One service publishes an order status; another consumes it. A field is renamed, a type is tightened and both applications pass their own tests. After deployment, fulfilment stops understanding some messages. Someone proposes gRPC so contracts can no longer break by accident.
That is an understandable reaction. gRPC lets teams define service methods and messages in advance, commonly using Protocol Buffers, and generate typed clients and server interfaces. But a well-typed interface is not a guarantee that two independently deployed systems always remain compatible.
What becomes more explicit
Instead of agreeing vaguely to “send an order object”, the team publishes a definition of the service: available methods, request types, response types and fields. Developers working in different languages can generate interfaces from a shared schema.
This catches some mistakes earlier and makes the contract easier to review before implementation. It cannot define the business meaning by itself. A field called “confirmed” does not establish whether an order has been paid for.
Protocol Buffers identify fields with numbers. Safe evolution means respecting the compatibility rules for existing numbers, avoiding arbitrary reuse of deleted fields and treating semantic changes as real contract changes. An apparently valid schema can still break a business flow if the meaning of a message changes. The gRPC introduction explains its service-definition approach.
Remote calls can still fail
A gRPC method is still a network call. The server may be unavailable, a response may arrive late, or the connection may disappear. Clients need deadlines, considered retry policies and an explicit way to handle an unknown operation result.
Suppose the method reserves inventory. If the caller times out, the reservation may already exist. Generated client code does not stop a retry from reserving twice. That needs a stable business operation identity or another safe retry mechanism.
Nor does choosing gRPC automatically make a slow service fast. Its binary messages and streaming support can be useful, but database queries, business logic and downstream services often determine overall latency. Measure the real bottleneck before changing transport.
Streaming is useful when the product needs a stream
gRPC supports methods that send multiple messages within a call, including client, server and bidirectional streaming. That may fit continuous updates or high-frequency internal communication better than repeated polling.
It also introduces questions about broken connections, recovery positions, duplicated updates and how long the receiver can wait. Those are worth solving for a genuine streaming workflow, not for a simple request to fetch one order.
An internal protocol need not be the public API
Browsers often need an additional approach, such as gRPC-Web with suitable proxy support, to consume gRPC-based services. External partners may prefer a plain HTTP/JSON API. Using different protocols at different boundaries is a reasonable product decision.
I would begin with the history of actual integration failures. Which changes were incompatible? Would schema checks or consumer contract tests have caught them without a migration? If teams keep changing the business meaning of fields without agreement, a different protocol simply gives them a new place to make that mistake.
gRPC earns its place when explicit service contracts and the communication model reduce real coordination costs. It does not remove ownership of compatibility, network failures or business outcomes.