Introduction to Edge and Hybrid Computing
If you are not living under a rock, you must have heard about Cloud Computing. For those who don't know, 'Cloud Computing' refers to computing done on servers stored somewhere else. It just means it will deliver computing services "over the internet," which will offer boosted infrastructure and resources and reduce the cost of using an entire-fledged server. You pay for what you use.
There are multiple types of cloud computing, but that is not what we will discuss today. In this blog, we are going to know about different use cases of Edge and Hybrid computing. So without further ado, let's get started!
What is Edge Computing?
Before understanding Edge Computing, we must first understand the words that make it, i.e., Edge and Computing.' Edge refers to the geographic distribution, and Computing refers to the processes running in an environment. So, Edge Computing is computing that is done near the data source. It focuses on bringing the computation closer rather than relying on the data centre far from the data source. It will bring the cloud nearer to you.
What are the Benefits of Edge Computing?
Significant advantages of Edge computing are:
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Latency: Latency refers to the time it takes to send data between two points on the network. Communication takes place at the light's speed, but large physical distances in addition to network blockage or disruption can delay data movement across the web. This reduces the ability of a system to respond in real-time. So, what edge computing does is lessen the Latency to its minimum and its ability to process and store data faster, enabling more efficient real-time applications critical to companies.
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Bandwidth: Bandwidth is the sum of data that a network can carry over time. All networks, including wireless communication, have limited bandwidth. This means that there is a cap on the amount of data and the number of devices that can communicate across the network. Although it is possible to increase network bandwidth to add more devices and data, the cost factor is enormous. Almost any technology that applies to the latency problem applies to the bandwidth problem.
Edge computing makes smarter decisions concerning bandwidth and will only allow the traffic, which is useful for computing. Edge computing does the compute work on-site, sometimes on the edge device itself. The amount of the data to be sent can be reduced significantly by processing data locally, which requires far less bandwidth or connectivity time than might otherwise be necessary.
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Cost: Edge computing helps minimize bandwidth use and server resources. Cloud resources are finite and cost money.
What are the use cases of Edge Computing?
- IoT Devices: Devices that connect to the Internet are called Smart devices. They can benefit from running code on itself rather than in the cloud for more efficient user interactions. For example, Facial recognition scan in Apple devices stores the data mobile-only rather than on servers which helps users unlock the device faster.
- Self-Driving Cars/Transportation: Autonomous vehicles need to react in real-time without waiting for instructions from a server. Edge computing can help because self-driving cars require a lot of data that needs to be processed faster. So, installing a device in the vehicle rather than on servers can broadly impact AI's decision-making ability.
- Improved Healthcare: The healthcare industry has been expanding and moving towards technology, and the amount of data collected from devices of patients, sensors, and other medical equipment is enormous. That enormous data volumes require edge computing to apply automation and analytics to access the data, ignore the unimportant data, and identify the problem that patient might be having or can have shortly with the use of that data. Doctors can prescribe medication and take immediate action to help patients avoid health incidents in real-time. For example, the Apple watch showed data to its owner that you might have a possibility of heart attack and you need to seek medical assistance immediately, which turned out to be true. So, improving healthcare can be done through Edge devices.
- Network Optimization: Edge computing can help enhance network utility by determining performance for users over the Internet and then applying AI to determine the most reliable, low-latent network path for the user's traffic.
What is Hybrid Computing?
A Hybrid Cloud is a combination of the public cloud service combined with a private cloud. The goal is to combine the services and data from different cloud models to create an automated, unified, and well-managed computing environment.
Combining public services with the private clouds and the data centre as a hybrid is the new definition of corporate cloud computing. A hybrid cloud is the environment where the private and public services are used together to create value. A hybrid cloud is a mix of both private and public clouds. Having the ability to move workloads between private and public clouds gives the flexibility to meet the need in computing, cost, and performance requirements.
What are the Benefits of Hybrid Cloud Computing?
Improved Scalability and Control: A hybrid cloud environment gives organisations massive control over their data. As businesses evolve every second and the demand for IT services fluctuates, the hybrid cloud allows organisations to scale their workloads accordingly.
Increased Agility and Innovation: The potential to respond automatically to changes is crucial for innovation and competition. A hybrid cloud model helps organisations grow their stronghold by optimising IT performance and providing the swiftness needed to meet changing business demands. Companies with a hybrid cloud are not limited to their private on-premise infrastructure; they can easily expand their infrastructure to the cloud and quickly test, prototype, and launch new products.
Security: Data is an organisation's most valuable asset, and protecting it is a much more significant task than it seems. The public cloud has a much more open environment than a private cloud and is more susceptible to cyberattacks. Organisations that have sensitive data can store it in their private cloud. Though data still needs to be transmitted to the public cloud for analytics, an extensive encryption method can be implemented to remain as secure as possible.
What are the use cases of Hybrid Computing?
High Availability and Disaster Recovery (DR): In HA and DR, the IT team needs to replicate their on-prem infrastructure implementations in the cloud. If the functioning in "on-prem" data centres is disrupted, then applications could fail over to the cloud and continue to run without disrupting the users. The hybrid cloud can also be constructed for High Availability. Enterprises must use load balancers that distribute traffic between on-premises and cloud environments as required.
Cloud as Data Centre Extension: In this use case, the cloud can provide extra support while on-premises handles the primary data. This use case is widely used in the healthcare sector. For example, patient monitoring is dealt with on-prem to prevent latency issues. Cloud can act as a back-end server, which collects all the data from monitoring patients and can be integrated with other large data sets to support advanced diagnostics.
In this blog, we discussed edge computing and its various use cases and hybrid computing and its different use cases. Finally, we decided which type of computing is best suited for which organisation and how Xenonstack can help you. So, you will know where to look whenever you choose to pursue any computing!
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