Unexpected bursty traffic brought by certain sudden events, such as news in the spotlight on a social network or discounted items on sale, can cause severe load imbalance in backend services. Migrating hot data - the standard approach to achieve load balance - meets a challenge when handling such unexpected load imbalance, because migrating data will slow down the server that is already under heavy pressure. This article proposes PostMan, an alternative approach to rapidly mitigate load imbalance for services processing small requests. Motivated by the observation that processing large packets incurs far less CPU overhead than processing small ones, PostMan deploys a number of middleboxes called helpers to assemble small packets into large ones for the heavily-loaded server. This approach essentially offloads the overhead of packet processing from the heavily-loaded server to helpers. To minimize the overhead, PostMan activates helpers on demand, only when bursty traffic is detected. The heavily-loaded server determines when clients connect/disconnect to/from helpers based on the real-time load statistics. To tolerate helper failures, PostMan can migrate connections across helpers and can ensure packet ordering despite such migration. Driven by real-world workloads, our evaluation shows that, with the help of PostMan, a Memcached server can mitigate bursty traffic within hundreds of milliseconds, while migrating data takes tens of seconds and increases the latency during migration.

中文翻译：

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PostMan：通过按需卸载数据包处理来快速缓解突发流量


某些突发事件（例如社交网络上的新闻焦点或打折商品）带来的意外突发流量可能会导致后端服务负载严重不平衡。迁移热数据——实现负载平衡的标准方法——在处理这种意外的负载不平衡时会遇到挑战，因为迁移数据会减慢已经承受很大压力的服务器的速度。本文提出了 PostMan，这是一种快速缓解处理小请求的服务负载不平衡的替代方法。由于观察到处理大数据包比处理小数据包所产生的 CPU 开销要少得多，PostMan 部署了许多称为助手的中间盒，将小数据包组装成大数据包，以供负载较重的服务器使用。这种方法本质上将数据包处理的开销从负载较重的服务器卸载到助手。为了最大限度地减少开销，PostMan 仅在检测到突发流量时才按需激活助手。负载较重的服务器根据实时负载统计数据确定客户端何时与助手连接/断开连接。为了容忍帮助程序故障，PostMan 可以跨帮助程序迁移连接，并且可以在进行此类迁移时确保数据包排序。在实际工作负载的驱动下，我们的评估表明，在PostMan的帮助下，Memcached服务器可以在数百毫秒内缓解突发流量，而迁移数据则需要数十秒，并增加了迁移过程中的延迟。