Request for stack 2024

Every few years it’s good to ask, “What is the best stack to build new software in?”. Lately I’ve been thinking about the resurgence of vertical scaling over horizontal scaling. If you app is only going to serve millions of requests per day, there is no reason not to vertically scale it. The days of 2GB ram, 1 vcpu servers are long gone. Now you can get terabytes of ram and thousands of virtual cpus.

My prediction is that going forward AI will consume 99% of compute spend  with actual code consuming only 1% of the total compute. Those things in mind lets look at the stack. 

Application Server 

  • Rails if it has a UI
  • Java if it does not


  • Redis


  • Postgres

Analytics Database

  • Postgres

Each ‘cell’, to use Amazon terminology, consists of one application server, a cache and a database. Just three servers. Then for reliability setup another ‘cell’ in a different availability zone. In total you have 6 servers. 

For someone who has run projects with 100s of cloud ‘servers’ 6 seems rather few. But with today’s cloud we can have 1000 vcpus across 100 ‘servers’ or across 6 ‘servers’. And the performance of the application built with only 6 will be better. 

Today’s default micro-service architecture is useful for improving deployment cadence in large teams. But it no longer provides scaling advantages compared to old school vertical strategies. If your project only includes 40~ servers with 2 cpu each, why not just use 3 servers? 80 vcpu is 80 vcpu, whether you draw 40 boxes or 3 boxes around them. 

Unless you are using 1000+ vcpu you might want to consider just using one box for your entire application. 

A clear sign you are overdoing micro services 

Fine grained services

Microservices have been the thing for over 15 years. They are great in large companies with CI/CD environments. But as your situation drifts farther away from the ideal microservice use case traps abound. 

Building a new service for one endpoint 

If you find yourself having a conversation where you need to create a new endpoint somewhere, but adding it to any of your existing services would break the concept of that microservice. Turning it instantly into a ball of mud with no clear purpose. You have fallen into this trap. microservice does not mean each service has only one HTTP endpoint. That use case is better served with Cloud functions like AWS lambda. 

The problem here is that we have gone too far in splitting up the monolith. Splitting a monolith with 100 HTTP endpoints into a dozen or so services with eight endpoints each is great. Splitting up a monolith with 100 endpoints into 100 services is counter productive. Instead of having an actual purpose the single endpoint microservice becomes the xyz endpoint microservice. 

Endpoints are things that microservices empower. An endpoint in of itself should never justify the creation of a microservice. 

Up in the air

We are in a phase where planning becomes quite difficult. ChatGPT has started a capitalistic AI war. Microsoft swept in to shepherd commercialization. Google is on the back foot for now. Amazon will launch something I have no doubt. ChatGPT style tech would make Alexa viable by solving the fractal conversation problem. 

The players are moving, immense amounts of capital has been unleashed. But for us on the outside it’s a difficult time. You can’t really plan for the future. Because the technology is advancing rapidly and is already transforming jobs in various industries.

GPT-4 has been in the news, but Midjourney has quietly advanced to the point where it is transforming job tasks in the graphic design industry. I read a complaint by a graphic designer this weekend describing how his job has become more prompt engineering than graphic design. Instead of needing to draw things he and his peers can now use AI image generation and then clean it up in photoshop. 

Video created by demonflyingfox using MidJourney V4.

In 2022 I ordered physical versions of two AI generated images that I thought were incredible examples of what AI could do. In 2023 these images are somewhat quaint. AI image generation can do so much more now. 

We don’t really know where things are going. How do you prepare exactly when the potential paths are so divergent? 

Some people claim AI will replace programmers. Others say we will never not need people to dig deep into the technical details. Personally, I lean towards the second. If AI coding hasn’t peaked yet we will likely see a 1000x increase in the amount of code being written. ChatGPT is quite good at explaining things but will it be useful at explaining interactions between multiple programs it has written? We can’t know at this point. 

Image of a line going exponential. Credit to Luke Muehlhauser who created and watermarked this image.

We are in the straight line at the far right now. We’ve discovered something about meaning in these large language models. A mapping between language and image, and mappings between language and language. It’s not AGI, but much like Deep Blue its obviously eclipsed human capabilities in some way. 

Neal Stephenson’s ‘The Diamond Age’ is a book I was intrigued by in my younger years. In it a girl is given a AI powered book which acts as her tutor from a very young age.  Much like that fictional book ChatGPT likely will become every child’s tutor going forward. Much like the iPhone, you won’t be able to buy a better one. Children have already used ChatGPT to make homework and writing assignments obsolete. The education system likely will not survive this advancement. 

The sum total of human knowledge has been put into this machine. Everyone who ever wrote anything is part of it. Buckle up. Don’t panic. Hold on. Let’s see what happens next.

Self-hosted is not cheaper or better. Your options are pay Amazon insane markups or deal with a Platform as a Service built by the lowest bidder.

We often see posts on hacker news about how Amazon charges an insane markup for hosting or data transfer, or anything. Then someone will post a comparison where they price out an equivalent amount of hardware and show that it would cost 1/5th or 1/10th the cost. They then assume, obviously, hiring an IT department that can run this hardware is an achievable goal. 

Sorry, no it’s not achievable. Most companies cannot build a decent IT team that could run their own servers. They don’t have the ability to organize or hire the IT people needed. Not to mention they would never be willing to pay the salary costs. Quite simply, most businesses that try to run their own hardware will have a lower quality internal platform than if they just paid Microsoft. Whats the point of having faster hardware if your software stack is stuck in 2005 and managed by college drop outs?

Most companies are not overflowing with smart programmers who want to run bare metal hardware. Those people are moved to higher paying jobs programming the actual products of the company. 

Collected Sledgeworx

The collection is out now!

I’ve finally released my collection Collected Sledgeworx on amazon.

I started blogging to share my thoughts and vent frustrations. My first blog was about futurism and politics, my second on fitness, my third was I ended up being much better at a writing about software than anything else.

In this book I have collected many of the posts on the blog from its inception until the second half of 2021. These writings can be found on the blog in similar form. But you will find that the works in this book have been edited and supplemented in small ways.

Thanks for being a reader as we continue along to 2030!