tetragon VS zipkin

Many interesting software are coming from the community, many are distributed through the package manager of the operating system. But for the others, you can download them from Github release pages, use snap or homebrew to cite a few. But this last installation method bypasses the security team that tries to improve the security of your operating system. By doing so, you are implicitly trusting the author he is not distributing malware or implementing backdoors. How many tools did you install by hand? Do you really trust all of them? Confidence is very important, yet it would be nice to limit capabilities for a set of binary that you don't fully trust. In this blog post, we will use Tetragon to forbid network usage for tools that don't need to.

Falco is a cloud native Kubernetes threat detection tool. It can detect unexpected behavior, intrusions, and data theft in real time. In the backend, it uses Linux eBPF technology to trace your system and applications at runtime. For example, it can detect if someone tries to read a secret file inside a container, access a pod as a root user, etc, and trigger a webhook or send logs to the monitoring system. There are similar tools like Tetragon, KubeArmor, and Tracee which also provide Kubernetes runtime security.

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.