Hiring: remote redis-ops engineer (full-time, long-term)
Some background first. Our setup is redis-ops plus three downstream services, seven figures of daily requests, peaking around nine in the evening.
One last trap: in container environments remember to adjust the memory-related parameters in step. Otherwise the host limit and the process expectation disagree, and the symptom is intermittent, unreproducible failure.
// Minimal reproduction: you must use a real long-tail distribution here.
// Uniform load-test traffic will never trigger this.
func (s *Server) handle(ctx context.Context) error {
conn, err := s.pool.Acquire(ctx)
if err != nil {
return fmt.Errorf("acquire: %w", err)
}
defer conn.Release()
return s.do(ctx, conn)
}The first thing was to collapse the variables. We were changing config and upgrading the version at the same time, and afterwards nobody could say which change caused what. We rolled back to moving one variable at a time, re-ran three times, and only then did the curve settle. Tedious, but not skippable.
On trade-offs, my view is this: if nobody on the team owns this area long-term, do not introduce a second mechanism. With two coexistence you first have to work out which one is even in play when things break, and that costs far more than the performance you saved.