The growth of edge computing is providing businesses with new options for where, when, and how they store and process data. As a result, companies with cloud-first computing strategies are now revising them to include more edge use cases. They’re evolving and extending core-to-edge networks to achieve critical business goals such as delivering a superior digital customer experience, reducing costs, and improving security. There are already 15 billion edge devices deployed in the field, states STL Partners. 

What Is Edge Computing? 

Edge computing is a distributed computing model that stores and processes data where it is created — at the edge of the network. Data is either processed by connected devices themselves or onsite using edge computing. This capability eliminates the need for data to be transported across corporate or cloud networks for processing, which creates time delays and increases costs. Real-time data processing enables myriad IoT use cases across industries. The growing use of AI and 5G will only magnify this trend. 

$445 billion: Size of edge market by 2030, up from $9 billion in 2020. Source: STL Partners. 

By pursuing a decentralized model, enterprises can place edge sites close to customers and employees, enabling the delivery of robust digital services with real-time personalization capabilities. 

In a recent blog, we highlighted the advantages of edge computing, which include real-time data processing, lower storage and processing costs, lower latency, and enhanced regulatory compliance. 

Read our blog, Understanding the Impact of Edge Computing on Data Center Management

What Is Cloud Computing?

Cloud computing is the provision of computing resources on-demand over the Internet. Cloud service providers offer services such as Software as a Service (SaaS) business applications, Infrastructure as a Service (IaaS), and Platform as a Service (PaaS) and charge on a pay-as-you-go consumption based model.

Businesses choose cloud computing, because of its incredible flexibility, scalability, accessibility, and potential cost savings. They can add and subtract services and scale and up and down to match customer demand. (To save with cloud computing, companies need to exercise discipline and not waste spending on unused services. Many use cloud FinOps services to accomplish this goal.)

Source: BMC Software

Edge Computing Versus Cloud Computing: Considerations and Use Cases

With both edge and cloud computing, IT teams gain newfound flexibility in where they process and store data. The chart from STL Partners provides a handy cheat sheet on how to determine when to use edge versus cloud computing, by comparing performance against variables such as latency, security, cost, and more. We also provide an easy-to-use guide which suggests which use cases are best for edge and cloud computing below. 

Source: STL Partners

Ultra-Low/Low Latency	Greater Latency
Edge Computing	Cloud Computing
• Artificial intelligence models  • Autonomous vehicles / traffic management  • Content delivery  • Industrial automation • Oil and gas monitoring  • Patient monitoring • Predictive maintenance  • Real-time analytics • Smart cities and infrastructure  • Smart home applications • Smart grid applications • Telehealth	• Anything as a service (IaaS, PaaS, and more) • Business applications (including collaboration platforms) • Backup data workloads • Business continuity/disaster recovery services • Chatbots • Complex analytics/business intelligence • Data storage • File hosting • IT applications  • Large-scale data processing • Mobile services • Remote monitoring and management • SaaS applications  • Video streaming

3 verticals: Will comprise 84% of the edge computing market by 2026. They are media, transportation, and manufacturing. Source: STL Partners

Data Processing Scale
Small-/Medium-Scale	Large-Scale
Edge Computing	Cloud Computing
• 1-100+ racks • Includes network closets, server closets, micro data centers, and regional data centers, and telecommunications towers	• Thousands of racks • Includes managed service providers, colocation providers, and hyperscalers

Technology Environment
Decentralized	Centralized
Edge Computing	Cloud Computing
• Complex to manage • Many sites and devices to configure, update, • monitor, and manage  • More challenging to scale	• Simple to manage • Companies can rely on partners for data center management • Easy to scale

Regulatory Requirements
Sensitive Data	All Data Types
Edge Computing	Cloud Computing
• Sensitive data (PCI, PII, PHI) • Includes data governed by industry and country regulations	• Can be used for both sensitive and less sensitive data • Regulated data must be processed and stored in the country or region it is collected

Data Security Objectives
Improve Security	Enable Faster Innovation
Edge Computing	Cloud Computing
• Data is decentralized and there is less connectivity, reducing exposure risks • Less data is stored • Only aggregated data insights are shared to the cloud	• Data is centralized, increasing the need for strong data protections • The cloud contains raw data, including sensitive data

Locations
Remote	Centralized
Edge Computing	Cloud Computing
• May not always have internet access; devices need to be accessible by cell serviceIncludes remote locations • May not have IT individuals on staffMay be used in harsh environments (e.g., factories, telecom sites)	• Requires high bandwidth availabilityIn centralized locations close to customers • Serviced regularly by IT staff, both remotely and in-person • Often has state-of-the-art IT environments, with carefully controlled power and cooling

Edge Versus Cloud Computing: Which Should You Choose?

As the charts above indicate, you’ll consider different variables and use cases before selecting the right computing model. Thus, the answer to whether you should choose edge or cloud computing is likely, “Both.”  

Your company is transforming in real-time. You are evolving your business model to increase competitiveness, developing digital products and services, enabling employees to work remotely, and creating a data-driven culture. That means the mix of core, edge, and cloud computing services you use is ever-changing. 

While edge growth is an exciting trend, it’s also creating greater network complexity. Your IT teams are managing more sites and devices. And since edge sites often power critical services, it’s essential to keep these devices up and available. Much of this work will happen remotely, using tools that enable teams to access, configure, change, and power-cycle devices, even when internet access isn’t available. 

Whether you rely on cloud, edge computing, or both, you need 360-degree visibility to be successful. One way to achieve this is by deploying technology, such as configuration management databases (CMDBs) and data center infrastructure management solutions (DCIMs) that improve visibility, support enforcement of controls, and streamline management tasks. 

CMDBs can help your company automatically discover all of its software, hardware, and virtualized assets across your core-to-edge network; track configurations and changes; and aid IT service teams with diagnosing root causes when issues arise. DCIMs enable your IT teams to improve visibility into the power chain and improve thermal management, boosting performance of your larger edge sites, such as regional edge data centers. 

You can maximize edge sites advantages by monitoring and managing assets with Device42 CMDB and DCIM solutions.