At Netflix, we heavily use gRPC for the purpose of backend to backend communication. When we process a request it is often beneficial to know which fi

Practical API Design at Netflix, Part 1: Using Protobuf FieldMask

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2021-09-26 15:30:08

At Netflix, we heavily use gRPC for the purpose of backend to backend communication. When we process a request it is often beneficial to know which fields the caller is interested in and which ones they ignore. Some response fields can be expensive to compute, some fields can require remote calls to other services. Remote calls are never free; they impose extra latency, increase probability of an error, and consume network bandwidth. How can we understand which fields the caller doesn’t need to be supplied in the response, so we can avoid making unnecessary computations and remove calls? With GraphQL this comes out of the box through the use of field selectors. In the JSON:API standard a similar technique is known as Sparse Fieldsets. How can we achieve a similar functionality when designing our gRPC APIs? The solution we use within the Netflix Studio Engineering is protobuf FieldMask.

Protocol Buffers, or simply protobuf, is a data serialization mechanism. By default, gRPC uses protobuf as its IDL (interface definition language) and data serialization protocol.