R2P2: Making RPCs first-class datacenter citizens

Remote Procedure Calls are widely used to connect datacenter applications with strict tail-latency service level objectives in the scale of µs. Existing solutions utilize streaming or datagram-based transport protocols for RPCs that impose overheads and limit the design flexibility. Our work exposes the RPC abstraction to the endpoints and the network, making RPCs first-class datacenter citizens and allowing for in-network RPC scheduling. We propose R2P2, a UDP-based transport protocol specifically designed for RPCs inside a datacenter. R2P2 exposes pairs of requests and responses and allows efficient and scalable RPC routing by separating the RPC target selection from request and reply streaming. Leveraging R2P2, we implement a novel join-bounded-shortest-queue (JBSQ) RPC load balancing policy, which lowers tail latency by centralizing pending RPCs in the router and ensures that requests are only routed to servers with a bounded number of outstanding requests. The R2P2 router logic can be implemented either in a software middlebox or within a P4 switch ASIC pipeline. Our evaluation, using a range of microbenchmarks, shows that the protocol is suitable for µs-scale RPCs and that its tail latency outperforms both random selection and classic HTTP reverse proxies. The P4-based implementation of R2P2 on a Tofino ASIC adds less than 1µs of latency whereas the software middlebox implementation adds 5µs latency and requires only two CPU cores to route RPCs at 10 Gbps linerate. R2P2 improves the tail latency of web index searching on a cluster of 16 workers operating at 50% of capacity by 5.7× over NGINX. R2P2 improves the throughput of the Redis key-value store on a 4-node cluster with master/slave replication for a tail-latency service-level objective of 200µs by more than 4.8× vs. vanilla Redis.


Presented at:
USENIX Annual Technical Conference 2019,, Renton, WA, USA, July 10-12, 2019
Year:
2019
ISBN:
978-1-939133-03-8
Laboratories:




 Record created 2019-07-11, last modified 2019-08-12

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