Resolve "Implement Quarkus/Kotlin protype"

This MR resolves most of #109 (closed) and contains the first part of a prototype for a theodolite implementation in Kotlin.

At the moment, this MR contains the following parts:

• #129 (closed) Implementation for search strategies and restrictions
  • Linear search
  • Binary search
  • lower bound restriction
  • simple unit test
• #133 (closed) (merged with !82 (merged)) Adds a logging capability
• #130 (closed) Features of run_uc -> #126 (closed) and #127 (closed)
• #127 (closed) (merged with !79 (closed))
  • Communication with zookeeper, for example for resetting after a experiment run
• #126 (closed) (merged with !81 (closed))
  • Communication with Kafka, for example to create or delete Topics
• an execution package as a starting point for running theodolite
• ability to load Kubernetes resource configuration as yaml files, configure the loaded resource and deploy the modified resources to K8s. And, based on this, the implementation of the benchmark UC1 (I couldn't find a ticket for this, is there one already @stu203404)

Todos before ready to merge:

• apply open reviews (mostly for @stu203404)
• apply open reviews (mostly for @stu200776 and @stu126940)
• replace print statement with logger calls to fully resolve #133 (closed)
• finalize exemplary implementation of UC1
• maybe we should add a basic implementation of the SLOChecker (#135 (closed)) and the MetricFetcher (#139 (closed)) before merge moved to #135 (closed) and #139 (closed)

This MR closes:

Closes #126 (closed), Closes #127 (closed), Closes #133 (closed), Closes #129 (closed)

analysis/README.md

@@ -4,7 +4,7 @@ This directory contains Jupyter notebooks for analyzing and visualizing
 benchmark execution results and plotting. The following notebooks are provided:
 
 * [demand-metric.ipynb](demand-metric.ipynb): Create CSV files describing scalability according to the Theodolite `demand` metric.
-* [demand-metric-plot.ipynb](demand-metric-plot.ipynb): Create plots based on such CSV files.
+* [demand-metric-plot.ipynb](demand-metric-plot.ipynb): Create plots based on such CSV files of the `demand` metric.
 
 For legacy reasons, we also provide the following notebooks, which, however, are not documented: