Quickstart

This runs through the installation and usage of 2019-snakemake-byok8s.

Step 1: Set up Kubernetes cluster with minikube.

Step 2: Install byok8s.

Step 3: Run the byok8s workflow using the Kubernetes cluster.

Step 4: Tear down Kubernetes cluster with minikube.

Step 1: Set Up Virtual Kubernetes Cluster

For the purposes of the quickstart, we will walk through how to set up a local, virtual Kubernetes cluster using minikube.

Start by installing minikube:

scripts/install_minikube.sh

Once it is installed, you can start up a kubernetes cluster with minikube using the following commands:

cd test
minikube start

NOTE: If you are running on AWS, run this command first

minikube config set vm-driver none

to set the the vm driver to none and use native Docker to run stuff.

If you are running on AWS, the DNS in the minikube kubernetes cluster will not work, so run this command to fix the DNS settings (should be run from the test/ directory):

kubectl apply -f fixcoredns.yml
kubectl delete --all pods --namespace kube-system

Step 2: Install byok8s

Start by setting up a python virtual environment, and install the required packages into the virtual environment:

pip install -r requirements.txt

This installs snakemake and kubernetes Python modules. Now install the byok8s command line tool:

python setup.py build install

Now you can run:

which byok8s

and you should see byok8s in your virtual environment's bin/ directory.

This command line utility will expect a kubernetes cluster to be set up before it is run.

Setting up a kubernetes cluster will create... (fill in more info here)...

Snakemake will automatically create the pods in the cluster, so you just need to allocate a kubernetes cluster.

Step 3: Run byok8s

Now you can run the workflow with the byok8s command. This submits the Snakemake workflow jobs to the Kubernetes cluster that minikube created.

You should have your workflow in a Snakefile in the current directory. Use the --snakefile flag if it is named something other than Snakefile.

You will also need to specify your AWS credentials via the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables. These are used to to access S3 buckets for file I/O.

Finally, you will need to create an S3 bucket for Snakemake to use for file I/O. Pass the name of the bucket using the --s3-bucket flag.

Start by exporting these two vars (careful to scrub them from bash history):

export AWS_ACCESS_KEY_ID=XXXXX
export AWS_SECRET_ACCESS_KEY=XXXXX

Run the alpha workflow with blue params:

byok8s --s3-bucket=mah-bukkit workflow-alpha params-blue

Run the alpha workflow with red params:

byok8s --s3-bucket=mah-bukkit workflow-alpha params-red

Run the gamma workflow with red params, &c:

byok8s --s3-bucket=mah-bukkit workflow-gamma params-red

(NOTE: May want to let the user specify input and output directories with flags.)

All input files are searched for relative to the working directory.

Step 4: Tear Down Kubernetes Cluster

The last step once the workflow has been finished, is to tear down the kubernetes cluster. The virtual kubernetes cluster created by minikube can be torn down with the following command:

minikube stop