AutoSpotting VS savings-estimator

There's a service that handles obtaining the cheapest spot instances to your specs by a former aws engineer https://github.com/LeanerCloud/AutoSpotting

Effectively, it starts up cheap spot instances (based on specified criteria) across a variety of instance types to replace whatever regular instance in an autoscaling group comes online and then spins down the regular instance.

EG: That m4a you wanted may be expensive... but nobody is using m4ad so it's 85% off and it meets the specified CPU/RAM requirements... auto spotting will spin it up instead.

Having used it on and off over the years it is sometimes eyebrow raising to see 4xl boxes running cheaper than the xl box they replaced :)

I've been heavily using ChatGPT on my autospotting.io software, where it 3-5x my productivity, releasing in 6 weeks more improvements than in the previous 6 months combined: https://github.com/LeanerCloud/AutoSpotting/discussions/489

Relevant: https://github.com/cloudutil/AutoSpotting

I've seen some third party services that automate migration to / replacement with spot instances, but haven't used them yet personally.

Going serverless, in many places, has been the most effective cost optimization for me.

I've also been maintaining a Golang library that essentially exposes the same data structure used under the hood by ec2instances.info as a Golang data structure, which is very convenient for embedding into other tools that can do lots of things with this raw data, like I do it in my AutoSpotting project.

I think autospotting can do this.

https://github.com/AutoSpotting/AutoSpotting is an interesting project that might help you with implementing this. It will automatically swap-out on-demand instances for spot and auto-restart as on-demand if spot capacity disappears.

we scale up to about 100 machines. We use spot instances EXTENSIVELY. And that configuration was tricky actually. Its been a couple of months now. Works pretty ok.

k3s is actually pretty simple to use now. the tricky part was to integrate with https://github.com/kubernetes/cloud-provider-aws and https://github.com/DirectXMan12/k8s-prometheus-adapter

The hardest part is to get it to work with spot instances. we use https://github.com/AutoSpotting/AutoSpotting to integrate with it.

- an OSS Spot Savings estimator GUI app using the Fyne.io toolkit for Go - https://github.com/LeanerCloud/savings-estimator

At https://leanercloud.com we realized that the main obstacle of cloud cost optimization is lack of skin in the game of individual contributors such as engineers when it comes to the cloud costs of their company.

In order to overcome this, we’re introducing SkinInTheGame, our incentive alignment program that pays back individual contributors who help us drive adoption of our tools in order to save their company money.

This consists of 50% of our AWS Marketplace revenue from that customer for the first 3 months after starting to use our cost optimization tools, so about 2% of the total generated savings over those 3 months (we charge up to 5% of savings and pay the AWS Marketplace fee of 20%).

The only requirement is to write us on Slack as soon as you sign up on the AWS Marketplace, so we know who you are and how to pay you (we’ll need the AWS account ID, company name and your Paypal email address).

You will be paid a lump sum via Paypal in the 4th month from signing up, as soon as we get paid by the AWS Marketplace.

For AutoSpotting you can conveniently estimate the savings and your corresponding income using our https://github.com/LeanerCloud/savings-estimator open source tool, which you can also use to quickly apply the required configuration to your AWS account.

Feel free to ask if you have any further questions.