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Debugging CUBE Services without Containers
CUBE is a complex software infrastructure, comprising the main core backend, as well as a constellation of ancillary services. Usually, if things break, the first place to start debugging is to make sure the ancillary services are all OK. This page documents a workflow that can be useful in debugging these CUBE services. Essentially, instructions on starting each core service directly (i.e. not in containers) is provided.
Due to the distributed and containerized nature of CUBE, debugging the ancillary services, pfcon, pfioh, and pman can be particularly difficult. The most effective method of debugging is to run the services non-containerized, but preserving the pattern of volume mounts using symbolic links in the host filesystem, followed by a typical CUBE directive.
Create the following paths on the host FS -- in any directory. I typically do this in the ChRIS_ultron_backend dir, but for debugging the services outside of ChRIS, any directory (like ~/tmp) will be fine:
mkdir -p ./FS/remote # Simulate remote FS
chmod 777 ./FS/remote
# To debug "local" services, uncomment the following
# (Note that at first this is probably not necessary)
# mkdir -p ./FS/local # Simulate local FS
# chmod 777 ./FS/local
sudo mkdir /hostFS
sudo ln -s $(pwd)/FS/remote /hostFS/storeBase # Simulates the FS within the pman/pfioh
# containers
# If you are trying to debug *all* services, including 'local' ones,
# uncomment the below
#sudo ln -s $(pwd)/FS/local /hostFS/pfconFS # Simulates the FS within the pfcon/cube
# containers
sudo mkdir -p /usr/users # Explicitly maps the CUBE internal path
sudo chmod 777 /usr/usersThe storeBase will be used by pfioh and pman and simulates the remote FS. The pfconFS and /usr/users simulates the local and CUBE DB trees.
You must export an environment variable, HOST_IP to the terminal running pfurl and ``pfcon```. On Linux this is:
export HOST_IP=$(ip route | grep -v docker | awk '{if(NF==11) print $9}')A source of some frustration can be the pfurl module which is used internally by pfcon. If debugging pfurl code while debugging the interaction of the services, it is a good idea to link the pfurl.py module in the virtualenv to the file being edited. In my setup, this is effected by:
cd ~/src/python-env/chris_env/lib/python3.5/site-packages/pfurl
mv pfurl.py pfurl.orig.py
ln -s ~/src/pfurl/pfurl/pfurl.py .Alternatively, if you make changes to pfurl and propagate these all the way through the git repo, docker hub, and up to PiPy, then you can install this laters pfurl in the virtualenv for pfcon to use:
pip3 install pfurl==X.Y.Zwhere X.Y.Z is the version of pfurl to install.
The simplest way to debug is to open four terminals. Each terminal will be used to run a specific service. Typically from left to right the terminals should be anchored in the following source repositories:
| Terminal 1 | Terminal 2 | Terminal 3 | Terminal 4 |
|---|---|---|---|
| pfurl | pfcon | pfioh | pman |
In each terminal, cd to the bin dir of each, and run the respective service from terminal
./pfcon --forever --httpResponse
./pfioh --forever --httpResponse --createDirsAsNeeded --storeBase /hostFS/storeBase
rm -fr /tmp/pman ; ./pman --rawmode 1 --http --port 5010 --listeners 12It is important that all the services need to stop and be restarted each time a change is made. In particular, the pman service needs its database cleared if the same job is being submitted repeatedly during debugging.
If you don't rm -fr /tmp/pman before each call to pman you WILL get unpredictable results and behaviour!
In debugging one often will repeat the same pfurl command and associated JSON over and over again. Within this JSON is a directive specifying the service name to the swarm manager. Sometimes, the service remains in the swarm scheduler and if the same pfurl is resent with the same service name, pman will throw an internal exception that is hard to notice.
The solution is to check on the swarm service using
dsland if it exists, to remove the service
dss <service>where dsl (docker service list) is a shell alias
alias dsl="docker service ls "and dss (docker service stop) another alias
alias dss="docker service rm "Assuming satisfied preconditions, let's say hello to pfcon. It will in turn ask each of pfioh and pman hello and return the response.
./pfurl --verb POST --raw --http ${HOST_IP}:5005/api/v1/cmd --httpResponseBodyParse --jsonwrapper 'payload' --msg \
'{ "action": "hello",
"meta": {
"askAbout": "sysinfo",
"echoBack": "Hi there!",
"service": "host"
}
}'To find the status on a job, say job 89 as in the examples below, use
./pfurl --verb POST --raw --http ${HOST_IP}:5005/api/v1/cmd --httpResponseBodyParse --jsonwrapper 'payload' --msg \
'{ "action": "status",
"meta": {
"remote": {
"key": "89"
},
"service": "host"
}
}'In these calls, be sure that the HOST_IP env variable is set correctly.
