1,235 research outputs found
Real-Time Context-Aware Microservice Architecture for Predictive Analytics and Smart Decision-Making
The impressive evolution of the Internet of Things and the great amount of data flowing through the systems provide us with an inspiring scenario for Big Data analytics and advantageous real-time context-aware predictions and smart decision-making. However, this requires a scalable system for constant streaming processing, also provided with the ability of decision-making and action taking based on the performed predictions. This paper aims at proposing a scalable architecture to provide real-time context-aware actions based on predictive streaming processing of data as an evolution of a previously provided event-driven service-oriented architecture which already permitted the context-aware detection and notification of relevant data. For this purpose, we have defined and implemented a microservice-based architecture which provides real-time context-aware actions based on predictive streaming processing of data. As a result, our architecture has been enhanced twofold: on the one hand, the architecture has been supplied with reliable predictions through the use of predictive analytics and complex event processing techniques, which permit the notification of relevant context-aware information ahead of time. On the other, it has been refactored towards a microservice architecture pattern, highly improving its maintenance and evolution. The architecture performance has been evaluated with an air quality case study
Microvision: Static analysis-based approach to visualizing microservices in augmented reality
Microservices are supporting digital transformation; however, fundamental
tools and system perspectives are missing to better observe, understand, and
manage these systems, their properties, and their dependencies. Microservices
architecture leans toward decentralization, which yields many advantages to
system operation; it, however, brings challenges to their development.
Microservices lack a system-centric perspective to better cope with system
evolution and quality assessment. In this work, we explore
microservice-specific architecture reconstruction based on static analysis.
Such reconstruction typically results in system models to visualize selected
system-centric perspectives. Conventional models are limited in utility when
the service cardinality is high. We consider an alternative data visualization
using 3D space using augmented reality. To begin testing the feasibility of
deriving such perspectives from microservice systems, we developed and
implemented prototype tools for software architecture reconstruction and
visualization of compared perspectives
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