[网络领域顶会追踪系列#15][NSDI'22]使用OpTel检测短暂的光学事件

本系列为个人论文阅读笔记，大多数应该是对顶会摘要的个人菜鸟翻译，旨在让感兴趣的朋友能快速浏览、获取信息。如有错误或心得，欢迎在评论区交流指正！

Detecting Ephemeral Optical Events with OpTel

背景

光骨干网的衰退或失败事件会影响云服务的服务级别协议（service level agreement, SLA）。迅速地检测和排查这些事件以最小化它们的影响是很很重要的。

挑战

现有的遥测系统基于比较玄学（arcane）的工具（如SNMP），并且使用供应商指定的控制器来收集光数据，这影响了这些系统的灵活性和可扩展性。结果是，它们不能按时收集需要的数据，以及不能以很及时的方式排查出衰退或失败事件。

工作

设计和实现了OpTel，一个光遥测系统，使用一个集中式的供货商无感知（vendor-agnostic）的控制器来以流方式收集光数据。

具体的，它在光设备和控制器之间提供了灵活的供应商无感知的接口，并且从设备卸载数据管理任务（如创建一个查询表）到控制器上。结果是，OpTel可以收集秒级别的细粒度数据。

实验

它以及在腾讯的光骨干网上运行了超过六个月。细粒度的数据收集可以检测出短生命周期的事件（即转瞬即逝的事件）。和现有的遥测系统相比，OpTel精准地测量了超过两倍的光事件。它也能够在数秒内排查这些事件，比最先进方案快几个数量级。

原文摘要

Degradation or failure events in optical backbone networks affect the service level agreements for cloud services. It is critical to detect and troubleshoot these events promptly to minimize their impact. Existing telemetry systems rely on arcane tools (e.g., SNMP) and vendor-specific controllers to collect optical data, which affects both the flexibility and scale of these systems. As a result, they fail to collect the required data on time to detect and troubleshoot degradation or failure events in a timely fashion. This paper presents the design and implementation of OpTel, an optical telemetry system, that uses a centralized vendor-agnostic controller to collect optical data in a streaming fashion. More specifically, it offers flexible vendor-agnostic interfaces between the optical devices and the controller and offloads data-management tasks (e.g., creating a queryable database) from the devices to the controller. As a result, OpTel enables the collection of fine-grained optical telemetry data at the one-second granularity. It has been running in Tencent's optical backbone network for the past six months. The fine-grained data collection enables the detection of short-lived events (i.e., ephemeral events). Compared to existing telemetry systems, OpTel accurately detects 2x more optical events. It also enables troubleshooting of these optical events in a few seconds, which is orders of magnitude faster than the state-of-the-art.