

Two of the more common approaches to deploying Kubernetes in hybrid environments are from cloud-to-cloud and cloud to on-prem. Whether this is from using a single control plane like Rancher, Platform9, or Gardener to create multiple clusters that are managed from a single location, or utilizing Kubernetes federation to create a cluster that spans different regions, this model has become a key feature offered by Kubernetes that has helped drive adoption.

This is made possible by the very nature of Kubernetes being a standard portable platform across cloud providers, ability to manage infrastructure as code, ability to setup networking between them whenever needed with the help of multi-cluster service meshes and also due to the ability to orchestrate the deployments using Kubefed and Crossplane.

And the interesting thing about networking in cloud is that it need not be just be limited to the cloud provider within your region but can span across multiple providers across multiple regions as needed and this is where projects like Kubefed, Crossplane definitely does help.

Projects like Kubefed and Crossplane are especially useful here since they help you to manage and orchestrate clusters and the requests you send across different cloud providers even if its going to be across regions.

When choosing distributed tracing tools, considerations include your technology stack, business requirements, and monitoring complexity. Zipkin, SkyWalking, and OpenTelemetry are popular distributed tracing solutions, each with its unique features.

From the perspective of the realization of GraphQL infrastructure, the interesting direction is "Finding". How to find the problem? How to find the bottleneck of the system? Distributed Tracing System (DTS) will help answer this question. Distributed tracing is a method of observing requests as they propagate through distributed environments. In our scenario, we have dozens of subgraphs, gateway, and transport layer through which the request goes. We have several tools that can be used to detect the whole lifecycle of the request through the system, e.g. Jaeger, Zipkin or solutions that provided DTS as a part of the solution NewRelic.

Zipkin is a distributed tracing system used for tracking and analyzing how requests move through complex systems, especially in setups with many interconnected services, known as microservices.

Distributed Tracing: Middleware for distributed tracing like Jaeger and Zipkin helps monitor and trace requests as they flow through multiple microservices, aiding in debugging, performance optimization, and understanding the system's behavior.

For microservice tracing, you might want to look at Zipkin [0], or OpenTelemetry [1]

[0] https://zipkin.io/

I’ve not used a self-hosted solution before, but here’s one I found. https://zipkin.io/

> IMO the reason these vendors can and do charge so much is not because telemetry software is hard.

I always saw it as "they are charging for their polished UI/experience"

The UI of https://zipkin.io/ versus DataDog is kind of... not really in the same ballpark?

There are the zipkin https://zipkin.io/ and jaeger https://www.jaegertracing.io/ packages/components you can use both have quickstarts if you consider that to be a beginner's guide.

Zipkin, which was developed by Twitter, is an open source tool for distributed tracing that can also be used to troubleshoot latency issues in your application. While Zipkin is Java-based, py_zipkin is an implementation for Python.