Edge Computing

Design in the cloud, execute at the edge: A hybrid framework that focuses on distributed data

Getting the best of both worlds is the key to managing distributed data growth for industrial IoT applications.


Getting the best of both worlds is the key to managing distributed data growth for industrial IoT applications.

Edge computing is growing rapidly and it offers many benefits as compared to cloud computing: low bandwidth requirement, low data cost, low latency, distributed computing workload, and etc.  For many organizations, they simply cannot send data to the cloud for privacy and security requirements. In this case, edge computing is necessary and an on-premises (on-prem)  solution needs to be implemented.

However, on-prem applications have their own limitations, including:

  1. Difficult to manage applications and devices across multiple sites. Today’s companies are distributed globally, and their solutions are deployed globally. When each site runs its own applications within its own local network, application management and support become more challenging.

  2. Difficult to analyze data across multiple sites. Data is more powerful as the data set grows. By keeping data in silos reduces the effectiveness of driving data insights.

  3. Cannot reap long-term benefits of cloud features. Today’s cloud infrastructure offers many advanced features. Not being able to leverage on them can potentially hurt a company’s competitiveness in the long run.

How do we resolve these limitations? The solution is to design in the cloud and execute at the edge. For example, Prescient Designer offers the unique capability to design application logic in the cloud and then deploy them to the edge for execution. This means that application logic can be distributed to multiple sites across the globe. Since execution is at the edge, data stays safely on-prem. However, the user still has the option to send processed or non-sensitive data to the cloud for aggregation and analysis.

Organizations can overcome the limitations of on-prem solutions by:

  1. Design in the cloud. Designing in the cloud makes it easy to distribute application logic to multiple sites across the globe. The cloud contains only the application logic, not the data. This also makes it easy to track changes to the application, in a single place, for all organizational sites.

  2. Execute at the edge. Application logic is delivered to the edge via secure and encrypted communication tunnel. Application logic is then executed at the edge and raw and sensitive data are processed at the edge. This helps preserve data privacy and makes it easier to follow data protection regulations.

  3. Process data at the edge and then distribute it. Typically, processed data will be saved in on-prem databases, and this is executed via the application logic. But if the user chooses to, they can send processed or non-sensitive data to the cloud. When the cloud aggregates such data from all sites, it can perform advanced data analytics on it.

The benefits of cloud computing and edge computing can be realized in Prescient Designer because applications are built in low-code. Low-code applications in Prescient Designer are coded in simple JSON data objects, vs. complex code bases, so they incur little delay or bandwidth to distribute. Furthermore, applications can be moved easily between the edge and the cloud, allowing users to optimize where the processing happens, making this a compelling framework to serve the growing need of distributed data acquisition and analytics.

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