Despite being a strong advocate for AWS, this is where I will say Google completely outshines Amazon.<p>Google's approach to pricing is, "do it as efficiently and quickly as possible, and we'll make sure that's the cheapest option".<p>AWS's approach is more, "help us do capacity planning and we'll let you get a price break for it.".<p>Google applies bulk discounts after the fact, AWS makes you ask for them ahead of time.
The notion that the break even point is 70% is ignoring some really important stuff.<p>If you reserve workload x on hardware y for n years, you're effectively strapping yourself into a sure-to-be-obsolete and more expensive platform which you'll have to then move off of at an arbitrary point n years in the future.<p>If you don't move, you wind up paying a premium to be stuck with the obsolete / more expensive platform just to avoid the cost of migration.<p>RIs are a lock in.
My experience with AWS reserved instances has not been very good previously.<p>1. Once you buy a reserved instance, you're locked in to that type and price for the duration, even though newer types at lower prices may get introduced (as they almost definitely would over 1-3 yrs).<p>2. If you're from outside the US, you might not be able to resell your reserved instance. So you're stuck with an old instance type at an inflated cost.<p>In contrast, Google Cloud just gives you a price equivalent to a reserved instance price (or better), based on hours of usage, without asking for an upfront commitment.
One of the major issues we've seen with our customers is that many of them (especially startups and SMBs/SMEs) don't have the ability to dedicate a team to just managing their RI capacity. We've also seen enterprise customers optimizing up to 70% of their EC2 usage, but many of them have trouble ensuring a level of utilization due to rapidly changing infrastructure.
I'd definitely argue that GCP has a better model for some use cases as it requires less active effort for optimizing billing, however if you manage your RIs on AWS effectively you can often get a better price. Looks like Azure has also gone down the same route as AWS, which is quite an interesting move on their part.<p>Disclosure: I head engineering/devOps at Engineer.ai - one of our products Cloudops.ai allows our customers to save up to 15% of their AWS bill without making RI purchases, as well as get discounted prices and additional flexibility (custom lock-in periods) for RIs they do wish to purchase. Feel free to reach out for information - my email address is in my about section.
My experience from Sumo Logic is to take full advantage of RIs you need to do capacity planning and that takes some effort. Still that's way over 30% of savings which are needed if you run at scale.<p>Would recommend using CloudHealth or other tool vs. using custom ETL. I tried do it myself on my tools, but got worse results than using dedicated tool.<p>However, dedicated tool need input from development. Sometimes it's worth to buy non-convertible RIs for bigger instance. Sometimes convertible RIs are easier. I just found that convertible RIs with some upfront are incredible tricky to calculate amortisation.
> To automate this, we built an ETL process in SQL and Python that detects when we fall outside this band and automatically prepares a purchase for us to approve.<p>@Stripe: Will this (or parts of it) be open sourced?
Similar idea to rolling your own, my company uses Cloudability for AWS purchase planning. It saved a bunch of money as far as I remember.<p><a href="https://www.cloudability.com/" rel="nofollow">https://www.cloudability.com/</a>
I thought that payment processors are using their own hardware. How is AWS protecting their own customers' privacy? - can uncle Bob insert his fancy flash drive, copy my data, and sell it? Before you say it is encrypted - where does the encryption happen and doesn't AWS employees have access to the keys too?