Edge computing is a new term used to define localized cloud infrastructure technology services. Whereas the majority of cloud network infrastructure services are located away from the user, edge computing aims to bring the cloud closer to home.
One of the more significant issues with cloud infrastructure technology services is that the server you are connecting to can be located anywhere in the world. If you are in the country of origin, then this issue doesn’t apply; but for those in different geographic locations, this can result in high latency and security worries due to varying laws in different countries across the globe.
To explain it simply, edge computing aims to offload some aspects of server operation to hardware in or near to the home or workplace. Instead of connecting to a remote server, the same functionality can be achieved through a single on-site server or even through ‘Internet of Things’ devices. Let us discuss why edge computing is the next step in cloud computing.
Let’s look at four benefits that are most prevalent for those advocating to move their global infrastructure services to edge computing: Reliability and Speed, Security, and Versatility.
Reliability and Speed – The first significant advantage of edge computing is its locality to the user. Edge computing aims to bring the servers closer to the devices connecting to it.
First off, this is beneficial in terms of latency. With servers being closer to connecting hardware, there is less distance for packets of data to travel. Edge computing, coupled with the increasing use of fiber optic cabling means that latency is a much smaller issue than it was before.
This enables the use of performance-reliant programs such as virtual desktop network infrastructure services in the cloud. IT service management consultant firms would agree that these VDI solutions would have traditionally been confined to use on a private cloud due to the declining usability over high latency connections. These latency reductions mean it is entirely possible to omit the need for private clouds and fully migrate to global infrastructure services offered on the public cloud. This saves companies time and money in the long term.
Security – The next advantage of edge computing is its improved security for infrastructure technology services, which is a heavy focus for IT service management consulting firms. Traditional cloud computing is burdened by being incredibly centralized, meaning that massive data centres are susceptible to things like network outages and attacks over the network, something of which IT service management companies actively try to avoid.
If a service has all of its computing hardware in one location, this can render the service unavailable if network connections drop out. By distributing the processing power across multiple geographical locations, this can reduce the risk of complete outages. If these smaller server clusters do run into downtime, they can also re-route all of their traffic to other locations, offering a necessary fallback.
This also means that less data is collected together in a single location on a network. If a network were accessed with malicious intent, there would be less information to abuse thanks to the server having a much smaller proportion of the total data on it. Many IT service management consulting firms would agree that with less bandwidth being routed to these locations, it also means that less data can be intercepted and misused, making for more secure IT service management solutions with edge computing.
Versatility – The third, and arguably most important benefit of edge computing, is its versatility compared to traditional cloud infrastructures.
Many edge computing IT service management solutions have the infrastructure already available for companies to take advantage of in different geographical locations. This dramatically reduces the time needed to implement networks, as well as the cost in purchasing hardware and space for the hardware.
This has been found to significantly improve streaming service quality, where latency can play a massive part in reducing the performance of these services. This also translates over to any high bandwidth cloud-based services, whereby high latency and interruptions to connections can result in a reduction of perceived usability to the user. Bringing these servers closer to home means that data can be transmitted more quickly, and any lost data can be requested again more quickly as well, eliminating buffering.
Using edge networks to deliver content, while feeding analytical data back to more centralized network infrastructure for analysis by AI and Machine Learning algorithms, can result in the best of both worlds for IT service management companies looking to ensure optimum efficiency of their network infrastructure services. It also means that sensitive data is accessed less frequently, and is, therefore, more secure.
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