Cloud Computing vs. Edge Computing: Which is Better for My Business?

What is the best computing model for your company? A good way to answer this question is by analyzing both of these technology models to understand key differences, how they work, and how they can help you and your business.

Mariana Bellorín Aguilera - Technical Writer
Cloud Computing vs. Edge Computing: Which is Better for My Business?

Cloud computing or edge computing? Comparing these two computing models is very common, especially after 2020, when edge computing became more mainstream among large companies and edge platforms went to great lengths in making the onboarding and migration process easier. With increased adoption by companies focused on improving user experience, efficiency and time-to-market while reducing their IT operational costs, and powered by a rising number of professionals fluent in edge-based technologies, industries across the world accelerated their digital transformation plans.

The trend of heavy capital investment in software, hardware and networking is expected to continue. In an increasingly hyper-connected economy, speed, reliability, scale and user experience are critical, and designing a robust solution will make a key difference for your business.

Considering the growing data demands of users worldwide, and the need for a reliable, scalable and secure platform to handle those demands, what is the best computing model for your company? A good way to answer this question is by analyzing both of these technology models to understand key differences, how they work, and how they can help you and your business.

What is Cloud Computing?

Just a few years ago, the use of on-premise technology was still widespread. In other words, the software had to be installed on a computer and you could only edit documents or complete tasks from that computer. Larger companies had to set up and maintain internal servers, manage specialized networking equipment, and hire IT operational staff working round-the-clock to mitigate downtime and manage the operation of their organization’s resources.

The emergence of cloud computing represented an evolution away from on-premise infrastructure management, as it facilitated the implementation of new technologies, new processes and reduced costs. With cloud computing, companies can contract with a cloud service provider, like AWS or Google Cloud, and provision processing power, storage capacity and security resources without the need to develop, install, secure, maintain, or update these resources themselves. All this is the responsibility of the cloud provider.

Unlike older on-premise based models, which had to support a vast number of physical servers sitting in a temperature-controlled room with endless rows of server racks, first-generation cloud computing resources reduced the number of physical servers needed to serve a business by using containerized or virtualized resources, which can house a number of server instances and other services in a single physical server.

In addition, cloud technology also facilitates remote work models. Anyone with an Internet connection can access the platform around the globe and use all the available applications and tooling to manage their computing resources. Best of all, any modifications are applied and saved directly to the cloud.

Cloud Computing: Characteristics

In summary, we can say that cloud computing uses remote data centers and servers for large-scale data processing, analysis and transfer. In some cases, cloud services can also provide massive storage capacity as an additional feature. By providing virtualized computational resources on demand, this deployment makes infrastructure more elastic and scalable. You benefit from this using any of the three types of platforms that cloud technology offers:

  • Infrastructure as a Service (IaaS): companies lease processing (such as servers) and storage (such as data centers) resources from a third party.
  • Platform as a Service (PaaS): developers can write, deploy and manage applications, without worrying about resources, such as software and hardware.
  • Software as a Service (SaaS): refers to management tools and programs (such as CRM, ERP, administrative and accounting software, and others).

The Cloud in Everyday Life: Use Cases

Imagine a company that regularly works with a large amount of data, spreadsheets, documents, transactions and records. With the old model, software must be—either manually or automatically—installed on each individual server, machines have to be identified, upgrades need to be rolled out, users and groups need to be authenticated and authorized, specific servers and their supporting services must be assigned for data processing, and the team must define a way to keep the files updated and in the same place. And these are just a handful of costly operational activities that managers and their supporting staff need to run and maintain on an on-going basis.

The risk of relying on the standalone, non-distributed compute model is that if a server is compromised or damaged, valuable information could be lost, corrupted or stolen. Both the business and reputation of your company can be affected if an important document is lost or if an outdated report is sent to your client because no one knows which computer the most updated version was saved on.