First, a simplefsapp plugin:
./pfurl --verb POST --raw --http ${HOST_IP}:5005/api/v1/cmd --httpResponseBodyParse --jsonwrapper 'payload' --msg '
{ "action": "coordinate",
"threadAction": true,
"meta-store": {
"meta": "meta-compute",
"key": "jid"
},
"meta-data": {
"remote": {
"key": "%meta-store"
},
"localSource": {
"path": "/data/dicomDir"
},
"localTarget": {
"path": "/usr/users/test/foo/feed_90/simplefsapp_90/data",
"createDir": true
},
"specialHandling": {
"op": "plugin",
"cleanup": true
},
"transport": {
"mechanism": "compress",
"compress": {
"encoding": "none",
"archive": "zip",
"unpack": true,
"cleanup": true
}
},
"service": "host"
},
"meta-compute": {
"cmd": "$execshell $selfpath/$selfexec /share/outgoing --saveinputmeta --dir ./",
"auid": "rudolphpienaar",
"jid": "89",
"threaded": true,
"container": {
"target": {
"image": "fnndsc/pl-simplefsapp",
"cmdParse": true
},
"manager": {
"image": "fnndsc/swarm",
"app": "swarm.py",
"env": {
"meta-store": "key",
"serviceType": "docker",
"shareDir": "%shareDir",
"serviceName": "89"
}
}
},
"service": "host"
}
}' Here is a slightly more useful plugin, the "fake" dircopy container:
./pfurl --verb POST --raw --http ${HOST_IP}:5005/api/v1/cmd --httpResponseBodyParse --jsonwrapper 'payload' --msg '
{ "action": "coordinate",
"threadAction": true,
"meta-store": {
"meta": "meta-compute",
"key": "jid"
},
"meta-data": {
"remote": {
"key": "%meta-store"
},
"localSource": {
"path": "/data/dicomDir"
},
"localTarget": {
"path": "/usr/users/test/foo/feed_90/simplefsapp_90/data",
"createDir": true
},
"specialHandling": {
"op": "plugin",
"cleanup": true
},
"transport": {
"mechanism": "compress",
"compress": {
"encoding": "none",
"archive": "zip",
"unpack": true,
"cleanup": true
}
},
"service": "host"
},
"meta-compute": {
"cmd": "$execshell $selfpath/$selfexec /share/outgoing --saveinputmeta --dir /share/incoming",
"auid": "rudolphpienaar",
"jid": "89",
"threaded": true,
"container": {
"target": {
"image": "fnndsc/pl-dircopy",
"cmdParse": true
},
"manager": {
"image": "fnndsc/swarm",
"app": "swarm.py",
"env": {
"meta-store": "key",
"serviceType": "docker",
"shareDir": "%shareDir",
"serviceName": "89"
}
}
},
"service": "host"
}
}' In this call, be sure that the HOST_IP env variable is set correctly. Now, a call to the pl-simpledsapp:
pfurl --verb POST --raw --http ${HOST_IP}:5005/api/v1/cmd --httpResponseBodyParse --jsonwrapper 'payload' --msg '
{ "action": "coordinate",
"threadAction": true,
"meta-store": {
"meta": "meta-compute",
"key": "jid"
},
"meta-data": {
"remote": {
"key": "%meta-store"
},
"localSource": {
"path": "/neuro/users/rudolphpienaar/Pictures"
},
"localTarget": {
"path": "/home/rudolph/tmp/Pictures",
"createDir": true
},
"specialHandling": {
"op": "plugin",
"cleanup": true
},
"transport": {
"mechanism": "compress",
"compress": {
"encoding": "none",
"archive": "zip",
"unpack": true,
"cleanup": true
}
},
"service": "host"
},
"meta-compute": {
"cmd": "$execshell $selfpath/$selfexec --sleepLength 0 --prefix out- /share/incoming /share/outgoing",
"auid": "rudolphpienaar",
"jid": "89",
"threaded": true,
"container": {
"target": {
"image": "fnndsc/pl-simpledsapp",
"cmdParse": true
},
"manager": {
"image": "fnndsc/swarm",
"app": "swarm.py",
"env": {
"meta-store": "key",
"serviceType": "docker",
"shareDir": "%shareDir",
"serviceName": "89"
}
}
},
"service": "host"
}
}
'A more meaningful example, using the pl-med2img plugin:
pfurl --verb POST --raw --http ${HOST_IP}:5005/api/v1/cmd --httpResponseBodyParse --jsonwrapper 'payload' --msg '
{ "action": "coordinate",
"threadAction": true,
"meta-store": {
"meta": "meta-compute",
"key": "jid"
},
"meta-data": {
"remote": {
"key": "%meta-store"
},
"localSource": {
"path": "/usr/users/test/foo/feed_90/simplefsapp_90/data"
},
"localTarget": {
"path": "/usr/users/test/foo/feed_90/simplefsapp_90/med2img/data,
"createDir": true
},
"specialHandling": {
"op": "plugin",
"cleanup": true
},
"transport": {
"mechanism": "compress",
"compress": {
"encoding": "none",
"archive": "zip",
"unpack": true,
"cleanup": true
}
},
"service": "host"
},
"meta-compute": {
"cmd": "$execshell $selfpath/$selfexec --outputFileType jpg --sliceToConvert -1 --func invertIntensities /share/incoming /share/outgoing",
"auid": "rudolphpienaar",
"jid": "90",
"threaded": true,
"container": {
"target": {
"image": "fnndsc/pl-med2img",
"cmdParse": true
},
"manager": {
"image": "fnndsc/swarm",
"app": "swarm.py",
"env": {
"meta-store": "key",
"serviceType": "docker",
"shareDir": "%shareDir",
"serviceName": "89"
}
}
},
"service": "host"
}
}
'Running all the services containerized can result in a lag in debugging, mostly because log files sometimes need to be fully flushed. At times, it is better to run the services non-containerized.
In such instances, add a breakpoint using pudb.set_trace() typically in charm.py. Then start the CUBE dev environment in a containerized fashion:
sudo rm -fr /hostFS/storeBase/* ; sudo rm -fr /usr/users/* ; *make*When execution stops at the breakpoint, kill all the ancillary containers
dkrm pfcon
dkrm pfioh
dkrm pmanwhere dkrm is actually a function I have in .bashrc
dkrm ()
{
NAME=$1;
ID=$(dkl | grep $NAME | awk '{print $1}');
docker stop $ID && docker rm -vf $ID
}and then restart these services directly as per instructions above.