add-training.sh

#!/bin/bash

export LC_NUMERIC="en_US.UTF-8"

if ([ $# -lt 5 ]); then
    echo "Usage:"
    echo
    echo "  $0 <training-identifier> <vm-size (e.g. c1.c28m225d50)> <vm-count> <start in YYYY-mm-dd> <end in YYYY-mm-dd> [--donotautocommitpush]"
    echo
    exit 1;
fi

training_identifier=$(echo "$1" | tr '[:upper:]' '[:lower:]')
vm_size=${2:-c.c10m55}
vm_count=${3:-1}
start=$4
end=$5
autopush=1
if [[ "$6" == "--donotautocommitpush" ]]; then
	autopush=0
fi

short=$(echo "$training_identifier" | cut -c1-4)

output="instance_training-${training_identifier}.tf"

cat >> resources.yaml <<-EOF
  training-${short}:
    count: ${vm_count}
    flavor: ${vm_size}
    start: ${start}
    end: ${end}
    group: training-${training_identifier}
EOF

if (( autopush == 1 )); then
	git add resources.yaml
	git commit -m 'New training'
	git push
fi

vm_cpu=$(echo $vm_size | sed 's/[^0-9]/ /g' | awk '{print $2}')
vm_mem=$(echo $vm_size | sed 's/[^0-9]/ /g' | awk '{print $3}')

ts_end=$(date -d "$end 23:59" +%s)
ts_stt=$(date -d "$start 00:00" +%s)
vm_seconds=$(( ts_end - ts_stt ))
price=$(python3 cost.py $vm_cpu $vm_mem $vm_seconds | head -n 1)
machines=$(python3 cost.py $vm_cpu $vm_mem $vm_seconds | tail -n 1)
aws_id=$(echo $machines | sed "s/'/\"/g" | jq .name -r)
price=$(echo "$price * $vm_count" | bc -l)
price_int=$(printf "%0.2f" $price)
yourname=$(git config --global --get user.name)

printf "
Subject: UseGalaxy.eu TIaaS Request: Approved

Dear **X**,

Thanks for submitting your TIaaS request! Based on your choice, we have allocated ${vm_count} servers, each with ${vm_cpu} cores and ${vm_mem} GB of RAM. If you find that it is not enough for your training, please contact us and we can update that at any time.

TIaaS provides a private queue for your training in addition to the regular one, which should make your jobs run a bit faster. To make use of it, we have created a training group for you that is accessible at

https://usegalaxy.eu/join-training/${training_identifier}

Please ask your users to go to that URL during your training (from ${start} to ${end}). Once it is over, the link will not be usable anymore but the users can still access their data at usegalaxy.eu.

Queue Status:
If you find yourself wondering where your students are during the training, you can use the queue status page to see which jobs are being run by people in your training: https://usegalaxy.eu/join-training/${training_identifier}/status

Support:
If during the workshop you experience issues with the server, you can ask for support in the Galaxy Europe Gitter channel: https://matrix.to/#/#usegalaxy-eu_Lobby:gitter.im

AWS Estimate:
If you wanted to run a similar training on AWS, we estimate that for ${vm_count} ${aws_id}machine(s), it would cost ${price_int} USD.

Workshop Feedback:
When your workshop is over, if you used GTN materials, please let us know how it went on the workshop feedback issue: https://github.com/galaxyproject/training-material/issues/1452

TIaaS Feedback:
We encourage you to send us a short review sharing your experience, tips for other instructors,... that we will publish in https://galaxyproject.eu/news?tag=TIaaS. Your feedback is very valuable to keep this service up and running for free.

We really appreciate your support. Thank you very much for using Galaxy and don't hesitate to contact us if you have any questions!

Kind regards,

${yourname}

--
UseGalaxy.eu
Bioinformatics Group
Department of Computer Science
Albert-Ludwigs-University Freiburg
Georges-Köhler-Allee 106
79110 Freiburg, Germany
"