In this context, the benefits of cloud computing can be perceived in different aspects:

  • Accessibility: you can be connected from any device to access the information. Anytime someone needs to view, edit, or update a document, they can do it, regardless of device type, location, or time. The files will always be available.
  • Organization: with cloud solutions, you can create a virtual space to store all your relevant information. When it is needed, everyone knows where to look for it.
  • Scalability: an increase in demands and requests to a cloud service doesn’t necessarily mean a bad performance. With virtualized resources available on demand, companies can quickly allocate more resources to prepare for access spikes like Black Friday events, or respond to surges in minutes to add more capacity.
  • Task automation: some cloud solutions allow you to automate certain tasks, especially related to data storage, processing, and transfer.
  • Large-scale data storage and processing: cloud computing has been key in the development of technologies such as Machine Learning, Artificial Intelligence and Big Data. Considering the cloud’s characteristics and the hyperscale data centers that are implemented to provide its services, it is easier for the cloud to handle the large amounts of data that this type of technology needs to function correctly.

What is Edge Computing?

Decentralization can be considered one of the chief characteristics of edge computing. According to the LF Edge’s Open Glossary of Edge Computing, edge computing can be defined as “the delivery of computing capabilities to the logical extremes of a network in order to improve the performance, operating cost and reliability of applications and services.” For this, equipment and infrastructure is geographically distributed, which allows it to be closer to end users. This architecture provides each demand with lower latency, since the data must travel shorter distances for processing. “By shortening the distance between devices and the cloud resources that serve them, and also reducing network hops, edge computing mitigates the latency and bandwidth constraints of today’s Internet, ushering in new classes of applications,” LF Edge explains.

With the number of connected devices increasing constantly, as well as users increasingly demanding better experiences while using applications and websites, companies must find a way to process and deliver their data in a highly efficient way. Edge computing appears like a good solution to this situation, distributing more resources between the centralized cloud data centers and the devices.

Edge Computing: Characteristics

Edge computing is a serverless technology. That means that the provider is responsible for the maintenance and administration of the infrastructure, while allocating resources in a dynamic way to meet the needs and demands of its customers.

Edge computing uses a decentralized and distributed architecture, providing lower latency, more reliability, more security and unlimited scalability compared to traditional cloud computing solutions. The edge enables real-time data processing, essential for time-sensitive and mission-critical applications. The sum of these factors is reflected in better performance while significantly reducing operating costs.

Wide and intelligent distribution also means greater and better scalability. In this scenario, you have more flexible resources to scale as needed, but it can also be done automatically without intensive resource management, eliminating the possibility of performance hiccups while reducing operational overhead.

By having different edge locations where the users can be connected, the network can route them automatically to the closest location, but also route them to a more efficient one in case of a traffic spike or if one of the servers is unavailable.

Edge Computing in Everyday Life: Use Cases

In a hyper-connected economy, brands and companies have changed the way they relate to and communicate with their customers; websites and applications enable this. Yes, it’s a more horizontal and direct relationship, but it’s also a hard one, considering customers are more demanding. Their experiences have to be perfect for them to stick around and, lastly, convert.

It’s a fact that faster sites and applications sell more. For example, “Amazon found that every 100 milliseconds of downtime cost them one percent in sales and Google found that an extra .5 seconds in search page generation time dropped site traffic by 20 percent”, as reported by IT Business Edge. Speed is key even for SEO, resulting in better positions in search engines for sites with superior speed, user satisfaction, and user experience. This context forces companies to look for new ways to optimize content delivery and has consequences for both parts of the equation: developers and customers.

In the report “Assess And Enhance Your Modern Application Delivery Journey”, Forrester explains “as the world moves to Modern Application Delivery (MAD), modernized application development and delivery (AD&D) teams release more frequently — quarterly (26% of global developer survey respondents), monthly (24%), weekly (11%), or even daily (6%) to keep up with customers’ and employees’ demands.¹” It seems like a lot of work and time go into planning, creating, coding, developing and deploying new products and solutions at a fast pace.

