Abstract
Osmotic computing is a new IoT application programming paradigm thats driven by the significant increase in resource capacity/capability at the network edge, along with support for data transfer protocols that enable such resources to interact more seamlessly with Cloud-based services. Much of the difficulty in QoS and performance monitoring of IoT applications in an Osmotic computing environment is due to the massive scale and heterogeneity (IoT + Edge + Cloud) of computing environments. To, this end, this work presents an integrated monitoring system for monitoring IoT applications decomposed as microservices and executed in an Osmotic computing environment. A real-world smart parking IoT application is used for an experimental evaluation and for demonstrating the effectiveness of the proposed approach. Through rigorous experimental evaluation, we validate the Osmotic monitoring system ability to holistically identify variation in CPU, memory, and network latency of microservices deployed across Cloud and Edge layers.