Edge vs. cloud: Which computing technology is for you?
Over the past few decades, a lot of processing has moved from the edge to the cloud. Processing and storing data in the cloud provides many benefits, but developers are realizing the value of edge computing in many use cases, especially as the IoT landscape matures. Most businesses don’t need to choose one or the other exclusively — in fact, edge and cloud often work in tandem to create the best solution.
In this post, we’ll take a closer look at edge computing and cloud computing, the pros and cons of each, and how they can work together in IoT use cases.
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What is edge computing?
Edge computing brings the computing process as close as possible to the data source. Taking this approach reduces latency and allows for reduced bandwidth usage. With the advent of large-scale IoT applications that involve millions of devices and reams of data, edge computing can save companies considerable time and data costs. For example, a smart factory that’s equipped with many IIoT sensors attached to machines and robots on the floor might utilize edge computing to pre-process all that inflowing data, running analytics on a local machine, and only sending specific reports — rather than all the raw data — to the cloud.
Recommended reading: Edge Computing and IoT
Pros of edge computing
Let’s look at some of the pros of edge computing:
Because data stays onsite rather than being transferred to a remote server, the transmission time is cut, allowing for faster processing.
Since edge computing only deals with local networks, there are fewer chances for things to go wrong, and events on the other side of the world are less likely to have an impact. In many cases, such as the smart factory use case example, data collection and processing can continue even if there’s an interruption in the internet connection.
Data that stays on-site is less likely to be compromised because there are fewer points of vulnerability in its journey.
Edge computing eliminates the “as-a-service” costs that come with transferring and storing all your data on cloud servers.
Scaling up your operation becomes simpler when you do not have to rent larger and larger remote servers to store data.
Cons of edge computing
Now let’s take a look at some of the drawbacks of edge computing:
1. Edge-specific security threats
While you have tighter security if your data is not traveling the globe, that also means it’s your responsibility to provide adequate security against hacking on local servers.
2. Infrastructure cost
This may not be a concern if you are working from a location with a great internet infrastructure. But if you must build up that infrastructure yourself, it could be a costly investment.
3. Stable power supply
Computing is more centralized in edge computing, leaving you more susceptible to local disruptions. A power outage, for example, could have a much greater impact. This is why your physical location is important in edge computing.
4. Hardware location
Since it’s all local, you have to store and monitor the physical hardware involved, ensuring local server rooms are operating and reliable.
What is cloud computing?
Cloud computing involves sending data from local devices to remote servers for storage and processing. With cloud computing, you access storage, applications, and most other functionality found in a computer system via the internet. In essence, it’s a “virtual” computer that can incorporate processing power from hardware all over the world via the internet. To use a cloud computing approach with your IoT devices, you need to rent space on a server. Cloud services come in a number of forms:
- Software as a service (SaaS) are applications that run in the cloud.
- Platform as a service (PaaS) provides all aspects of a computer system, from databases to storage to networks via the cloud.
- Infrastructure as a service (IaaS) is like PaaS, but takes a “pay as you go” model, so it’s very scalable.
Let’s take a look at a few of the most common cloud providers:
- Amazon Web Services (AWS) is one of the most well-developed on-demand cloud computing platforms out there. It’s available to governments, businesses, and individual subscribers and takes a pay-as-you-go payment structure.
- Microsoft Azure runs the entire Office suite on the cloud as well as providing PaaS and IaaS.
- Google Cloud is not quite as large as its competitors, but it excels in areas such as machine learning and advanced analytics.
- IBM Cloud is much smaller but still offers most of the same services the others do — and includes Watson AI, a question-answering computer system.
- Oracle Cloud has become the go-to service for data management, providing storage, applications, and services on demand through the company’s global network of servers
Recommended reading: Cloud computing and IoT
Pros of cloud computing
Let’s look at some of the pros of cloud computing:
Because computing takes place on machines that are remote, you can hire services only for data you need to be processed. For example, you might have massive demands in January but very little in February — but with cloud services on a pay-as-you-go model, that fluctuation is not a problem.
Because cloud servers are remote, you can access all the data and processing power you need from mobile devices.
3. Insight and Analytics
Most cloud services include built-in data analytics functionality, allowing you to track big data without needing to invest in the often expensive software needed.
Recommended reading: What’s the relationship between IoT and big data?
With so many people working from home these days, having a centralized system allows remote teams to access data and work together more easily.
5. Quality control
When everyone is working from the same files and storage, it cuts back on human error.
Cons of cloud computing
Now let’s look at a few cons of cloud computing:
If your entire system depends on an internet connection to provide access to cloud services, productivity comes to a screeching halt whenever your connection is interrupted.
2. Security and privacy
While well-respected cloud services provide security and privacy assurances, as soon as you are storing data on outside servers, it’s no longer only in your hands — and you are taking an inherent risk.
3. Vulnerability to attack
With cloud computing, all your data is streamed to the internet, creating additional points of vulnerability to cyber attacks.
4. Slow backup and restore
Since all the data is remote, uploading large files takes considerably longer than it would on local drives. When considering a cloud-only solution, think about the amount of data you will need to send and receive regularly.
5. Vendor lock-in
Just like being locked into a cell phone plan, it is very hard to change IaaS service providers once you are enmeshed in a system.
Is cloud computing or edge computing right for your business?
In most situations, cloud computing and edge computing are not mutually exclusive. Many use cases work best with a blending of the two, especially where IoT sensors are involved. For example, an industrial site might have some edge computing servers on-site to harvest data, carry out initial processing, and decide what to send on to the cloud. The cloud servers then store that data and allow remote managers to access and analyze it along with similar information from other company sites, giving them visibility into productivity and driving increased efficiencies.
The connection between cloud computing, edge computing, and IoT
As noted, most IoT deployments work best when relying on a combination of cloud and edge computing. Let’s look at a few use case examples of how these complementary technologies work together to help projects run efficiently and meet with success:
Smart home IoT products can provide homeowners with increased control and insights around utility usage, home security, and more. A smart security system might process data from video cameras and motion sensors locally, allowing for quicker alerts when a breach is detected — and avoiding potential security vulnerabilities that might arise if all the data is passed on to a third-party server. The system may still utilize a cloud service to send and store periodic reports and updates.
When satellites gather images of earth and space, they do some of the processing and analysis right on board — at the network edge. Once processed, the images are sent back to cloud servers on earth, utilizing a blend of edge and cloud computing to achieve their goals.
In smart utilities use cases, connected IoT devices are typically deployed inside water and power meters. These sensors often have limited processing power and capability and may be battery-powered. They send data to local smart grid servers, which provide computing power near the edge to aggregate and pre-process the sensor data. Once processed, select data and reporting are sent to cloud servers where utility companies can utilize it to identify trends in power usage and make decisions about rates and services.
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