Nowadays, edge computing is emerging as a solution for this situation, thanks to its characteristics and the nature of its infrastructure. Building faster, more secure and scalable applications is easier with a serverless model. Besides, edge computing provides automation, observability, multilayer and zero-trust security, and integration with third-party solutions, simplifying application development and content delivery, while bringing the data closer to the user with its globally distributed network at the same time.

Developing edge applications helps to enhance your customer experience, and makes you more competitive in the market. Currently, we can observe how in industries such as e-commerce, video games, video streaming, healthcare, and finance, in which a fast and fluid response to the user’s or service’s request is crucial to ensuring a seamless, fast and smooth user experience, companies are already implementing edge computing solutions.

For example, lag time experienced while playing online has been minimized and data delivery has increased, improving real-time game play, reducing video jitter, providing faster screen painting, and enhancing the overall gaming experience. With the edge network looking to optimize data delivery to the last mile, it is also possible to watch an episode of a series or an entire movie without the frustration of service interruptions.

For e-commerce, computing power served from the edge can easily manage unexpected traffic peaks like Black Friday or the Christmas holidays with almost zero risk of your shopping platform going dark and offline. This is possible not only because of edge computing’s lower latency and speed, but its high level of scalability, as it distributes the demand in an intelligent and efficient way across the network, with no need for extra work from your team, because it’s done automatically. Network distribution ensures more edge locations where your users can be connected. The global result is a faster and frictionless experience for customers, ensuring lower abandonment, more converts and increased checkout speed.

So whether you are playing games, shopping online, streaming an original series or calling a colleague using video chat, you are probably using a service that already works with edge computing.

Beyond these, low-latency and efficient data processing are fundamental for the evolution of IoT, AI, VR/AR and hyper-automation, which will benefit from implementing solutions at the edge. In particular, use cases such as autonomous vehicles and smart houses have an array of sensors that capture, transmit and process a considerable amount of data every millisecond, from their environment and sometimes in real-time, so speed and reliability are key for machine learning, precise handling, contextual mapping and intelligent routing for self-driving and preventing accidents.

The future is on the edge, even for telecommunications. Deploying this computing model will enable using edge infrastructure for public and private 5G networks such as vEPC, MEC, Open Caching and other VNFs, which can be managed and optimized with its features for a better performance.

Cloud Computing vs. Edge Computing, The Dilemma

If we compare cloud computing and edge computing, we can establish some differences:

In contrast to the cloud model, collaboration and participation across different platforms and providers is another characteristic of edge computing that can help you boost your performance and reduce costs. Edge computing embraces an open architecture standard that allows for multi-cloud and hybrid cloud setups. This allows for interoperability between your system and the provider’s technology stack. Open standards also allow third-party solutions to integrate with the customer and provider solutions. This approach opens the possibilities to companies; guarantees compatibility for different resources, coding languages, and protocols; and minimizes the risk of vendor lock-in.

Today, data security has been elevated as a high priority for companies around the globe. Big data breaches, relentless DDos attacks, destructive malware and insidious ransomware have increased businesses at risk, stalled operations and tarnished the reputation of brands. The centralized model in cloud solutions deploys methods, such as credentials or two-step verification, to ensure only authorized users can access the platform and has an array of other defensive tools to prevent the lion’s share of attacks. However, the centralized model is not impervious to concentrated attacks and can still be compromised. One key drawback of the centralized model is that it has a single point of failure: the data center itself. Concentrated attacks to the data center can hinder network traffic and obstruct connections.

The decentralization that defines edge computing doesn’t necessarily mean less protection for your data. In fact, decentralization solves many of the limitations that centralized data centers possess. An edge computing provider can design a robust security plan with many layers of security. This can include network layer protections, WAF, DDoS preventions, bot mitigation, advanced authentication methods and a 24/7 monitoring of the network to detect vulnerabilities as well to identify and prevent any possible attack. In addition, with edge computing, the data processing can occur across many nodes and even on the devices themselves, increasing and improving data security and privacy.

