The advent of Machine Learning (ML) and Artificial Intelligence (AI) technology has helped companies to push the boundaries of their apps to a great extent. While most of the tech giants are leveraging on AI to make path-breaking solutions, Amazon Web Services (AWS) has employed AI technology to make their internal procurement process much more robust and effective.
In a recent interaction at Pacific Science Center’s 14th Annual Foundation of Science Breakfast, Amazon Web Services (AWS) CEO Andy Jassay told that AWS is relying on AI to add the number of new servers required to meet the growing demand of cloud servers. He explained that artificial intelligence is playing a crucial role in anticipating the demand for its services. Not only it is helping AWS to meet the demand but also cutting down the cost of operations.
“One of the least understood aspects of AWS is that it’s a giant logistics challenge, it’s a really hard business to operate,” said Andy.
Considering the fact that adding servers is a time-consuming affair, by anticipating the accurate demand and keeping it deployed AWS is able to cater to direct consumers, partners and resellers.
Andy also told that, on daily basis, AWS is adding new servers to the network. This is clearly indicating at the scale AWS is growing.
The advancement in computing and exploded adoption of the Internet has spiked the demand for cloud servers. Companies are willing to keep their business on 24/7. Besides, their unprecedented interest in crunching accumulated data has created a demand for process specialised servers. Cloud-based Analytics Servers, Cache Servers etc. are high in demand.
The geographical demand for AWS is spreading across the world. The company is leaving no stone unturned to make the procurement process as easy as possible. Both, offline and online sales partners are selling AWS services, be it dedicated cloud server migration, reseller hosting, specialised cloud hosting or migrating & managing infrastructure on the cloud, round the clock. The AI-powered process help AWS to pick up signals its sales arm follow. Unlike consumer facing products, enterprise sales cycles are notoriously long and could end up straining the delivery mechanism.
Besides, tracking consumer behaviour on AWS has also helped the company understand the growing demand to a certain level.
“Most of the customers start slow with AWS, and then accelerate their usage as they see more benefits, which could lead to spikes in demand if they move faster than anticipated,” said Andy.
Therefore, Amazon uses a forecasting model powered with Machine Learning and artificial Intelligence that helps AWS to take capacity related decisions.
AWS is not only replying in AI for anticipating demand, it’s also leveraging on the technology to improve their support services. AI powered system is helping AWS to understand the maintain the capacity of components for its data centres, which are crucial during the time of any downtime.