On July 26, a packed Javits Center gathered to hear keynotes and sessions billed as “The cloud event for everyone.” I attended the AWS Summit and I’ll share my key takeaways – all focused on AI in some form. Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, delivered the keynote.
Most of today’s organizations are going through a digital transformation process, where they’re updating their technology, integrating IT systems, and taking advantage of edge computing. At the same time, organizations are dealing with limited resources, the challenges of old technology, and the need to keep their infrastructure stable and manageable.
Businesses have been transitioning to cloud computing for the better part of the past two decades, and during that time, cloud has gone through many evolutionary phases.
At the turn of the century, “cloud” referred to hosted services where business would deploy their technology in a third-party data center. This evolved to co-location services, which lead to the multi-tenant solutions we have today. The commonality between these is they are all centralized compute models.
Since the birth of computing, networks have evolved alongside compute architecture. From mainframes to client servers to branch office computing, networks have had to keep pace by undergoing their own evolutionary processes. Today, compute has become highly distributed and that’s driving yet another major shift: to remain effective, networks now must be distributed.
Today’s high focus on customer experience is prompting many businesses to modernize their contact centers. As companies shift their communications to the cloud, it creates several challenges that did not exist when the contact center platform was on-premises. Smaller businesses are likely to purchase the telecom services directly from a contact center as a service (CCaaS) provider, but that’s not typically an option for large businesses.