INTERTEC BLOG

Cloud-to-Edge Service Models

May 26, 2022 / by Frederid Palacios

Now that cloud computing is commonplace, IT leaders and businesses are searching for ways to optimize their preexisting cloud infrastructure. For many, the next big thing is edge computing. Edge computing quite literally brings data to the “edge” of the cloud. With easier access to data, this model reduces latency, bringing data to users faster. 

So, how do businesses get to the edge? With a cloud-to-edge service model, users can integrate edge computing into their current cloud strategy. Still, implementing any new cloud model takes strategy, so we’re here to break down everything you need to know about cloud-to-edge service models. 

Young businessman sitting in office chair in front of a wall with cloud thought sketched on a chalkboard above his head

Edge Computing

 

Before jumping into cloud-to-edge service models, it’s important to understand how edge computing differs from traditional cloud computing. As we mentioned, edge computing involves specifically placing data on the “edge” of a cloud network as opposed to the core. While the cloud is all about speed and accessibility, edge computing takes that one step further. 

With edge computing, not only is data stored at the edge of a cloud network but it is also processed closer to the source. Because data is more easily accessible, latency is significantly reduced. This means that users can process, access, and share data faster with the edge than traditional means of cloud computing. 

For many organizations, it may seem as though your current cloud infrastructure is fast enough to meet your needs. While this may be true for now, consider the volume of data you are processing and storing. With the implementation of applications such as IoT devices, this volume will increase if it hasn’t already. If your cloud infrastructure cannot process such a vast volume of data fast enough, it will eventually overwhelm your network, creating bandwidth and latency issues. 

This is where edge computing comes in. The edge is equipped to handle a greater volume of data than traditional cloud methods, ensuring that an organization’s infrastructure can process significant amounts of data with ease. For organizations looking to scale up their cloud infrastructure, the edge is the solution you need to maintain agility and speed while expanding your network. 

 

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Implementing the Cloud-to-Edge Service Model



Streamline Applications

 

The first step to implementing the cloud-to-edge service model is to streamline all preexisting applications. The cloud is all about centralization, and the edge is no different. Still, with centralization comes more complex infrastructure designs. For all applications to work interoperably in one location, applications need to be streamlined to maintain efficiency. 

The best way to streamline applications is first to update them to operate more efficiently and effectively. Ensuring that applications are up-to-date and working correctly is essential because it will be more of a hassle to go back in afterward and make these changes. In addition to updating applications, it can be highly beneficial to automate them. Implementing automated updates and backups will save you time in the long run and ensure that applications continue to run efficiently long after you introduce them to the edge. 

 

Map Out Your Edge Plan

 

Once applications are running optimally, it’s time to decide how and where these applications will be processed. This essentially means that you will be determining what exactly will be on the edge and more easily accessible versus what will be stored deeper in the cloud, needing a stronger level of connectivity. 

While it may seem as though the whole purpose of the edge is to make everything more accessible, that isn’t feasible. Furthermore, not every application and system on your network needs to be as easily accessible as others. Consider which data is critical for local operations and what you use on a daily basis. When making these determinations, keep agility in mind. These functions take more priority in the need to operate independently and maintain connectivity than less frequently used data. 

It’s also important to consider which systems require data consistency and add the most value to your business - if they don’t, they may be better suited to the core of the cloud. The data stored deeper in the cloud will still be stored and easily accessible, but it isn’t so crucial to your daily operations that it needs to take up valuable space on the edge. 

 

Address the Risks

 

With any shift of services, there is risk involved. If done incorrectly, your organization could lose or compromise valuable data or cause cloud misconfigurations later down the road. Even beyond the transition to the edge, data is more valuable when located on the edge. Just as this data is easier for your organization to access, it is easier for others to access. In contrast, data and systems stored deeper into the core of the cloud are more secure. 

While you want specific data to avoid latency issues and move faster, hence why it was moved to the edge, you run the risk of exposing it to greater security risks. Data necessary for daily operations needs to be easily and quickly accessed. Still, it also needs to be highly protected from security threats as it sustains your day-to-day operations. For this reason, the edge requires a bit of a balancing act when choosing which data to store. 

Nevertheless, there are risks with any cloud model. As the cloud has no real “borders,” it draws a lot of attention from hackers. As such, organizations must consider the security risks present when implementing a cloud-to-edge service model. Fortunately, there are preventative measures that organizations can take to mitigate these risks. 

 

The Future of the Cloud

 

Many companies choose to utilize third-party service providers for their cloud service needs. With an MSP, organizations can easily outsource their migration to not only the cloud but the edge as well. With expert assistance, organizations significantly reduce the risk of running into cloud misconfigurations later on. 

Even beyond migration, an MSP will help organizations determine which data is best-suited for the edge versus the core of the cloud. In helping to facilitate the balancing act between accessibility and security, organizations can make the right decision regarding their data. 

MSPs will also improve cloud security as a whole with 24/7 monitoring. By monitoring your cloud environment, organizations can not only detect security threats quickly but also prevent them altogether. As data on the edge is at a higher risk than data stored deeper in the cloud, constant monitoring is the best way to avoid a major data breach. With an MSP, organizations can receive all of the benefits of edge computing at no stress to their internal department, ensuring accuracy, security, and efficiency. 

When executed correctly, the cloud-to-edge service model will provide organizations with enhanced speed, agility, and efficiency. Edge computing enables businesses to engage with data faster, accelerating daily operations while opening them up to new digital opportunities. With an improved ability to access and process significant volumes of data, the cloud-to-edge service model is the future of the cloud.

 

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Tags: Cloud Migration

Frederid Palacios

Written by Frederid Palacios

Fred Palacios is a seasoned software architect with more than 20 years of experience participating in the entire software development cycle across a host of different industries--from automotive and services to petroleum, financial, and supply chain. In that time, his experience working closely with high-level stakeholders has provided him with a strategic vision for developing the right solutions to flexibly meet critical business needs. As CTO of Intertec, he's continuing to focus on the creation of business-critical applications for large enterprise projects, particularly those that handle high concurrency and large datasets. He is passionate about using technology as a tool to solve real-world problems and also mentoring technical teams to achieve their maximum potential and deliver quality software.

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