You trade a very bubbly flux of outages across countless bespoke deployments, hosts, and topologies for something with failures that are more rare but also more widespread when they occur.
Personally, I think what you’re noticing is that outages and failures are much more high profile than they used to be because it’s bigger news when these big bubbles burst than it was in that noisier flux where small outages were occurring all the time.
After some internal discussions, the accountants apologized.
Google isn’t exactly a shining star.
Here are some Github, Inc. (AS36459) IP addresses for github.com
140.82.112.3
140.82.112.4
140.82.113.3
140.82.113.4
140.82.114.3
140.82.114.4
140.82.121.3
140.82.121.4
192.30.255.112
192.30.255.113These github.com addresses I listed are static for years at a time. As such, there is nothing to "update".
Resilient code is easy to read/grasp code. It should pass a 3 am test too.
Azure has been having capacity problems all year and some new instance types aren't available to customers or you need special usage requests approved
I’ve noticed a number of changes over the past couple of years to make it easier to manage mixed pools of compute resources - both spot and on-demand - a good way for AWS to spread load across different instance classes.
Or build your own: https://github.com/hrbrmstr/pewpew :)
You might visualize a small slice of DDoS attacks and similar routine automatically detectable botnet stuff, but nothing actually serious or interesting.