Vnode: Low-Overhead Transparent Tracing of Node.js-Based Microservice Architectures

Herve M. Kabamba (), Matthew Khouzam and Michel R. Dagenais
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Herve M. Kabamba: Computer and Software Engineering Department, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
Matthew Khouzam: Ericsson Canada, Montréal, QC H4S 0B6, Canada
Michel R. Dagenais: Computer and Software Engineering Department, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada

Future Internet, 2023, vol. 16, issue 1, 1-20

Abstract: Tracing serves as a key method for evaluating the performance of microservices-based architectures, which are renowned for their scalability, resource efficiency, and high availability. Despite their advantages, these architectures often pose unique debugging challenges that necessitate trade-offs, including the burden of instrumentation overhead. With Node.js emerging as a leading development environment recognized for its rapidly growing ecosystem, there is a pressing need for innovative performance debugging approaches that reduce the telemetry data collection efforts and the overhead incurred by the environment’s instrumentation. In response, we introduce a new approach designed for transparent tracing and performance debugging of microservices in cloud settings. This approach is centered around our newly developed Internal Transparent Tracing and Context Reconstruction (ITTCR) technique. ITTCR is adept at correlating internal metrics from various distributed trace files to reconstruct the intricate execution contexts of microservices operating in a Node.js environment. Our method achieves transparency by directly instrumenting the Node.js virtual machine, enabling the collection and analysis of trace events in a transparent manner. This process facilitates the creation of visualization tools, enhancing the understanding and analysis of microservice performance in cloud environments. Compared to other methods, our approach incurs an overhead of approximately 5% on the system for the trace collection infrastructure while exhibiting minimal utilization of system resources during analysis execution. Experiments demonstrate that our technique scales well with very large trace files containing huge numbers of events and performs analyses in very acceptable timeframes.

Keywords: cloud; microservices; distributed tracing; transparent tracing; trace analysis; debugging; performance; monitoring; Node.js; trace context (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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