  gRPC is at the heart of modern distributed system architectures. Based on
HTTP/2 and Protocol Buffers, it provides highly performant, standardized, and
polyglot communication across loosely coupled microservices and is increasingly
preferred over REST- or GraphQL-based service APIs in practice. Despite its
widespread adoption, gRPC lacks any advanced privacy techniques beyond
transport encryption and basic token-based authentication. Such advanced
techniques are, however, increasingly important for fulfilling regulatory
requirements. For instance, anonymizing or otherwise minimizing (personal) data
before responding to requests, or pre-processing data based on the purpose of
the access may be crucial in certain usecases. In this paper, we therefore
propose a novel approach for integrating such advanced privacy techniques into
the gRPC framework in a practically viable way. Specifically, we present a
general approach along with a working prototype that implements privacy
techniques, such as data minimization and purpose limitation, in a
configurable, extensible, and gRPC-native way utilizing a gRPC interceptor. We
also showcase how to integrate this contribution into a realistic example of a
food delivery use case. Alongside these implementations, a preliminary
performance evaluation shows practical applicability with reasonable overheads.
Altogether, we present a viable solution for integrating advanced privacy
techniques into real-world gRPC-based microservice architectures, thereby
facilitating regulatory compliance ``by design''.
