{"id":355781,"date":"2017-01-19T15:26:06","date_gmt":"2017-01-19T23:26:06","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=355781"},"modified":"2022-01-18T06:14:52","modified_gmt":"2022-01-18T14:14:52","slug":"geo-distribution-actor-based-services","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/geo-distribution-actor-based-services\/","title":{"rendered":"Geo-Distribution of Actor-Based Services (Preliminary TechReport)"},"content":{"rendered":"

(This technical report is now redundant, see our conference publication<\/a>)<\/p>\n

Many service applications use actors as a programming model for the middle tier, to simplify synchronization, fault-tolerance, and scalability. However, efficient operation of such actors in multiple, geographically distant datacenters is challenging, due to the very high communication latency.<\/p>\n

We present Geo<\/em>, an open-source geo-distributed actor system that improves performance by caching actor states in one or more datacenters, yet guarantees the existence of a single latest version by virtue of a distributed cache coherence protocol.\u00a0Geo<\/em> supports both volatile and persistent actors, and supports updates with a choice of linearizable and eventual consistency. Our evaluation on several workloads shows substantial performance benefits, and confirms the advantage of supporting both replicated and single-instance coherence protocols as configuration choices. For example, replication can provide fast, always-available reads and updates globally, while batching of linearizable storage accesses at a single location can boost the throughput of an order processing workload by 7x.<\/p>\n","protected":false},"excerpt":{"rendered":"

(This technical report is now redundant, see our conference publication) Many service applications use actors as a programming model for the middle tier, to simplify synchronization, fault-tolerance, and scalability. However, efficient operation of such actors in multiple, geographically distant datacenters is challenging, due to the very high communication latency. We present Geo, an open-source geo-distributed 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