Rethinking Distributed Systems for the Datacenter

Today's most popular applications are deployed as massive-scale
distributed systems in the datacenter. Keeping data consistent and
available despite server failures and concurrent updates is a
formidable challenge. Two well-known abstractions, strongly consistent
replication and serializable transactions, can free developers from
these challenges by transparently masking failures and treating
complex updates as atomic units. Yet the conventional wisdom is that
these techniques are too expensive to deploy in high-performance
systems.

I will demonstrate a new approach to designing distributed systems
that allows strongly consistent distributed systems to be built
with little to no performance cost. Taking advantage of the properties
and capabilities of the datacenter environment, we can co-design
distributed protocols and the network layer. Specifically, I will
describe two systems for state machine replication, Speculative Paxos
and Network-Ordered Paxos, and one for distributed transaction
processing, Eris, built using this approach. They are able to achieve
5-17x performance improvements over conventional designs. Moreover,
they achieve performance within 2% of their weakly consistent
alternatives, demonstrating that strong consistency and high
performance are not incompatible.
Dan Ports is Research Assistant Professor in Computer Science
and Engineering at the University of Washington, where he
leads the distributed systems research group. His group's research
focuses on building practical distributed systems with strong
theoretical underpinnings. Prior to joining the faculty at UW in 2015, Dan
received the Ph.D. from MIT (2012), where he was advised by Barbara
Liskov, and completed a postdoc at UW CSE. His research has been
recognized with best paper awards at NSDI and OSDI.