mirror of
https://github.com/ClusterCockpit/cc-backend
synced 2024-11-10 08:57:25 +01:00
9.4 KiB
9.4 KiB
CC-HANDSON - Setup ClusterCockpit from scratch (w/o docker)
Prerequisites
- Perl
- Yarn
- Go
- Optional: curl
- Script migrateTimestamp.pl
Documentation
You find READMEs or api docs in
- ./cc-backend/configs
- ./cc-backend/init
- ./cc-backend/api
ClusterCockpit configuration files
cc-backend
./.env
Passwords and Tokens set in the environment./config.json
Configuration options for cc-backend
cc-metric-store
./config.json
Optional to overwrite configuration options
cc-metric-collector
Not yet included in the hands-on setup.
Setup Components
Start by creating a base folder for all of the following steps.
mkdir clustercockpit
cd clustercockpit
Setup cc-backend
- Clone Repository
git clone https://github.com/ClusterCockpit/cc-backend.git
cd cc-backend
git checkout dev-job-archive-module
Will be merged soon into master
- Setup Frontend
cd ./web/frontend
yarn install
yarn build
cd ../..
- Build Go Executable
go build ./cmd/cc-backend/
- Prepare Datafolder and Database file
mkdir var
touch var/job.db
- Activate & Config environment for cc-backend
cp configs/env-template.txt .env
- Optional: Have a look via
vim ./.env
- Copy the
config.json
file included in this tarball into the root directory of cc-backend:cp ../../config.json ./
- Back to toplevel
clustercockpit
cd ..
Setup cc-metric-store
- Clone Repository
git clone https://github.com/ClusterCockpit/cc-metric-store.git
cd cc-metric-store
- Build Go Executable
go get
go build
- Prepare Datafolders
mkdir -p var/checkpoints
mkdir -p var/archive
- Update Config
vim config.json
- Exchange existing setting in
metrics
with the following:
"clock": { "frequency": 60, "aggregation": null },
"cpi": { "frequency": 60, "aggregation": null },
"cpu_load": { "frequency": 60, "aggregation": null },
"flops_any": { "frequency": 60, "aggregation": null },
"flops_dp": { "frequency": 60, "aggregation": null },
"flops_sp": { "frequency": 60, "aggregation": null },
"ib_bw": { "frequency": 60, "aggregation": null },
"lustre_bw": { "frequency": 60, "aggregation": null },
"mem_bw": { "frequency": 60, "aggregation": null },
"mem_used": { "frequency": 60, "aggregation": null },
"rapl_power": { "frequency": 60, "aggregation": null }
- Back to toplevel
clustercockpit
cd ..
Setup Demo Data
mkdir source-data
cd source-data
- Download JobArchive-Source:
wget https://hpc-mover.rrze.uni-erlangen.de/HPC-Data/0x7b58aefb/eig7ahyo6fo2bais0ephuf2aitohv1ai/job-archive-dev.tar.xz
tar xJf job-archive-dev.tar.xz
mv ./job-archive ./job-archive-source
rm ./job-archive-dev.tar.xz
- Download CC-Metric-Store Checkpoints:
mkdir -p cc-metric-store-source/checkpoints
cd cc-metric-store-source/checkpoints
wget https://hpc-mover.rrze.uni-erlangen.de/HPC-Data/0x7b58aefb/eig7ahyo6fo2bais0ephuf2aitohv1ai/cc-metric-store-checkpoints.tar.xz
tar xf cc-metric-store-checkpoints.tar.xz
rm cc-metric-store-checkpoints.tar.xz
- Back to
source-data
cd ../..
- Run timestamp migration script. This may take tens of minutes!
cp ../migrateTimestamps.pl .
./migrateTimestamps.pl
- Expected output:
Starting to update start- and stoptimes in job-archive for emmy
Starting to update start- and stoptimes in job-archive for woody
Done for job-archive
Starting to update checkpoint filenames and data starttimes for emmy
Starting to update checkpoint filenames and data starttimes for woody
Done for checkpoints
- Copy
cluster.json
files from source to migrated folderscp source-data/job-archive-source/emmy/cluster.json cc-backend/var/job-archive/emmy/
cp source-data/job-archive-source/woody/cluster.json cc-backend/var/job-archive/woody/
- Initialize Job-Archive in SQLite3 job.db and add demo user
cd cc-backend
./cc-backend --init-db --add-user demo:admin:AdminDev
- Expected output:
<6>[INFO] new user "demo" created (roles: ["admin"], auth-source: 0)
<6>[INFO] Building job table...
<6>[INFO] A total of 3936 jobs have been registered in 1.791 seconds.
- Back to toplevel
clustercockpit
cd ..
Startup both Apps
- In cc-backend root:
$./cc-backend --server --dev
- Starts Clustercockpit at
http:localhost:8080
- Log:
<6>[INFO] HTTP server listening at :8080...
