3 ms·
> they were down for 7.5% of the time I needed them, or had business hours uptime of 92.5% You can obviously compute this for a particular customer, but being
by swiftcoder 10d ago
> they were down for 7.5% of the time I needed them, or had business hours uptime of 92.5%
You can obviously compute this for a particular customer, but being a global service, it's pretty much guaranteed that someone somewhere experienced the worse of those numbers
- names_are_hard 10d agoYou can compute them for the average. In other words, the total customer impact is the number of business-hours of downtime across all customers divided by the total number of business hours of all customers. This is important because it's quite possible that the downtime is biased toward the times they have the most active users.
- Anon1096 10d agoBig systems worth their salt already do this as weighted uptime, considering request successes / total requests rather than wall clock uptime as internal SLOs. But these numbers aren't really ever published because it gives away information about your customer base. https://cloud.google.com/blog/products/gcp/available-or-not-that-is-the-question-cre-life-lessons?hl=en https://cloud.google.com/blog/products/gcp/available-or-not-...
- lanstin 10d ago"Failed customer interactions" - if you have a way to actually see requests before they hit your datacenter, e.g. some async third party client libraries.
- swiftcoder 9d agoOn this topic, as a service operator, it's really nice when you also own your SDKs, and have client-side telemetry about failed requests. Gives you a much clearer picture of end-to-end reliability (at least for the subset of customers who opt-in to telemetry)