https://github.com/bhklab/azure-aks-snakemake-merida
Scripts to configure and run the MERIDA_snakemake_pipeline on Azure Kubernetes Service
https://github.com/bhklab/azure-aks-snakemake-merida
Last synced: 3 months ago
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Scripts to configure and run the MERIDA_snakemake_pipeline on Azure Kubernetes Service
- Host: GitHub
- URL: https://github.com/bhklab/azure-aks-snakemake-merida
- Owner: bhklab
- Created: 2022-03-09T22:43:48.000Z (about 3 years ago)
- Default Branch: master
- Last Pushed: 2022-03-15T18:24:14.000Z (about 3 years ago)
- Last Synced: 2024-12-30T03:24:26.561Z (5 months ago)
- Language: Shell
- Size: 13.7 KB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Azure Kubernetes Service (AKS) Cluster for Snakemake Deployment
Repository with code to provision an AKS cluster which can be used to
dynamically scale compute resources for an arbitrary Snakemake pipeline.
## Requirments
### Installing Miniconda
This repo uses conda to simplify dependency management and installation.
To get started with setup you can install miniconda3 using the instructions available here: https://docs.conda.io/en/latest/miniconda.html.
### Setting Up Your Software Environment
The first step to deploying an analysis pipeline is to install the various
software packages it depends on.
All commands should be executed from the top level directory of this repository.
### Python and System Dependencies
Conda can be used to install all Python and most OS system dependencies using:
```
conda env create --file envs/aks-snakemake.yml
```
This will take some time to run as it gathers and installs the correct package versions. The environment it creates should be called `aks-snakemake`.
If it is not automatically activated after installation please run
`conda activate aks-snakemake` before proceeding to the next step.
## Configuration
Open the files named `dot_*`, fill in your values for the requested configuration variables, then rename the files as instructed in the
comments in each file.
This will ensure your specific configuration is not pushed to the
GitHub.
## Deployment
TODO::
## References
1. [Auto-scaling Azure Kubernetes cluster without shared filesystem](https://snakemake.readthedocs.io/en/stable/executor_tutorial/azure_aks.html)
2. [Deploy a model to an Azure Kubernetes Service cluster](https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-azure-kubernetes-service?tabs=python)