Towards cloud‐based unobtrusive monitoring in remote multi‐vendor environments. (16th September 2021)

• Record Type: Journal Article
• Authors: Moeyersons, Jerico; Kerkhove, Sarah; Wauters, Tim; De Turck, Filip; Volckaert, Bruno
• Is Part Of: Software, practice & experience. Volume 52:Number 2(2022)
• Page Start: 427
• Page End: 442
• Publication Date: 2021-09-16
• Subjects: Docker -- sidecar containers -- unobtrusive monitoring; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.3029
• Languages: English
• ISSNs: 0038-0644

Abstract

Abstract: Nowadays, many complex multi‐vendor production environments, such as telecom infrastructures in smart cities or on‐board passenger information systems in trains, are based on micro‐services and deployed in the cloud. From a service integrator viewpoint, building new solutions for these environments, which can host a large number of externally designed and developed micro‐services, is often complex and error‐prone. This is in part due to undocumented behaviour or undocumented architectural specifications of such systems. Advanced service monitoring can offer a solution to quickly detect anomalies or unexpected service interaction behaviour during on‐site integration. However, the monitoring service should not have an impact on the production environment itself. Therefore, this article proposes an agent‐based unobtrusive monitoring platform, capable of monitoring both internally developed and externally developed services through the use of sidecar containers. It monitors state, metrics and network traffic at micro‐service level and the research was conducted as part of the DynAMo research project, a collaboration with various industry partners. Prototype evaluation proves that our solution has a negligible impact (below 0.02% CPU usage on average) on an existing micro‐service environment just as other monitoring systems like Prometheus while offering additional functionality focused on multi‐vendor service integration. This makes it suitable to be deployed in complex production domains to further aid on‐site integration and quickly find potential new anomalies.