February 2018 Summaries

This guide provides examples for writing Dockerfiles for Python web apps. It covers using appropriate base images (debian for dev, alpine for production), hot reloading during development with gunicorn, optimizing cache layers, serving static files, and multi-stage production builds to reduce final image size. The tutorial also includes a simple directory structure, Dockerfile examples, .dockerignore file, hot reloading with Gunicorn, running single python scripts, serving static files, single stage production build, and multi-stage production build.

Running a proof-of-concept for HDFS (Hadoop Distributed File System) on Kubernetes involves adapting the traditional HDFS architecture, where namenodes and datanodes are typically deployed on dedicated VMs, to a Kubernetes environment. In Kubernetes, the ephemeral nature of pods necessitates solutions like wrapping the namenode in a Service to provide a static IP or hostname for reliable communication, while Stateful Sets ensure datanodes maintain consistent identities and data. This setup allows for a fully distributed HDFS to run on a single node by utilizing Kubernetes Persistent Volumes to emulate multiple storage volumes on a single disk. The implementation demonstrates how Kubernetes can manage container-level distribution, even on a single node, paving the way for running applications like Apache Spark on this HDFS setup in future explorations.

This guide provides an exhaustive approach to writing Dockerfiles for Node.js web applications. It covers various aspects such as using appropriate base images (carbon for development and alpine for production), hot reloading during development with nodemon, optimizing Docker cache layers, serving static files, multi-stage production builds, and some pro tips like using COPY over ADD and handling CTRL-C kernel signals. The guide also includes examples of simple Dockerfile and .dockerignore file, hot reloading with nodemon, optimizations for better performance, serving static files, single-stage and multi-stage production builds.

This guide provides a comprehensive tutorial on writing Dockerfiles for Go web applications. It covers various aspects such as packaging as a container, working with different versions of Go, creating reproducible environments, and building and deploying final compiled binaries. The text also discusses live reloading, package management, single-stage production builds, multi-stage production builds, binary compression using UPX, and the use of dep instead of glide for dependency management. Additionally, it introduces a new section on using scratch as the base image instead of alpine to further reduce the size of the final Docker image.