IoT Cloud Integrated with Edge Computing
Performance improvement with architectural considerations
When integrated with the Edge computing in the IoT ecosystem, Cloud computing can add better business value and higher performance to the IoT fed Big Data and Analytics solutions.
We all know the recent growing trends for Cloud Computing. Cloud marked a paradigm shift in Information Technology and the Computing field. IoT Cloud is a critical player in the overall data ecosystem. The central role the Cloud plays in IoT is to facilitate the data integration of the solution components.
IoT solutions are mainly used to provide real-time information to consumers. The data required in real-time can be massive in scale. The Cloud, along with computing power, storage, network, analytics, metering, and billing components, can make this information rapidly available for the consumers. However, there are always network concerns in remote locations as I highlighted in my IOT Solution guide book.
As I pointed out in previous articles, the integration of the Cloud to IoT can create new revenue streams from streaming big data. Integrating the Cloud with the IoT can create new business models enriched by real-time analytics and directly-consumed information anywhere at the same time.
We can confirm that without the Cloud, the IoT can hardly add any value due to its real-time data and information-rich nature requiring a special hosting mechanism. However, without the integration of Edge Computing, Cloud services cannot provide optimal performance.
The addition of the Cloud to the IoT can also contribute to improved security, availability, and performance of the IoT-based Big Data and Analytics solutions.
Cloud providers have rigorous security, availability, and performance metrics established based on a service consumption model. In particular, IoT-enabled Cloud systems seem to pose additional security measures, as evident in several public Cloud service offerings. Edge computing enhanced these capabilities to the next level.
What is Edge Computing?
After Cloud Computing, Edge Computing can be seen as a paradigm shift in the IT industry.
The purpose of Edge Computing is to bring computing and data storage components close to the service consumption locations. This innovative approach can dramatically improve network bandwidth and network response times especially by reducing network latency.
The key point is:
When integrated with the Edge computing in the IoT ecosystem, Cloud computing can add better business value to the IoT based Big Data and Analytics solutions. The main reason for this is that Edge computing can do the filtering for the Cloud to focus on the usable data.
Therefore, it is essential for the IoT solution architects and designers to understand the Cloud Computing service models leveraging Edge Computing approach and the lead solutions considering these key technology components. In order to obtain optimal performance, higher security, higher availability, and lower costs, we must integrate Cloud & Edge Computing for the IoT and Big Data Analytics solutions.
As IoT solution architects and designers, being aware of the capabilities of Cloud technology stacks, Edge Computing, and their powerful management tools can be extremely beneficial in creating large-scale commercial IoT and Big Data Analytics solutions.
This capability is a technical leadership requirement for the IoT solution architects and designers to add desired business value to the commercial IoT solutions.
Reference
Architecting Digital Transformation by Dr Mehmet Yildiz
Samples from my technology and architecture books on Medium
Digital Transformation Handbook for Solution Architects
An Architectural and Design Guide
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