- Log:
- Use local internet browser to access interface
- You should see and be able to browse finished Jobs
- Metadata is read from SQLite3 database
- Metricdata is read from job-archive/JSON-Files
- Create User in settings (top-right corner)
- Name
apiuser
- Username
apiuser
- Role
API
- Submit & Refresh Page
- Name
- Create JTW for
apiuser
- In Userlist, press
Gen. JTW
forapiuser
- Save JWT for later use
- In Userlist, press
- Starts Clustercockpit at
- In cc-metric-store root:
$./cc-metric-store
- Start the cc-metric-store on
http:localhost:8081
, Log:
- Start the cc-metric-store on
2022/07/15 17:17:42 Loading checkpoints newer than 2022-07-13T17:17:42+02:00
2022/07/15 17:17:45 Checkpoints loaded (5621 files, 319 MB, that took 3.034652s)
2022/07/15 17:17:45 API http endpoint listening on '0.0.0.0:8081'
- Does *not* have a graphical interface
- Otpional: Test function by executing:
$ curl -H "Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJFZERTQSJ9.eyJ1c2VyIjoiYWRtaW4iLCJyb2xlcyI6WyJST0xFX0FETUlOIiwiUk9MRV9BTkFMWVNUIiwiUk9MRV9VU0VSIl19.d-3_3FZTsadPjDEdsWrrQ7nS0edMAR4zjl-eK7rJU3HziNBfI9PDHDIpJVHTNN5E5SlLGLFXctWyKAkwhXL-Dw" -D - "http://localhost:8081/api/query" -d "{ \"cluster\": \"emmy\", \"from\": $(expr $(date +%s) - 60), \"to\": $(date +%s), \"queries\": [{
\"metric\": \"flops_any\",
\"host\": \"e1111\"
}] }"
HTTP/1.1 200 OK
Content-Type: application/json
Date: Fri, 15 Jul 2022 13:57:22 GMT
Content-Length: 119
{"results":[[JSON-DATA-ARRAY]]}
Development API web interfaces
The --dev
flag enables web interfaces to document and test the apis:
- http://localhost:8080/playground - A GraphQL playground. To use it you must have a authenticated session in the same browser.
- http://localhost:8080/swagger - A Swagger UI. To use it you have to be logged out, so no user session in the same browser. Use the JWT token with role Api generate previously to authenticate via http header.
Use cc-backend API to start job
- Enter the URL
http://localhost:8080/swagger/index.html
in your browser. - Enter your JWT token you generated for the API user by clicking the green Authorize button in the upper right part of the window.
- Click the
/job/start_job
endpoint and click the Try it out button. - Enter the following json into the request body text area and fill in a recent start timestamp by executing
date +%s
.:
{
"jobId": 100000,
"arrayJobId": 0,
"user": "ccdemouser",
"subCluster": "main",
"cluster": "emmy",
"startTime": <date +%s>,
"project": "ccdemoproject",
"resources": [
{"hostname": "e0601"},
{"hostname": "e0823"},
{"hostname": "e0337"},
{"hostname": "e1111"}],
"numNodes": 4,
"numHwthreads": 80,
"walltime": 86400
}
- The response body should be the database id of the started job, for example:
{
"id": 3937
}
- Check in ClusterCockpit
- User
ccdemouser
should appear in Users-Tab with one running job - It could take up to 5 Minutes until the Job is displayed with some current data (5 Min Short-Job Filter)
- Job then is marked with a green
running
tag - Metricdata displayed is read from cc-metric-store!
- User
Use cc-backend API to stop job
- Enter the URL
http://localhost:8080/swagger/index.html
in your browser. - Enter your JWT token you generated for the API user by clicking the green Authorize button in the upper right part of the window.
- Click the
/job/stop_job/{id}
endpoint and click the Try it out button. - Enter the database id at id that was returned by
start_job
and copy the following into the request body. Replace the timestamp with a recent one:
{
"cluster": "emmy",
"jobState": "completed",
"stopTime": <RECENT TS>
}
-
On success a json document with the job meta data is returned.
-
Check in ClusterCockpit
- User
ccdemouser
should appear in Users-Tab with one completed job - Job is no longer marked with a green
running
tag -> Completed! - Metricdata displayed is now read from job-archive!
- User
-
Check in job-archive
cd ./cc-backend/var/job-archive/emmy/100/000
cd $STARTTIME
- Inspect
meta.json
anddata.json
Helper scripts
- In this tarball you can find the perl script
generate_subcluster.pl
that helps to generate the subcluster section for your system. Usage: - Log into an exclusive cluster node.
- The LIKWID tools likwid-topology and likwid-bench must be in the PATH!
$./generate_subcluster.pl
outputs the subcluster section onstdout
Please be aware that
- You have to enter the name and node list for the subCluster manually.
- GPU detection only works if LIKWID was build with Cuda avalable and you run likwid-topology also with Cuda loaded.
- Do not blindly trust the measured peakflops values.
- Because the script blindly relies on the CSV format output by likwid-topology this is a fragile undertaking!