DynATOS+: A Network Telemetry System for Dynamic Traffic and Query Workloads
DynATOS+: A Network Telemetry System for Dynamic Traffic and Query Workloads
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通讯作者：
Chris Misa;Ramakrishnan Durairajan;R. Rejaie
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作者：
Chris Misa;Ramakrishnan Durairajan;R. Rejaie
-网络遥测系统提供对网络流量状态的重要可见性。通过利用现代可编程交换机硬件，在将这些系统扩展到生产网络流量工作负载方面取得了重大进展。在诸如流量工作量的组成以及在任何给定时间点运行的查询的数量和类型等动态情况下，对于有效利用这些硬件目标的有限资源的关注较少。然而，这两个动态对资源需求和查询准确性都有影响。在我们以前工作的基础上，DyATOS认为这个动力学问题促使将遥测系统重组为资源调度器，本文介绍了DyATOS+的设计、实现和评估。DyATOS+使用与DyATOS相同的高效时分近似和调度算法，并允许用户定义的查询精度和延迟规范，旨在实现与查询执行的权衡，以减少硬件资源使用。然而，与DyATOS不同的是，DyATOS+允许终端用户使用简单的精确度目标，从而显著减轻了终端用户表达查询的负担。例如，在DyATOS+中指定每个查询的精度目标的方法不再需要最终用户提前知道查询结果的平均范围或提交多个试验查询来调整他们的精度目标规格。我们进行了广泛的基于模拟的评估，评估结果如下：(I)DyATOS+的这一新功能在实践中有效，(Ii)详细说明了针对各种系统参数的查询执行和硬件资源使用所产生的权衡，以及(Iii)允许在流量工作负载组成发生变化的基础上评估系统性能，而流量工作负载构成的变化是该领域以前的工作所未及的。
—Network telemetry systems provide critical visibility into the state of network traffic. By leveraging modern programmable switch hardware, significant progress has been made to scale these systems to production network traffic workloads. Less attention has been paid towards efficiently utilizing these hardware targets’ limited resources in the face of dynamics such as the composition of the traffic workload as well as the number and types of queries running at any given point in time. However, both of these dynamics have implications on resource requirements and query accuracy. Building on our prior work DynATOS, which argues that this dynamics problem motivates reframing telemetry systems as resource schedulers , we present in this paper the design, implementation, and evaluation of DynATOS+. DynATOS+ relies on the same efficient time-division approximation and scheduling algorithm that DynATOS uses and that allows for user-defined query accuracy and latency specifications that are intended to result in tradeoffs with respect to query execution to reduce hardware resource usage. However, unlike DynATOS, DynATOS+ significantly reduces the burden on end users to express their queries by allowing them to use simple-to-state accuracy goals. For example, the method for specifying per-query accuracy goals in DynATOS+ no longer requires end users to either know the average range of query results in advance or to submit multiple trial queries to tune their accuracy goal specifications. We perform extensive simulation-based evaluations that (i) show that this new functionality of DynATOS+ works in practice, (ii) illustrate in detail the tradeoffs that result with respect to query execution and hardware resource usage for a wide range of systems parameters, and (iii) allow for an assessment of system performance under changing query workloads on top of changes in the composition of traffic workloads that has eluded previous work in this area.