As part of my interview prep, last night I challenged myself to do the following:
- Make a Kubernetes cluster (on Google Cloud Platform)
- …running Dockerized Zookeeper (1) and Kafka (2)
- …with Kafka reporting stats into Datadog
- Send in synthetic load from a bunch of Go programs moving messages around on Kafka
- Then run an experiment to kill the Kafka master and watch how the throughput/latencies change.
Since thats a lot of that stuff I’ve never touched before (though I’ve read up on it, and it uses all the same general concepts I’ve worked with for 15 years) it should not be too surprising that I didn’t get it done. Yet.
The surprising thing is where I got stuck. I found a nice pair of Docker containers for Zookeeper and Kafka . I got Zookeeper up and running, and I could see it’s name in the Kubernetes DNS . My two Kafkas were up and running, and they found the Zookeeper via service discovery. So far so good. But then something went wrong with the place where I was going to run clients from; it could not talk to either of the Kafkas via TCP, connection timed out. What’s more, I couldn’t be sure that both of my Kafkas were even being advertised by Kubernetes DNS.
Learning how to debug in the container environment is one of the hardest things. It’s like walking around in a brewery in the dark armed only with a keychain flashlight and your nose, looking for the beer leak.
I think it is time to take a break from container-ville and use small, local Kafka on my Mac to develop the synthetic load generator. That will also be interesting, because I’m hoping to be able to generate spiky, floody flows of messages using feedback from producers to consumers. It is actually something I’ve had in mind for years, and never had the right situation calling on me to finally try it out.