When we have to process a large number of files, we should be aware of the resources the process consumes. Here's the scenario I faced in my work recently: we have to create one archive file from lots of files that are stored on an S3 bucket. Created archive files must be placed on another S3 bucket. The number of files of an archive could be 700,000. The size of each file is up to 10MiB.
Stripe provides an easy way to implement subscription services. This document explains how Stripe's subscription works and the things you can. They also provide an example to implement fixed-price subscriptions, like Netflix. You can try the example repository on GitHub and see the whole lifecycle of a subscription. Actually, you don't have to even set up any environment for the example app if you have Docker on your computer. The only dependency is Docker.
Sometimes I want to make multiple outputs from multiple processes into one single output. Let's say we have to aggregate K8s pod logs from a deployment. We could do that by redirecting each output to a file and follow the file by tail -f like below. tempfile=$(mktemp /tmp/rip-example.XXXXXXXXXX) trap "rm \"$tempfile\"" EXIT pods=$(kubectl get pods | grep Running | grep -oe "app-[a-z0-9\-]\+") for pod in $pods do kubectl logs -f "$pod" >> "$tempfile" & done tail -f "$tempfile" However, that method consumes disk spaces.
Sometimes I want to create a new gem or modify existing gems to extend/fix them. However, I do not want to install tons of additional development tools on my host machine for that. Recently, I created a shell script which creates an instant development environment on Docker for that. #!/bin/sh -e exec docker run --rm -it \ --workdir=/work \ -v $(pwd):/work \ -v=$HOME/.gitconfig:/root/.gitconfig \ -v=$HOME/.ssh:/root/.ssh \ -v=$HOME/.
Active Job adapter interface I've created an Active Job adapter to run my background jobs on Google Cloud Run via Google Cloud Tasks. Although it is the first time for me to create an adapter for Active Job, this is working very well so far. https://github.com/esminc/activejob-google_cloud_tasks-http Creating an Active Job adapter itself is not so hard. You can see that by exploring the repository above. In fact, Active Job adapters are required to implement only two methods: enqueue and enqueue_at.