docker

Building R Binary Packages for Linux

Background One of the challenges of producing a performant build environment for linux, such as what might be used to have developers test software in identical environments, is the need to compile R packages from source on linux. If, however, one had an identical set of installed libraries, kernel version, compiler, etc., we could use binary packages in linux as well. Docker provides just such a shareable and identical environment for linux.

Container Notes

General notes about using containers

Using google cloud registry for private docker images

In this post, I will quickly build a docker image containing the sra-toolkit and a key for dbGaP downloads. Because the key file is private, I will be using the secure Google Container Registry to store the image for later use in genomics workflows. Background Container technologies like docker enable quick and easy encapsulation of software, dependencies, and operating systems. One or more containers can render entire software ecosystems portable, enhance reproducibility and reusability, and facilitate sharing of software, tools, and even infrastructure.

export POOL_NAME='preempt-1' export CLUSTER_NAME='cluster-1' gcloud beta container node-pools create ${POOL_NAME} --preemptible \ --cluster ${CLUSTER_NAME} --enable-autoscaling \ --min-nodes=0 --max-nodes=50 \ --machine-type=n1-standard-2 apiVersion: v1 kind: Job spec: nodeSelector: cloud.google.com/gke-preemptible: "true" template: spec: containers: - name: pyversion image: python:3.7 command: ["python", "--version"] restartPolicy: Never backoffLimit: 4