This is a course that is designed to get you from A, knowing little to very little about application deployment with Docker, to Z, deploying and scaling your Python applications with Docker, Docker Swarm and Kubernetes (for the brave!). Once you have your foundation set up you can deploy your applications in house or on the cloud using AWS, GCP, or Azure!
Step by step walkthrough of setting up your first EC2 instance on AWS, even if you are a total beginner. This walks you through creating an IAM user, the EC2 console, SSHing to your instance, exposing ports with security groups and installing packages.
Free DevOps for Data Scientists tutorials emailed to you each week on topics such as getting started with Docker, deploying RShiny on AWS, deploying with Kubernetes, data visualization infrastructure, and more.
Here is a fully formed and ready for production project template. Included: Extensive technical documentation, Dockerfiles for creating a custom image with Miniconda or using the base R rocker/shiny image, a base helm chart with the NGINX ingress, and a helm chart with the NGINX ingress and AWS EFS (networked storage) configuration.
A simple howto guide to configure Apache Airflow with a PostgreSQL or MySQL database backend and Celery Executor.
Install and manage bioinformatics software without losing your mind using Conda, Modules and EasyBuild. Using these tools covers all your bases, including common software like samtools, creating bundles such as for RNASeq, and do not distribute software such as CellRanger from 10X Genomics. The ebook is available as a PDF and as a zip file containing the original markdown files used to generate the PDF.
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