inference VS kafdrop

Yeah, inference[1] is our open source package for running locally (either directly in Python or via a Docker container). It works with all the models on Universe, models you train yourself (assuming we support the architecture; we have a bunch of notebooks available[2]), or train in our platform, plus several more general foundation models[3] (for things like embeddings, zero-shot detection, question answering, OCR, etc).

We also have a hosted API[4] you can hit for most models we support (except some of the large vision models that are really GPU-heavy) if you prefer.

[1] https://github.com/roboflow/inference

[2] https://github.com/roboflow/notebooks

[3] https://inference.roboflow.com/foundation/about/

[4] https://docs.roboflow.com/deploy/hosted-api

Are there any comparison to CMAK or Kafdrop ?

For Kafka I really liked using tools like conduktor or Kafdrop where you can basically create a subscription ad look at topics, events and payloads.

Kafdrop - https://github.com/obsidiandynamics/kafdrop

No mentions, and 1 open issue with a question 2) Kafka Drop https://github.com/obsidiandynamics/kafdrop

Kafdrop (https://github.com/obsidiandynamics/kafdrop) is very popular and pretty solid. I'd start there. Kafka itself also comes with some cli tools and you can also extract metrics out of it via JMX/jolokia.

Kafdrop