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Comment by josefresco | Hacker News Reader

I believe Google (G Suite) only claims 99.9% - sounds small, is actually a huge difference. They typically achieve a better % but that is all they "guarantee".

"Service Credit" means: (a) 10% of the total invoice charges for the affected month if the Monthly Uptime Percentage for any calendar month is between 99.0% and 99.9%; or (b) 25% of the total invoice charges for the affected month if the Monthly Uptime Percentage for any calendar month is between 99.0% and 95.0 %; or (c) 50% of the total invoice charges for the affected month if the Monthly Uptime Percentage for any calendar month is less than 95.0%.

Source: https://gsuite.google.com/terms/partner_sla.html

Edit: It appears Microsoft/Office 365 offers the same SLA / 99.9%

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For reference: over the course of a year, if you have an uptime of 99%, that means you are down for 3 days 15 hours per year. If you have 99.9% uptime, that means the downtime is roughly 9 hours per year. If you have 99.99% up, then the down is ~ 53 minutes per year. 99.999% then gives you ~5 minutes of down per year. 99.9999% will then give you ~31 seconds of downtime per year.

One thing to keep in mind is that for each 9 of uptime you have, add about two Zeros to the budget and increase the timeline by one time units up and then double it. So if 99% costs you $100 and a day of timeline on the project, then 99.9% will cost you $10,000 and two weeks of timeline, and 99.99% will cost you $1,000,000 and 4 months of timeline, and 99.999% will cost you $100,000,000 and 8 years of timeline, etc.

> for each 9 of uptime you have, add about two Zeros to the budget

It's more like going from the stone age to the bronze age. You need expertise and architecture suitable for achieving high availability, these are your budget increases, they are not linear at all. But the infrastructure itself doesn't necessarily get more expensive, on the contrary, new architecture could allow you to use the cheapest stuff available on the market.

Most likely u need an oracle to forecast all kinds of error in real world.

Much of Googles initial competitive advantage was a sharded architecture and understanding how to run a reliable service across unreliable nodes - mean time to detection and repair are more important than reliability of any one component, though better components can allow you to scale further - there's interesting multiplicative effects.

This is interesting! Is this a rule of thumb or common sense in the infrastructure world or is it something which there are studies? If there are studies do you have some links I could read further on?

What is timeline in this context?

Process & systems development.

Thanks.

Source?

So even if it's down for the whole month I still have to pay (and probably can't even get out of it; even without some sort of longer contract the lock in is strong). Those are some big corporation terms all right.

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