jnewland
> 1. While Ruby Central correctly removed access to shared credentials through its enterprise password manager prior to the incident, our staff did not consider the possibility that this credential may have been copied or exfiltrated to other password managers outside of Ruby Central’s visibility or control.
> 2. Ruby Central failed to rotate the AWS root account credentials (password and MFA) after the departure of personnel with access to the shared vault.
February 28th DDoS Incident Report
> there is a percentage of users that will not read the doc and just deploy it
I wonder what this percentage is? I'd wager that it is higher than you might have anticipated, especially given the other comments on this thread.
As an engineer on a team ultimately responsible for the availability of a production service, it's my responsibility to ensure that the percentage of engineers that know the latency side effects of any Redis calls they make is near 100%. In the presence of such variable latency, any means of making that variability more obvious to all users of Redis would be a positive step towards happy users and operators.
I'm confident many other users of Redis are using O(N) operations in production against small datasets without knowledge of how much latency will be introduced by those operations when that dataset grows. This is exactly the kind of situation that makes me immediately skeptical when I find Redis in a emergent system design.
I'm considering what initially felt like a draconian means of remediation: using rename-command to rename all O(N) commands to BIG_O_N_$COMMAND to ensure everyone using them knows the possible impact and to allow for easy detection during code review and/or Redis latency spikes.
The more I think about it this approach, the more I feel that this should be the default mode of operation for Redis in production. SREs around the world would collectively save decades of time if the every engineer writing Redis queries to knew this fact by heart:
> Redis is very fast as long as you use O(1) and O(log_N) commands. You are free to use O(N) commands but be aware that it’s not the case we optimized for, be prepared for latency spikes.
Large Scale DDoS Attack on GitHub.com
First off, if you use a DNS provider that has support for a ALIAS records or something similar, pointing your apex domain to <username>.github.io will ensure your GitHub Pages site is served by our CDN without these redirects.
I wish we could provide better service for folks without a DNS provider that supports ALIAS domains in the face of the constant barrage of DDoS attacks we've seen against the IPs we've advertised for GitHub Pages over the years. We made the decision to keep DDoS mitigation enabled for apex domains after seeing GitHub Pages attacked and going down a handful of times in the same week. It's a bummer that this decision negatively impacts performance, but it does certainly improve the overall availability of the service.
FWIW, we considered pulling support for GitHub Pages on apex domains about a year ago because we knew it'd be slower than subdomains and would require DNS configuration that would be challenging and frustrating for a large number of our users. However, we ended up deciding not to go that route because of the number of existing users on apex domains.
2. Was 10 seconds with a 10 second timeout (way to low to run `xm list` in a loaded situation). It's now 90 seconds with a 90 second timeout.
Profile the memory usage of any Ruby library by monkey-patching 'require'
Deployment is just a part of dev/ops cooperation, not the whole thing
Having additional Passenger processes available even when CPU bound will allow for greater throughput (if at a less-than-ideal speed) than having requests back up on the queue, however - especially if those requests spend a good amount of time waiting on DB, memcached, or other external API calls.
s/working directly with/delaying/
http://support.github.com/discussions/site/721-network-feed-...