I'm sure that you guys have done a lot of analysis but flipping to steel is the very last thing I would consider before reviewing the tech in the world today in relationship to TCOS as things move very fast.
You could frame infrastructure cost savings in many different ways though. The most obvious solution may seem to be the spend to move from the cloud to in house bare metal but I feel like you'll have a lot of costs that you haven't accounted for in maintenance, operational staff spend, cost in lost productivity as you make a bunch of mistakes.
Your core competency is code, not infrastructure, so striking out to build all of these new capabilities in your team and organization will come at a cost that you can not predict. Looking at total cost of ownership of cloud vs steel isn't as simple as comparing the hosting costs, hardware and facilities.
You could reduce your operating costs by looking at your architecture and technology first. Where are the bottlenecks in your application? Can you rewrite them or change them to reduce your TCOS? I think you should start with the small easy wins first. If you can tolerate servers disappearing you can cut your operating costs by 1/8th by using preemptible servers in google cloud platform for instance. If you optimize your most expensive services I'm sure you can cut hunks of your infrastructure in half. You'll have made some mistakes a long the way that contribute to your TCOS - why not look at those before moving to steel and see what cost savings vs investment you can get there?
Ruby is pretty slow but that's not my area of expertise - I wouldn't build server software on dynamic languages for a few reasons and performance is one of them but that's neither here nor there as you can address some of these issues in your deployment with modern tech I'm sure. Aren't there ways to compile the ruby and run it on the JVM for optimizations sake?
Otherwise do like facebook and just rewrite the slowest portions in scala or go or something static.
Try these angles first - you're a software company so you should be able to solve these problems by getting your smartest people to do a spike and figure out spend vs savings for optimizations.
You could frame infrastructure cost savings in many different ways though. The most obvious solution may seem to be the spend to move from the cloud to in house bare metal but I feel like you'll have a lot of costs that you haven't accounted for in maintenance, operational staff spend, cost in lost productivity as you make a bunch of mistakes.
Your core competency is code, not infrastructure, so striking out to build all of these new capabilities in your team and organization will come at a cost that you can not predict. Looking at total cost of ownership of cloud vs steel isn't as simple as comparing the hosting costs, hardware and facilities.
You could reduce your operating costs by looking at your architecture and technology first. Where are the bottlenecks in your application? Can you rewrite them or change them to reduce your TCOS? I think you should start with the small easy wins first. If you can tolerate servers disappearing you can cut your operating costs by 1/8th by using preemptible servers in google cloud platform for instance. If you optimize your most expensive services I'm sure you can cut hunks of your infrastructure in half. You'll have made some mistakes a long the way that contribute to your TCOS - why not look at those before moving to steel and see what cost savings vs investment you can get there?
Ruby is pretty slow but that's not my area of expertise - I wouldn't build server software on dynamic languages for a few reasons and performance is one of them but that's neither here nor there as you can address some of these issues in your deployment with modern tech I'm sure. Aren't there ways to compile the ruby and run it on the JVM for optimizations sake?
Otherwise do like facebook and just rewrite the slowest portions in scala or go or something static.
Try these angles first - you're a software company so you should be able to solve these problems by getting your smartest people to do a spike and figure out spend vs savings for optimizations.