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

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

It’s no secret that edge computing is gaining popularity and adoption, with both Forrester and Gartner having solid predictions for the technology’s going forward. Now, organizations developing 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 are incorporating edge computing into their overall cloud strategy. Here are three basic and actionable steps to take when implementing this type of model:

1. Update apps to run more efficiently and effectively – it’s time to simplify

Any digital transformation roadmap begins with an assessment of business needs and requirements, as well as an understanding of the impact of new technology on existing operations. Centralizing applications and services on the cloud requires implementing more complex, costly and highly available infrastructure designs at the edge to ensure that there is no impact on the business. Many organizations realize that when implementing cloud-to-edge service models, applications must first operate in a more distributed and autonomous manner to achieve the key benefits of performing on-premises data collection and processing, while maintaining a higher level of availability. This leads to an improved level of protection and stamina for critical business functions, particularly with the potential risk of losing connectivity to the cloud.

2. Decide how and where your data and applications will be processed – keep agility at the fore

The next step is to decipher how and where the data and applications will be processed or decide between what will be on the edge and easily accessible and what will be located deeper in the cloud and need a stronger level of connectivity. It’s important to think about the types of data processing that need to be done before considering turning things to the edge. The data required for critical and local site operations must remain on 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 consistency of data and centralized processing demands their performance on the edge, because this strategy does not 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 for other services hosted in the cloud such as smartphone keycard access and analytics, it is much more important for on-premises site operations and should be readily available to ensure that physical keycards are processed.

3. Assess and understand the risks of moving services to the edge – strive for large-scale decentralized security

The image data is on the edge like the banks’ outer coast. On the outer “edge” of the United States, anything along the “Outer Banks” is much less safe and more vulnerable to a hurricane or tropical storm. Data on the edge has similar security concerns. Transforming these services and the infrastructure to support them could create dozens, or perhaps hundreds, of new “small data centers” with new components, facilities, and considerations to manage. This can add significant workload to operations and prolong lifecycle management issues on a larger, more distributed scale. Additionally, as cutting-edge computing infrastructure such as work from home, the Internet of Things, and 5G gain strength, their lack of physical boundaries 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 processes are affected by the potential loss of connectivity to cloud services, companies must determine whether the evolving strategy is appropriate to their needs and requirements. Whether it’s perimeter applications, threat detection or debugging, security professionals return to basic network security principles when securing cloud-to-edge systems.

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

Leave a Comment