10,000 users tap "Log in" at 9:00:00. What breaks first?
A) CPU: password hashing
B) DB connections
C) SMS/email provider
D) Rate limiter
Reply with a letter and why.
#backend#systemdesign
Monday, 9:00. Login p99 is 14.2s.
Pods at 100% CPU. New pods need 3 min.
Marketing just emailed 2M users.
The load test? One user, 10,000 times.
Six messages. Three minutes. All fixable on Friday.
Which one would you have caught?
#sre#incidentresponse#devops
50% CPU: a login waits about 2× its work time.
90% CPU: 10×.
99% CPU: 100×.
Queues don't get slow slowly. They fall off a cliff.
What CPU target do you scale at?
#sre#performance#backend
"Login is slow, let's lower the bcrypt cost."
That makes it faster for attackers too. The fix is more hashing capacity, not weaker hashes.
Which would you pick: more cores, or a separate hashing pool?
#security#appsec#backend