Abstract: Embodiments of the present disclosure provide improved data observability mechanisms. Specifically, embodiments provide for managing event-structured observability data in a federated network and database platform. The improved mechanisms enable improved analysis of data-driven errors and/or storage of associated data for purposes of data observability processing actions and/or rendering for user analysis. Example embodiments are configured for receiving a data stream representing operational engagement of an event-structured service hosted by the federated network and database platform. Some example embodiments are further configured for generating event-structured observability data from the data stream utilizing an event processing pipeline. The example embodiments are further configured for storing the event-structured observability data in at least one event-structured observability data repository of the federated network and database platform.

Abstract: Embodiments of the present disclosure provide improved data observability mechanisms. Specifically, embodiments provide for managing event-structured observability data in a federated network and database platform. The improved mechanisms enable improved analysis of data-driven errors and/or storage of associated data for purposes of data observability processing actions and/or rendering for user analysis. Example embodiments are configured for receiving a data stream representing operational engagement of an event-structured service hosted by the federated network and database platform. Some example embodiments are further configured for generating event-structured observability data from the data stream utilizing an event processing pipeline. The example embodiments are further configured for storing the event-structured observability data in at least one event-structured observability data repository of the federated network and database platform.

Abstract: Systems and methods provide techniques for dynamic rate-limiting, such as techniques that utilize one or more of asynchronous rate-limiting, context-aware rate-limiting, and cost-aware rate-limiting. In one example, a method for asynchronous rate-limiting includes the steps of receiving a rate-limiting request for a service application; extracting one or more policy-defining parameters from the rate-limiting request; querying a local cache storage medium associated with the rate-limit decision node to identify one or more local rate-limiting policies associated with the rate-limiting request; determining, based on the one or more policy-defining parameters and the one or more local rate-limiting policies, a rate-limiting decision for the rate-limiting request; and transmitting the rate-limiting decision to the service application in response to the rate-limiting request.

Abstract: Systems and methods provide techniques for dynamic rate-limiting, such as techniques that utilize one or more of asynchronous rate-limiting, context-aware rate-limiting, and cost-aware rate-limiting. In one example, a method for asynchronous rate-limiting includes the steps of receiving a rate-limiting request for a service application; extracting one or more policy-defining parameters from the rate-limiting request; querying a local cache storage medium associated with the rate-limit decision node to identify one or more local rate-limiting policies associated with the rate-limiting request; determining, based on the one or more policy-defining parameters and the one or more local rate-limiting policies, a rate-limiting decision for the rate-limiting request; and transmitting the rate-limiting decision to the service application in response to the rate-limiting request.