The use of monitoring systems based on cloud computing has become common for smart buildings. However, the dilemma of centralization versus decentralization, in terms of gathering information and making the right decisions based on it, remains. Performance, dependent on the system design, does matter for emergency detection, where response time and loading behavior become very important. We studied several design options based on edge computing and containers for a smart building monitoring system that sends alerts to the responsible personnel when necessary. The study evaluated performance, including a qualitative analysis and load testing, for our experimental settings. From 700+ edge nodes, we obtained response times that were 30% lower for the public cloud versus the local solution. For up to 100 edge nodes, the values were better for the latter, and in between, they were rather similar. Based on an interpretation of the results, we developed recommendations for five real-world configurations, and we present the design choices adopted in our development for a complex of smart buildings.

Moving to the cloud is a topic that tends to be present in all enterprises that have digitalized their activities. This includes the need to work with software environments specific to various business domains, accessed as services supported by various cloud providers. Besides provisioning, other important issues to be considered for cloud services are complexity and performance. This paper evaluates the processes to be followed for the deployment of such a software environment in the cloud and compares the manual and automated methods in terms of complexity. We consider several metrics that address multiple concerns: the multitude of independent paths, the capability to distinguish small changes in the process structure, plus the complexity of the human tasks, for which specific metrics are proposed. We thus show that the manual deployment process is from two to seven times more complex than the automatic one, depending on the metrics applied. This proves the importance of automation for making such a service more accessible to enterprises, regardless of their level of technical know-how in cloud computing. In addition, the performance is tested for an example of an environment and the possibilities to extend to multicloud are discussed.

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