About Corey QuinnOver the course of my career, I’ve worn many different hats in the tech world: systems administrator, systems engineer, director of technical operations, and director of DevOps, to name a few. Today, I’m a cloud economist at The Duckbill Group, the author of the weekly Last Week in AWS newsletter, and the host of two podcasts: Screaming in the Cloud and, you guessed it, AWS Morning Brief, which you’re about to listen to.Links
CHAOSSEARCH.io
SQLite
TranscriptCorey Quinn: Welcome to AWS Morning Brief: Whiteboard Confessional. I’m Cloud Economist Corey Quinn. This weekly show exposes the semipolite lie that is whiteboard architecture diagrams. You see, a child can draw a whiteboard architecture, but the real world is a mess. We discuss the hilariously bad decisions that make it into shipping products, the unfortunate hacks the real world forces us to build, and that the best to call your staging environment is “theory”. Because invariably whatever you’ve built works in the theory, but not in production. Let’s get to it.On this show, I talk an awful lot about architectural patterns that are horrifying. Let’s instead talk for a moment about something that isn’t horrifying. CHAOSSEARCH. Architecturally, they do things right. They provide a log analytics solution that separates out your storage from your compute. The data lives inside of your S3 buckets, and you can access it using APIs you’ve come to know and tolerate, through a series of containers that live next to that S3 storage. Rather than replicating massive clusters that you have to care and feed for yourself, instead, you now get to focus on just storing data, treating it like you normally would other S3 data and not replicating it, storing it on expensive disks in triplicate, and fundamentally not having to deal with the pains of running other log analytics infrastructure. Check them out today at CHAOSSEARCH.io.Many things make fine databases that replicate data from one place to another, that takes various bits of data and puts them where they need to go. Other things do not make fine databases that do such things. Let’s talk about one of those today. For those who have never had the dubious pleasure of working with it, SQLite is a C library that implements a relational database engine. And it’s pretty awesome. It’s very clearly not designed to work in a client-server fashion, but rather to be embedded into existing programs for local use. In practice, that means that if you’re running SQLite, that’s S-Q-L-I-T-E, your database backend is going to be a flat-file or something very much like that, that lives locally. This is technology used all over the place, and mobile apps and embedded systems, in web apps for some very specific things. But that’s not quite the point. I once worked somewhere that decided to build a replicated environment that was active, active, active, across three distinct data centers. You would really hope that that statement was a non sequitur. It’s not. If you were to picture Hacker News coming to life as a person, and that person decided to design a replication model for a database from first principles, you would be pretty close to what I have seen. By taking a replicated model that runs on top of SQLite, you can get this to work, but the only way to handle that—because there’s no concept of client-server, as mentioned—so you have to kick all of the replication and state logic from the database layer, where it belongs up, into the application code itself, where it most assuredly does not belong. The downside of this—well, there are many downsides, but let’s start with a big one that this is not even slightly what SQLite was designed to do at all. However, take a startup that decides if there’s one core competency they have, it’s knowing better than everyone else; this is that story. Now, I am obviously not a developer, and I’m certainly not a database administrator. I was an ops person, which means that a lot of the joy of various