  We consider the problem of making apps fault-tolerant through replication,
when apps operate at the microsecond scale, as in finance, embedded computing,
and microservices apps. These apps need a replication scheme that also operates
at the microsecond scale, otherwise replication becomes a burden. We propose
Mu, a system that takes less than 1.3 microseconds to replicate a (small)
request in memory, and less than a millisecond to fail-over the system - this
cuts the replication and fail-over latencies of the prior systems by at least
61% and 90%.
  Mu implements bona fide state machine replication/consensus (SMR) with strong
consistency for a generic app, but it really shines on microsecond apps, where
even the smallest overhead is significant. To provide this performance, Mu
introduces a new SMR protocol that carefully leverages RDMA. Roughly, in Mu a
leader replicates a request by simply writing it directly to the log of other
replicas using RDMA, without any additional communication. Doing so, however,
introduces the challenge of handling concurrent leaders, changing leaders,
garbage collecting the logs, and more - challenges that we address in this
paper through a judicious combination of RDMA permissions and distributed
algorithmic design.
  We implemented Mu and used it to replicate several systems: a financial
exchange app called Liquibook, Redis, Memcached, and HERD. Our evaluation shows
that Mu incurs a small replication latency, in some cases being the only viable
replication system that incurs an acceptable overhead.

Distributed, Parallel, and Cluster Computing