Ensuring a Smooth and Effective Edge Deployment in the Cloud

Cloud computing isn’t a fad or limited to a few select industries. The ability to access a range of computing services, including databases, data storage, and servers, has applications in almost any industry, from retail to healthcare and finance.

Cloud computing in Edge AI brings numerous benefits to businesses, but combining it with edge deployment can unlock even greater innovation. By successfully integrating cloud and edge AI, businesses can go beyond the limitations of the cloud alone. While it doesn’t require an IT degree, following a few key steps can ensure a smooth and impactful integration, driving success and growth.

Steps for Integrating Edge and Cloud AI

Even though Edge AI deployment in the cloud isn’t difficult, it’s also not plug-and-play ready. There are some steps to follow to ensure everything goes smoothly. After all, one of the primary reasons for combining Edge and cloud technology is to push innovation further and not make it more difficult.

Identify Uses for Edge Computing

Okay, keeping your data closer to the source is a good reason to consider Edge deployment in the cloud. However, it’s not always the best reason to deploy the technology. Instead of getting excited over being able to access data in real-time, think about how the technology can be used in your business processes.

A good place to start is with your business model. Do you have a robust remote workforce that is constantly accessing cloud applications? What about your products? Do your products depend on receiving and relaying data in real time? If so, things like reduced latency, easy data access, flexibility, and connectivity are items Edge computing can help improve.

However, if your staff rarely uses the cloud or your devices aren’t dependent on real-time data, Edge deployment may not be a priority.

Connectivity Requirements

You already know connectivity is key. Without connectivity, your systems and networks are useless. Connectivity refers to bandwidth and you need plenty to ensure your services and infrastructure are supported. So, how much bandwidth do you need to support everything including Edge deployment? The answer varies by industry.

An energy company will probably run smoothly when its bandwidth supports latency speeds of around 10ms. Yes, this is low enough to keep most avid gamers happy. Energy companies can access, collect, and analyze data in real time. This means Edge deployment needs to take place in customers’ markets. For example, the bandwidth will need to be able to support Edge deployment in neighborhood substations. The deployment can’t be limited to the main energy hub.

When it comes to industries manufacturing and supporting self-driving (AI-powered) cars, latency speeds need to be lower than 10ms. Your deployment may include adding micro-edge centers. Where the micro-edge centers are located can vary. Some examples can include support from 5G wireless networks. Figuring out the connectivity requirements is a crucial step towards ensuring a smooth and effective Edge deployment.

Look at Your In-House IT Abilities

Edge deployment isn’t exactly a new technology but it’s also not a common skill. Skill gaps in IT departments are a growing problem that’s only expected to get worse as technology continues to advance at a rapid pace. There’s a good chance your IT department has a few gaps in its skill set and this probably includes Edge computing.

Don’t worry, the gap in IT skills doesn’t mean letting go of your current team and bringing in new graduates. Instead, take an inventory of your team’s existing skills. Edge deployment requires several skills, and your team may be more equipped than you or they fully realize.

Some of the necessary skills include data engineering, computer networking, cybersecurity, and cloud computing. There’s a good chance you can cross most or all of these skills off the list. What skills you’re missing in-house can be easily outsourced to consultants and managed service providers.

Data Security

If your business is handling consumer information, data privacy and security laws apply. You must meet specific compliance regulations to avoid potential fines and other penalties. For example, HIPAA applies to the healthcare industry and California has rules protecting consumers’ private information. These are only a couple of examples of existing data privacy regulations.

As noted earlier, your Edge deployment architecture can affect your existing cybersecurity protocols. To stay in compliance with industry standards, you need to take a look at how Edge deployment will affect your security. This will probably mean putting more robust measures in place. Your IT department will be vital to ensuring your data security after an Edge deployment in the cloud.

A Successful Edge AI Deployment in the Cloud is Possible

You can successfully deploy Edge AI technology in the cloud. However, it will take some planning and making a few adjustments to some existing practices and protocols.