LazyLog: A New Shared Log Abstraction for Low-Latency Applications
Ram Alagappan

Can we make shared logs faster without sacrificing consistency? Introducing LazyLog — a new log abstraction that rethinks how streaming systems handle ordering to achieve dramatically lower write latency.

Traditional shared logs enforce a strict, global order at write time, which guarantees consistency but slows ingestion. LazyLog flips this model: it defers the costly ordering step until data is read. The result? Faster writes, lower latency, and the same strong guarantees when order actually matters.

In this talk, you’ll learn:

  • Why traditional log-based systems create latency bottlenecks
  • How LazyLog delays ordering to accelerate data ingestion
  • Real-world examples of two systems built with the LazyLog abstraction
  • How LazyLog maintains consistency while boosting throughput

Developed at the University of Illinois, LazyLog was presented at SOSP, the premier conference for systems research — where it won the Best Paper Award.

If you’re building low-latency data pipelines or high-throughput distributed systems, this talk reveals a breakthrough approach that could reshape your streaming architecture.

Ram Alagappan
Assistant Professor, UIUC

Ram Alagappan is an Assistant Professor at UIUC, where he co-leads the Distributed And Storage Systems Lab (DASSL). His research focuses on storage systems, disaggregated memory, and distributed systems. His work has appeared at OSDI, SOSP, FAST, and EuroSys. He has won several awards, including an NSF CAREER award, teaching recognitions at UIUC, and best-paper awards at SOSP '24, FAST '20, FAST '18, and FAST '17. His open-source tools have had a practical impact, exposing more than 80 severe crash vulnerabilities across 20 widely used systems. Ideas from his work have been adopted by a financial database startup.

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