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License: MIT License
The students are spending too much time setting up the environments.
Update recourse limits for the following examples:
We need a 101 session about K8s in the exercises during the first lecture
As requested during the midway evaluation, a cheat sheet overview of the technologies would be nice to have.
Multiple groups are having issues running their workload. They report issues when deploying spark orchestrators and runners.
Make sure the next year's exercises are running:
We need computing resources before the course starts.
Due to GitHub actions two of the referenced images have changed location:
On Mac and Linux the service command does not work if the service is not a NodePort or LoadBalancer type.
https://minikube.sigs.k8s.io/docs/drivers/
If you don't have docker installed then a different driver will be used. Install docker / docker desktop and then set up minikube.
At one point in exercise 1 you give a task to create our pods within a stackable namespace
https://github.com/jakobhviid/BigDataCourseExercises/blob/main/lectures/02/exercises.md?plain=1#L18-L20
But in another part of exercise 1 it is said we need to create the hdfs cluster within another namespace
https://github.com/jakobhviid/BigDataCourseExercises/blob/main/lectures/02/exercises.md?plain=1#L42
For this semester we have one server therefore we need a different abstraction than the previous semesters.
Affected lecture: Lecture 03 - Distributed Transport and Streaming
checkup on cross referred lectures.
Make sure kubectl port-forward
is performed on a service and not on a pod in the exercises.
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