3 Steps To Take When Implementing Cloud-to-Edge Service Models

With the rapid push toward remote work, the pandemic catapulted enterprises into the age of anywhere operations. Nearly 50% of all employees will remain remote, creating challenges, opportunities, and security risks for IT organizations. Through this level of digital transformation, enterprise technologists have been encouraged to accelerate cloud migrations, increase end user satisfaction, automate service delivery, protect the entire infrastructure, and cut costs. These goals can be daunting and difficult to achieve collectively, but with the right creative strategies, they are attainable.

It’s no secret that edge computing is gaining popularity and adoption, as both Forrester and Gartner have strong predictions for the technology moving forward. Now, enterprises evolving their presence in the cloud are evaluating the benefits of edge to take their operations to the next level of speed and efficiency.

With cloud-to-edge service models, companies bake edge computing into their overall cloud strategy. Here are three foundational and actionable steps to take when implementing this type of model:

1. Update applications to operate more efficiently and effectively — time to streamline

Any digital transformation roadmap starts with the evaluation of business needs and requirements, as well as an understanding of the impact the new technology will have on current operations. Centralization of applications and services to the cloud requires implementing more complex, costly, and highly available infrastructure designs at the edge to ensure there is no impact to the business. Many organizations realize that when implementing cloud-to-edge service models, applications need to first operate in a more distributed and independent manner to realize the key benefits of performing local data gathering and processing, while maintaining a higher level of availability. This creates an enhanced level of protection and endurance for critical business functions, especially with the potential risk of losing connectivity to the cloud.

2. Map out how and where data and applications will be processed — keep agility top of mind

The next step is decoding how and where the data and applications will be processed or delineating between what will be on the edge and easily accessible and what will reside deeper in the cloud and need a stronger level of connectivity. It is important to consider which types of data processing need to be performed before looking at shifting things to the edge. Data that is needed for critical and local site operations must remain at the edge as it will allow these functions to operate independently, without the risk of losing connectivity to the cloud. There are also certain systems and services where the need for data consistency and centralized processing takes performing them at the edge out of question, because this strategy doesn’t add value to the business.

One use case for this would be local “caches” where there is no real time dependency and data consistency can be handled asynchronously. Take hotel key card management, for example. While some of this data may be useful to other services hosted in the cloud like smartphone keycard access and analytics, it is much more important at the edge for local site operations and should be easily available to ensure physical key cards are processed.

3. Evaluate and understand the risks of shifting services to the edge — strive to achieve decentralized full-scale security

Picture data at the edge like the coastline of the Outer Banks. On the outer “edge” of the US, anything located along the Outer Banks is far less secure and more susceptible to a hurricane or tropical storm. Data located at the edge has similar security concerns. Shifting these services and the infrastructure needed to support them can create dozens, or maybe even hundreds, of new ‘mini datacenters’ with new components, facilities, and considerations that have to be managed. This can add substantial overhead for operations and extend lifecycle management issues on a larger and more distributed scale. Additionally, as edge computing infrastructure such as work-from-home, IoT, and 5G gain steam, its lack of physical borders and containment provides a rich attack vector for hackers. Organizations must assess these risks when implementing cloud-to-edge service models. When critical business functions or operations are impacted due to the potential loss of connectivity to cloud services, companies must determine if an edge strategy is appropriate for their needs and requirements. Whether it’s perimeter applications, threat detection, or patching, security professionals return to basic principles of network security when securing cloud-to-edge systems.

Implementing cloud-to-edge service models requires careful planning and execution, as many of the potential risks can cause vulnerability for the business. The inability to access critical data opens up added security risks that are key considerations for organizations as they evaluate their systems and perform data mapping in the early stages of implementation. When done correctly, cloud-to-edge service models can provide organizations with greater speed and efficiency, enabling them to achieve their broader digital transformation and business goals. Cloud-to-edge is a powerful combination and opens a whole new world of exciting possibilities.