Authors: Boris Zibitsker & Alex Lupersolsky (BEZNext)
AI agents are rapidly changing enterprise computing. However, unlike traditional applications, they do not follow a fixed path. Instead, an agent interprets intent, builds a plan, and calls different tools dynamically for every request. Consequently, this makes system behavior very hard to predict. As a result, cloud costs and processing delays can spike suddenly.
For instance, traditional monitoring tools only tell you what went wrong after it happens. Therefore, they cannot help you predict future budgets or find hidden bottlenecks. To solve this, our white paper offers a better approach. Specifically, it explains how observability automation acts as a foundation to control costs and improve speed