gateway-api VS zipkin

# cilium/playbook.yml - name: Bootstrap the Kubernetes cluster hosts: localhost gather_facts: false become: true environment: KUBECONFIG: ~/.kube/config vars: helm_version: v3.14.4 kube_context: k3d-k3s-default tasks: - name: Install Kubernetes library ansible.builtin.pip: name: kubernetes<30 state: present - name: Install helm binary ansible.builtin.shell: cmd: "{{ lookup('ansible.builtin.url', 'https://git.io/get_helm.sh', split_lines=false) }}" creates: /usr/local/bin/helm environment: DESIRED_VERSION: "{{ helm_version }}" - name: Install Kubernetes gateway CRDs kubernetes.core.k8s: src: "{{ item }}" state: present context: "{{ kube_context }}" loop: - https://github.com/kubernetes-sigs/gateway-api/releases/download/v1.0.0/standard-install.yaml - https://github.com/kubernetes-sigs/gateway-api/releases/download/v1.0.0/experimental-install.yaml - name: Install cilium block: - name: Add cilium helm repository kubernetes.core.helm_repository: name: cilium repo_url: https://helm.cilium.io - name: Install cilium helm release kubernetes.core.helm: name: cilium chart_ref: cilium/cilium namespace: kube-system state: present chart_version: 1.15.x kube_context: "{{ kube_context }}" values: gatewayAPI: enabled: true kubeProxyReplacement: true encryption: enabled: true type: wireguard operator: replicas: 1

It has already been a couple of years since the Kubernetes Ingress was defined as a “frozen” feature while further development will be added to the Gateway API.

Kubernetes provides two APIs to achieve this, the Ingress API and the Gateway API.

With all that said, K8s is not really meant to function as an API gateway to arbitrary services. You should look into API gateways such as NGINX, Kong or others, service meshes as others have already pointed out, or have a look at the K8s Gateway API the SIG is currently working on. The last one is in the early stages of adoption, but it could provide you with a nice way to do an API Gateway right in K8s.

Maybe there's something in the new fangled gateways.

Keep an eye on the Gateway API GAMMA Initiative as it is currently evolving with the goal of streamlining how services meshes can implement the Gateway API and reduce some overlap.

The selling point for me was ability to configure it using Kubernetes CRD's and future support of the Gateway API (under development - <https://gateway-api.sigs.k8s.io/>).

Developers can version their API now within helm charts or even yaml templates held along the code in their repositories.

-- https://gateway-api.sigs.k8s.io

While you're learning about ingresses, also look into the k8s Gateway API, which is the next generation. https://gateway-api.sigs.k8s.io/

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.