The text delves into the design considerations for implementing a database throttler, comparing singular and distributed deployment models. A singular throttler acts as a centralized service that manages requests by accessing database and OS metrics directly, but it raises concerns about high availability and scaling. In contrast, a distributed throttler involves multiple instances, potentially across different availability zones, which can operate independently or collaborate by sharing metrics. The discussion also highlights the complexities introduced by separating metric collection from the throttler itself, such as through an API or agent, which can lead to issues with synchronicity and data staleness. The text explores the concept of reducing the throttler's impact on the system by controlling the frequency of metric collection and communication, suggesting strategies such as metric hibernation and efficient handling of replication lag. The challenges and trade-offs of each approach are examined, with a case study on the Vitess tablet throttler demonstrating a practical application of these principles.