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High-Availability at Massive Scale: Building Google's Data Infrastructure for Ads

机译:大规模规模的高可用性:为广告构建谷歌的数据基础架构

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Google's Ads Data Infrastructure systems run the multi-billion dollar ads business at Google. High availability and strong consistency are critical for these systems. While most distributed systems handle machine-level failures well, handling datacenter-level failures is less common. In our experience, handling datacenter-level failures is critical for running true high availability systems. Most of our systems (e.g. Photon, F1, Mesa) now support multi-homing as a fundamental design property. Multi-homed systems run live in multiple datacenters all the time, adaptively moving load between datacenters, with the ability to handle outages of any scale completely transparently. This paper focuses primarily on stream processing systems, and describes our general approaches for building high availability multi-homed systems, discusses common challenges and solutions, and shares what we have learned in building and running these large-scale systems for over ten years.
机译:谷歌的广告数据基础架构系统在Google上运行数十亿美元的广告业务。高可用性和强的一致性对这些系统至关重要。虽然大多数分布式系统处理机级故障良好,但处理数据中心级故障不太常见。在我们的经验中,处理数据中心级故障对于运行真正的高可用性系统至关重要。我们的大多数系统(例如Photon,F1,Mesa)现在支持多归归归归归档。多宿主系统一直在多个数据中心运行,在数据中心之间自适应地移动负载,能够完全透明地处理任何比例的中断。本文主要集中在流处理系统上,并描述了我们建立高可用性多宿主系统的一般方法,讨论了共同的挑战和解决方案,并分享了我们在建设中学到的内容并运行这些大型系统十多年。

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