AI to Revolutionise Cloud Networking: Here is how

Artificial Intelligence is revolutionising every aspect of the tech industry, including Cloud Networking

As more and more AI workloads enter the Cloud, the ability to “deliver better Cloud Networking solutions will become a key priority. “, according to ITPro Today

The information for this blog was sourced from ITPro Today’s website. You can read the full story here

Here are some of the key questions answered:

1 Will AI have an impact on Cloud Networks?

For AI to work to its full potential, it will require “unprecedented levels of performance from cloud networks.”

Data will need to be shared between remote servers and Cloud Networks will provide the essential link to enable the sharing of information. For the simplest of AI models to work, terabytes of data will need to be accessed at low latency rates.

Therefore, “networks will need to be able to support very high bandwidth with very high levels of performance.”

2 Is Cloud Networking ready for AI?

Cloud vendors have traditionally been able to offer solutions to help with network performance. There are many ways of boosting networking speeds for Cloud Networking including “direct connect networking services” and using the “hybrid cloud model”.

This may not apply to all AI workloads that require “exceptional network performance needs”. Other solutions may be required which include data processing units (DPUs). Companies such as Nvidia are already investing in this technology.

3 What to expect from Cloud Networking in the future?

Here are three predictions for the future:

1. Greater use of direct connects- In the past, big companies mostly used direct connect services for their complicated cloud setups and fast needs. But now, smaller businesses might start using them too to make the most of cloud-based AI workflows.
2. Higher egress costs- When data moves out of cloud networks, providers often charge fees called “egress” fees. AI tasks in the cloud might raise the fees that businesses pay for egress. In the future, being able to predict and control these charges caused by AI tasks will be crucial for saving money on cloud costs.
3. Fluctuating network consumption- Certain AI tasks in the cloud will use a lot of network resources for a short time, like when they’re training and moving large amounts of data. After training, they’ll use less network resources. So, being able to handle big changes in network use will be important for managing cloud network performance.