e2e: fuzz topology-aware

[askervin]

No description provided.

[codecov-io]

Codecov Report

Merging #621 (4c42d5f) into master (d62a007) will increase coverage by 2.96%.
The diff coverage is 77.21%.

@@            Coverage Diff             @@
##           master     #621      +/-   ##
==========================================
+ Coverage   36.27%   39.23%   +2.96%     
==========================================
  Files          52       52              
  Lines        6388     6943     +555     
==========================================
+ Hits         2317     2724     +407     
- Misses       3831     3954     +123     
- Partials      240      265      +25     

Impacted Files	Coverage Δ
...manager/policy/builtin/topology-aware/resources.go	66.04% <74.64%> (+8.07%)	⬆️
...urce-manager/policy/builtin/topology-aware/node.go	51.37% <100.00%> (+0.14%)	⬆️
...rce-manager/policy/builtin/topology-aware/pools.go	61.18% <100.00%> (+0.46%)	⬆️
...rce-manager/policy/builtin/topology-aware/cache.go	37.77% <0.00%> (+1.17%)	⬆️
pkg/dump/dump.go	60.81% <0.00%> (+4.47%)	⬆️

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[klihub]

That looks really nice !

I was trying to hack together something very similar using pure bash with random-generated sequence of actions of start, stop, restart, sleep N, fail C, exit C, and check (start/stop/restart the pod, sleep for N, stop container C with a simulated failure/success (exit 1/exit 0), checking actual vs. expected state). Instead of signals I was controlling the containers with a per-pod-per-container hostPath mounted /ctrl/ctrl file system entry which was read with a tail -F loop for commands (exit, fail)...

But I'll abort that exercise, this looks so much better, especially I imagine the verification part should be easier.

[askervin]

• Removed generated test code.
• Added big fat warning on skipping the test when generated tests are not found.
• Added help on generating tests.
• Added help on building fMBT (test generator) docker image if not found.
• Production Dockerfiles (fmbt-gui and fmbt-cli) added to fMBT devel branch for more decently sized images (0.4 GB vs 0.8 GB vs. 2.5 GB)

[klihub]

LGTM