Millions of web servers and a multitude of applications are producing ever-increasing amounts of data in real time at Meta. Regardless of how data is generated and how it is processed, there is a need for infrastructure that can accommodate the transport of arbitrarily large data streams from their generation location to their processing location with low latency. This paper presents Scribe, a multi-tenant message queue service that natively supports the requirements of Meta's data-intensive applications, ingesting > 15 TB/s and serving > 110 TB/s to its consumers. Scribe relies on a multi-hop write path and opportunistic data placement to maximise write availability, whereas its read path adapts replica placement and representation based on the incoming workload as a means to minimise resource consumption for both Scribe and its downstreams. The wide range of Scribe use cases can pick from a range of offered guarantees, based on the trade-offs favourable for each one.

In this paper, we evaluate the emerging Transactional Memory (TM) area by developing a set of Java transactional memory workloads and studying their performance under a Java Software Transactional Memory (STM) system and comparing them to their lock based counterparts. We provide a detailed performance and memory consumption analysis of the overheads of software transactional memory and transactional workloads within a production quality open source Java Runtime system. Additionally, we detail the impact of the various performance optimizations in both workloads and the underlying runtime system to improving both single thread performance and scalability.