What New Bugs Live in the Cloud? (and How to Exterminate Them)

As more data and computation move from local to cloud environments,
datacenter distributed systems have become a dominant backbone for
many modern applications. However, the complexity of cloud-scale
hardware and software ecosystems has outpaced existing testing,
debugging, and verification tools.

I will describe three new classes of bugs in large-scale datacenter
distributed systems: (1) distributed concurrency bugs, caused by
non-deterministic timings of distributed events such as message
arrivals as well as multiple crashes and reboots; (2) limpware-induced
performance bugs, design bugs that surface in the presence of
"limping" hardware and cause cascades of performance failures; and (3)
scalability bugs, latent bugs that are scale dependent, typically only
surface in large-scale deployments (100+ nodes) but not necessarily in
small/medium-scale deployments.

I will present some of our work in understanding and combating these
three classes of bugs, including semantic-aware model checking (SAMC),
taxonomy of distributed concurrency bugs (TaxDC), path-based
speculative execution (PBSE), and scalability checks (SCk). If time
permits, I will also briefly discuss some other interesting findings
from our Cloud Bug Study (3000+ bugs) and Cloud Outage Study (500+
outages).
Haryadi Gunawi is a Neubauer Family Assistant Professor in the Department of Computer Science at the University of Chicago where he leads the UCARE research group (UChicago systems research on Availability, Reliability, and Efficiency). He received his Ph.D. in Computer Science from the University of Wisconsin, Madison in 2009. He was a postdoctoral fellow at the University of California, Berkeley from 2010 to 2012. His current research focuses on cloud computing reliability and new storage technology. He has won numerous awards including NSF CAREER award, NSF Computing Innovation Fellowship, Google Faculty Research Award, NetApp Faculty Fellowships, and Honorable Mention for the 2009 ACM Doctoral Dissertation Award.

His research focus is in improving dependability of storage and cloud computing systems in the context of (1) performance stability, wherein he is interested in building storage and distributed systems that are robust to "limping" hardware, (2) reliability, wherein he is interested in combating non-deterministic concurrency bugs in cloud-scale distributed systems, and (3) scalability, wherein he is interested in developing approaches to find latent scalability bugs that only appear in large-scale deployments.