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As someone working on a mail service of my own, this is heartening to see. Even Google messes up sometimes.
Yup. And that's by design. Stability is asymptotic and increasingly expensive to reach toward 100%. There's a very intentional "this is good enough" point.
Earlier quoted context omitted.
Yup. And that's by design. Stability is asymptotic and increasingly expensive to reach toward 100%. There's a very intentional "this is good enough" point.
What are the main factors that could lead to such a situation?
Earlier quoted context omitted.
Yup. And that's by design. Stability is asymptotic and increasingly expensive to reach toward 100%. There's a very intentional "this is good enough" point.
What are the main factors that could lead to such a situation?
"The error budget stems from the observation that 100% is the wrong reliability target for basically everything
(pacemakers and anti-lock brakes being notable exceptions).
In general, for any software service or system, 100% is not
the right reliability target because no user can tell the
difference between a system being 100% available and 99.999% available.
There are many other systems in the path between
user and service (their laptop, their home WiFi, their ISP,
the power grid…) and those systems collectively are far less
than 99.999% available. Thus, the marginal difference
between 99.999% and 100% gets lost in the noise of other
unavailability, and the user receives no benefit from the
enormous effort required to add that last 0.001% of
availability.
If 100% is the wrong reliability target for a system, what,
then, is the right reliability target for the system? This
actually isn’t a technical question at all—it’s a product question.."
Earlier quoted context omitted.
Yup. And that's by design. Stability is asymptotic and increasingly expensive to reach toward 100%. There's a very intentional "this is good enough" point.
What are the main factors that could lead to such a situation?
In the aerospace industry, to get that last percent of a percent, 2 completely independent implementations of everything are used. Then to get another decimal, you add 2 more implementations and a consensus algorithm. Then of course you add static/unit/api/integration/stress/fuzz test suits for each implementation. Then test the tests. Then have a human run each test as the "second implementation" of the CI system. And so on, and so on. Each new decimal "9" cost multiple time more in human resource alone.
Then take into account the "productivity loss" of all those process and you need yet more poeple to progress as fast. Adding more people to a project has a diminishing return. After a while you can spend the entire GDP of the world and you wont be able to add another availability decimal point.
Semi-related, but can anyone suggest good open source email client? I'm working on several computers with macos/linux and Gmail isn't slow only on my deep learning rig, so I'm looking for something to replace it.
Semi-related, but can anyone suggest good open source email client? I'm working on several computers with macos/linux and Gmail isn't slow only on my deep learning rig, so I'm looking for something to replace it.
The calendar interfaces with your Google calendar too (with the Lightning and Provider for Google Calendar add-ons).
Available for Mac, Windows and Linux.