Nonintrusive Monitoring of Microservice-Based Systems

Pina, Fabio; Correia, Jaime; Filipe, Ricardo; Araújo, Filipe; Cardroom, Jorge

doi:10.1109/nca.2018.8548311

Cited by 25 publications

(19 citation statements)

References 6 publications

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“…Monitoring a full cross-technology service offering integrated with third-party services that cannot be altered or recompiled remains a research challenge. 12 Such type of service deployments also suffer from difficulties to assess adherence to security constraints. Current security monitoring solutions are often limited to network-level intrusion detection systems or monitoring authentication attempts.…”

Section: Related Workmentioning

confidence: 99%

“…and operational monitoring can be baked into API gateways (Kong, 10 Traefik, 11 etc.). Monitoring a full cross‐technology service offering integrated with third‐party services that cannot be altered or recompiled remains a research challenge 12 …”

Section: Related Workmentioning

confidence: 99%

“…Pina et al 12 propose a non‐intrusive monitoring system of micro‐service‐based systems based on log gateway activity to register all calls to and between micro‐services, as well as their responses, thus enabling the extraction of topology and performance metrics, without changing source code. The authors resorted to three Netflix components to gather metrics outside of the critical path while our proposed solution uses an agent‐based approach to gather metrics.…”

Section: Related Workmentioning

confidence: 99%

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Towards cloud‐based unobtrusive monitoring in remote multi‐vendor environments

et al. 2021

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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.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Towards cloud‐based unobtrusive monitoring in remote multi‐vendor environments

et al. 2021

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“…Phipathananunth et al [70] described Pink, a framework for synthetic runtime monitoring of microservices software systems. Pina et al [71] proposed a much simpler and noninvasive monitoring approach that includes topology and performance metrics. Zhou et al [72] presented a debugging approach for microservice systems based on the delta debugging algorithm, which is to minimize failure inducing deltas of circumstances for effective debugging.…”

Section: Related Workmentioning

confidence: 99%

No Free Lunch: Microservice Practices Reconsidered in Industry

Xiang¹,

Peng²,

He³

et al. 2021

Preprint

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Microservice architecture advocates a number of technologies and practices such as lightweight container, container orchestration, and DevOps, with the promised benefits of faster delivery, improved scalability, and greater autonomy. However, microservice systems implemented in industry vary a lot in terms of adopted practices and achieved benefits, drastically different from what is advocated in the literature. In this article, we conduct an empirical study, including an online survey with 51 responses and 14 interviews for experienced microservice experts to advance our understanding regarding to microservice practices in industry. As a part of our findings, the empirical study clearly revealed three levels of maturity of microservice systems (from basic to advanced): independent development and deployment, high scalability and availability, and service ecosystem, categorized by the fulfilled benefits of microservices. We also identify 11 practical issues that constrain the microservice capabilities of organizations. For each issue, we summarize the practices that have been explored and adopted in industry, along with the remaining challenges. Our study can help practitioners better position their microservice systems and determine what infrastructures and capabilities are worth investing. Our study can also help researchers better understand industrial microservice practices and identify useful research problems.

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“…Although this work measures data at the microservice level, network performance is not considered. Pina et al [33] instead focus mainly on monitoring the network performance without user code instrumentation. To avoid instrumentation they introduce infrastructural components that are used by the application such as the Application Programming Interface (API) gateway, the service discovery, and the load balancers.…”

Section: Application Performance Monitoring and Network Performance Mmentioning

confidence: 99%

A Black-box Monitoring Approach to Measure Microservices Runtime Performance

Brondolin

Santambrogio

2020

ACM Trans. Archit. Code Optim.

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Microservices changed cloud computing by moving the applications’ complexity from one monolithic executable to thousands of network interactions between small components. Given the increasing deployment sizes, the architectural exploitation challenges, and the impact on data-centers’ power consumption, we need to efficiently track this complexity. Within this article, we propose a black-box monitoring approach to track microservices at scale, focusing on architectural metrics, power consumption, application performance, and network performance. The proposed approach is transparent w.r.t. the monitored applications, generates less overhead w.r.t. black-box approaches available in the state-of-the-art, and provides fine-grain accurate metrics.

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Nonintrusive Monitoring of Microservice-Based Systems

Cited by 25 publications

References 6 publications

Towards cloud‐based unobtrusive monitoring in remote multi‐vendor environments

Towards cloud‐based unobtrusive monitoring in remote multi‐vendor environments

No Free Lunch: Microservice Practices Reconsidered in Industry

A Black-box Monitoring Approach to Measure Microservices Runtime Performance

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