3d9acf2fff
This entails writing a metric aggregation program since each worker has its own memory, and thus own metrics because of python gunicorn. The python client is a simple wrapper that makes web requests to it.
42 lines
686 B
Bash
Executable file
42 lines
686 B
Bash
Executable file
#!/bin/bash
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set -e
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REPO=quay.io/quay/quay-dev
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d ()
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{
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docker build -t $REPO -f dev.df .
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docker -- run --rm -v /var/run/docker.sock:/run/docker.sock -it --net=host -v $(pwd)/..:/src $REPO $*
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}
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case $1 in
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buildman)
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d /venv/bin/python -m buildman.builder
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;;
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dev)
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d bash /src/quay/local-run.sh
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;;
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notifications)
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d /venv/bin/python -m workers.notificationworker
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;;
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test)
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d bash /src/quay/local-test.sh
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;;
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initdb)
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rm -f test/data/test.db
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d /venv/bin/python initdb.py
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;;
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fulldbtest)
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d bash /src/quay/test/fulldbtest.sh
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;;
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prom)
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R=quay.io/quay/prom-monitor
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docker build -t $R prom_aggregator
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docker run --rm -it --net=host $R
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;;
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*)
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echo "unknown option"
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exit 1
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;;
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esac
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