Introduction While embarking on building any new server application, one of the key requirement is whether it needs durable, persistent storage of data (and in most cases, it does). This is followed by evaluating suitable data store. Likely evaluation criteria is Application’s Requirement (Tolerance for eventual consistency, High Availability etc.), Team’s familiarity, Costs, Tech. support availability and so on. In case of choices in relational databases, typical go to options are MySQL, PostgreSQL or even proprietary databases like Oracle , SQL Server. Seldom one considers SQLite for this purpose.
This post is proudly sponsored by Code & Co. Disclaimer: I’m not affiliated to fly.io at all, this is just a personal account of my experience with it. Fly.io 101 Even though fly is pretty much “Phoenix First” these days (they hired Chris McCord for a reason!), it’s still a very decent way to deploy a Reactive Rails app, as Matt Yorkley has demonstrated here. Let’s go through a quick list of preliminary information before we get started. Docker or Buildpacks? A lot of Rails developers considering Fly as a Platform as a Service these days are accustomed to the Heroku way of deploying apps via git push and Cloud Native Buildpacks that manage the deployment process automatically. While Fly defaults to a Dockerfile builder - and indeed, the Rails setup wizard will generate one for you, as we shall see - you can also use a buildpack builder by specifying a builder and buildpacks in the fly.toml configuration: [build] builder = "heroku/buildpacks:18" buildpacks = ["...", "..."] Also refer to this blog post to select the correct builder (at the moment of writing this would be heroku/buildpacks:18) Free Allowances While Fly has a quite generous stack of free allowances which will let you start and maintain a reasonably sized side-project for free, I would like to specifically point out their free postgres offering, which largely builds on the allowed 3GB of volume storage. Here are a few examples for how to configure it. Bear in mind though that the free compute allowance is summed together for all apps - if you exceed that, you might not be able to keep your whole Rails project free. Getting Started The first thing you’ll want to do, is to install the flyctl CLI (see here) Next, quite obviously, you need to create a Fly account. Run flyctl auth signup, which will in turn open the browser for you. Note that you will have to provide credit card information upfront, because ”here’s what happens if you give people freemium full access to a hosting platform: lots and lots of fr
Introduction Postgres queue tech is a thing of beauty, but far from mainstream. Its relative obscurity is partially attributable to the cargo cult of “scale”. The scalability cult has decreed that there are several queue technologies with greater “scalability” than Postgres, and for that reason alone, Postgres isn’t suitably scalable for anyone’s queuing needs. The cult of scalability would rather we build applications that scale beyond our wildest dreams than applications that meet concrete customer and business needs. Postgres’ operational simplicity be damned; scale first, operate later.
How I switched hosting my Go-based side projects from Amazon EC2 to Fly.io, significantly simplified deployment, and saved a bit of cash while I was at it.
At Terrateam, we are big fans of Fly.io. The service is hosted there and it’s served us well. Just deploy your TOML file, get your infrastructure, do something else with the rest of your day. One of the interesting sides of Fly is that they invest heavily in server-side SQLite. They’ve written a number of blog posts on how they enable server-side SQLite: I’m All-In on Server-Side SQLite - Ben Johnson, the author of BoltDB, joins Fly to work on Litestream, a SQLite replication solution. Introducing LiteFS - The introduction of LiteFS, which is a FUSE file system designed to replicate SQLite transactions over the network. LiteFS Cloud: Distributed SQLite with Managed Backups - Introducing backups and restores for LiteFS.
Introduction Postgres queue tech is a thing of beauty, but far from mainstream. Its relative obscurity is partially attributable to the cargo cult of “scale”. The scalability cult has decreed that there are several queue technologies with greater “scalability” than Postgres, and for that reason alone, Postgres isn’t suitably scalable for anyone’s queuing needs. The cult of scalability would rather we build applications that scale beyond our wildest dreams than applications that meet concrete customer and business needs. Postgres’ operational simplicity be damned; scale first, operate later.