Pricing methods are another differential between cloud computing and edge computing. With the cloud, you contract a plan of service, which includes a maximum capacity (for transfer, analyze, compute, process and storage data) to be used in a certain time period (monthly, semestral, yearly). If you need more resources, you need to upgrade your plan or pay the extra cost. Also, if you don’t use all the capacity offered by your provider, you lose money and waste these resources. Edge computing is based on a usage pricing model. You pay for what you use, with no payment for wasted idle time. This dynamic contract model adapts to every company’s needs, so you pay according to how much you use products and services, calculating the data transferred or processed with fixed fees. This way, it’s not mandatory to commit to any minimum use or contract term.

Deploying The Cloud is Good, But With The Edge, It’s Better

Undoubtedly, cloud computing was a large leap in the way companies approached the use of distributed networks, servers and complementary technologies that allowed them to advance in their digital transformation. However, some of its features were not enough to solve more critical situations, where response time, latency and availability of resources affect the user experience.

Edge computing is considered the best alternative to solve the problems and limitations of the cloud. According to Forrester, “edge computing brings computing close to the customer, so all the use cases that enable and influence customer behavior will be the first motivations for the edge. IoT will heavily drive use cases, but edge computing will go beyond these, from addressing on-demand compute to enabling real-time app engagements. Edge computing will augment cloud and on-premises to enable new customer experiences.²”

Considering it as the limit in the network, the experts think it’s natural that everybody eventually moves to the edge to guarantee efficient content delivery, low latency and better performance for building solutions and applications, thus creating more optimal experiences for users. Even though edge-based solutions are not very common these days, many industries are experimenting with them and reflecting on how they can be integrated into their technological architecture.

“Enterprises that have deployed edge use cases in production will grow from about 5% in 2019 to about 40% in 2024,” Gartner stated in its Forecast Analysis: CDN and Edge Services, Worldwide, in June, 2020³. This means that edge computing has a huge potential for growth and the prospect to have significant penetration in a few years, “as these projects demonstrate value and are deployed into production.”

For its part, the recently published 2021 report, the State of the Edge, considers edge computing a key factor in the “Fourth Industrial Revolution.” In the previous year, the 2020 report had already anticipated that more than $700 billion will be invested in edge computing in the next 10 years, including equipment, infrastructure and facilities related to its operation.

It is expected that advances in edge computing will continue and its adoption will become more and more popular. So, why wait until you are left behind if you can start to build with Edge Computing right now?

Azion’s Edge Platform

Azion’s Edge Platform is enterprise-grade, open, fully programmable, extensible and developer-friendly; this way, developers can build on their terms.

Our solution offers you all the advantages of moving your applications to the edge of the network:

  • Write and deploy serverless applications
  • Create zero-trust security architectures
  • Improve your content delivery experience
  • Build innovative IoT use cases
  • Low latency and real-time data analysis
  • Improved performance and security for your applications
  • Reduced costs

If you want to explore our platform, you can create a free account and use the $300 in credits we provide to start building your applications. If you have any questions, contact our Sales Team, who can help you choose the best services and products for your needs.


¹ Bieler, D., Chhabra N., Hopkins B., Kindness A., Pelino M., Pollard J., Staten J. & Sunil A. (2019). Predictions 2020: Edge Computing. Cambridge, MA: Forrester Research.

² Bieler, D., Chhabra N., Hopkins B., Kindness A., Pelino M., Pollard J., Staten J. & Sunil A. (2019). Predictions 2020: Edge Computing. Cambridge, MA: Forrester Research.

³ Chamberlin, T. & Medford, B. (2020) Forecast Analysis: CDN and Edge Services, Worldwide. Stamford, CT: Gartner.

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