Recent research has proposed a variety of cross-cutting tools to help monitor and troubleshoot end-to-end behaviors in distributed systems. However, most prior tools focus on data collection and aggregation, and treat analysis as a distinct step to be performed later, offline. This restricts the applicability of such tools to only doing post-facto analysis. However, this is not a fundamental limitation. Recent research has proposed tools that integrate analysis and decision-making at runtime, to directly enforce end-to-end behaviors and adapt to events.<\/p>\n
In this thesis I present two new applications of cross-cutting tools to previously unexplored domains: resource management, and dynamic monitoring. Retro, a cross-cutting tool for resource management, provides end-to-end performance guarantees by propagating tenant identifiers with executions, and using them to attribute resource consumption and enforce throttling decisions. Pivot Tracing, a cross-cutting tool for dynamic monitoring, dynamically monitors metrics and contextualizes them based on properties deriving from arbitrary points in an end-to-end execution.<\/p>\n
Retro and Pivot Tracing illustrate the potential breadth of cross-cutting tools in providing visibility and control over distributed system behaviors. From this, I identify and characterize the common challenges associated with developing and deploying cross-cutting tools. This motivates the design of baggage contexts, a general-purpose context that can be shared and reused by different cross-cutting tools. Baggage contexts abstract and encapsulate components that are otherwise duplicated by most cross-cutting tools, and decouples the design of tools into separate layers that can be addressed independently by different teams of developers.<\/p>\n
The potential impact of a common architecture for cross-cutting tools is significant. It would enable more pervasive, more useful, and more diverse cross-cutting tools, and make it easier for developers to defer development-time decisions about which tools to deploy and support.<\/p>\n","protected":false},"excerpt":{"rendered":"
Recent research has proposed a variety of cross-cutting tools to help monitor and troubleshoot end-to-end behaviors in distributed systems. However, most prior tools focus on data collection and aggregation, and treat analysis as a distinct step to be performed later, offline. This restricts the applicability of such tools to only doing post-facto analysis. 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