A poorly designed SaaS architecture creates limitations in setting the pricing strategy for the offerings and impacts new customer acquisition. Conversely, a good architecture sets the appropriate pricing model and accommodates special architecture-design requirements, while enabling scalability and customizability.
Enterprises facing high cloud costs are taking a more balanced look at where workloads should reside and considering repatriation to a cloud in their own data center or fully managed on Edge locations.
In the age of burgeoning data complexity and high-dimensional information, traditional databases often fall short when it comes to efficiently handling and extracting meaning from intricate datasets. Enter vector databases, a technological innovation that has emerged as a solution to the challenges posed by the ever-expanding landscape of data.
Migrating to the cloud has long been seen as a way for organizations to save money. The whole point of implementing this practice, after all, is to reduce operational costs. But these promised savings from migrating workloads to the cloud have failed to appear. In fact, many face the opposite problem: surging costs.
Companies have started leveraging advances in networking, algorithms and edge computing to run artificial-intelligence workloads outside of data centers and closer to where applications are being put to use.