zipkin VS conduit

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.

Leverage a service mesh like Istio or Linkerd to manage communication between microservices within the Kubernetes cluster. These service meshes can be configured to intercept JMX traffic and enforce access control policies. Benefits:

Looks like CNCF waved them through Graduation anyway, let's look at policies from July 28, 2021 when they were deemed "Graduated"

All maintainers of the LinkerD project had @boyant.io email addresses. [0] They do list 4 other members of a "Steering Committee", but LinkerD's GOVERNANCE.md gives all of the power to maintainers: [1]

> Ideally, all project decisions are resolved by maintainer consensus. If this is not possible, maintainers may call a vote. The voting process is a simple majority in which each maintainer receives one vote.

And CNCF Graduation policy says a project must "Have committers from at least two organizations" [2]. So it appears that the CNCF accepted the "Steering Committee" as an acceptable 2nd committer, even though the Governance policy still gave the maintainers all of the power.

I would like to know if the Steering Committee voted to remove stable releases from an un-biased position acting in the best interest of the project, or if they were simply ignored or not even advised on the decision.

I'm all for Boyant doing what they need to do to make money and survive as a Company. But at that point my opinion is that they should withdraw the project from the CNCF and stop pretending like the foundation has any influence on the project's governance.

[0] https://github.com/linkerd/linkerd2/blob/489ca1e3189b6a5289d...

From here, we can explore other developments and tutorials on Kubernetes, such as o11y or observability (PLG, ELK, ELF, TICK, Jaeger, Pyroscope), service mesh (Linkerd, Istio, NSM, Consul Connect, Cillium), and progressive delivery (ArgoCD, FluxCD, Spinnaker).

https://linkerd.io/ is a much lighter-weight alternative but you do still get some of the fancy things like mtls without needing any manual configuration. Install it, label your namespaces, and let it do it's thing!

Would it be possible to create a custom extension with the code that authorize traffic based on my custom access token?

Open source API Gateway (Apache APISIX and Traefik), Service Mesh (Istio and Linkerd) solutions are capable of doing traffic splitting and implementing functionalities like Canary Release and Blue-Green deployment. With canary testing, you can make a critical examination of a new release of an API by selecting only a small portion of your user base. We will cover the canary release next section.

I have experimented with other service meshes and I was able to get up to speed quickly: Linkerd = 1 day, Istio = 3 days, NGINX Service Mesh = 5 days, but Consul Connect service mesh took at least 11 days to get off the ground. This is by far the most complex solution available.

https://github.com/linkerd/linkerd2 (random example)

Out of the number of service mesh solutions that exist, the most popular open source ones are: Linkerd, Istio, and Consul. Here at Koyeb, we are using Kuma.