This is a Jupyter notebook designed to pull usage data from the monitoring system at https://monitoring.lsst.cloud. It then uses that to make initial guesses at what requests and limits for the various Phalanx apps should be set to.
- Python 3.11 or later
- JupyterLab environment
- Start in the repository root directory
- Create a new virtualenv:
python3 -m venv <path_to_venv>
- Activate it:
. <path_to_venv>/bin/activate
- Update pip:
pip3 install --upgrade pip
- Install requirements:
pip3 install -r requirements.txt
- Create a Jupyter kernel from the virtualenv:
python -m ipykernel install --user --name=<new_kernel>
- Put a token allowing you read access to all InfluxDBv2 buckets in the repository root as
influxdb.token
- Open limits.ipynb and select your new kernel as the kernel that will run it in the upper right.
- From the JupyterLab
Run
menu,Restart Kernel and Run All Cells...
- After a while, summary.json will contain recommendations for all your Phalanx applications in each environment
- From this data, create a set of appropriate generic and site-overridden values for each application