{"dataset":{"id":"00000000-0000-0000-0000-000000000045","slug":"grpc-best-practices","name":"gRPC best practices","description":"Source-linked guidance on gRPC fundamentals: protocol buffer service definitions, the four RPC types, deadlines, error status codes, and performance practices. Scoped to gRPC core concepts; not a language-specific tutorial corpus.","visibility":"public","version":1,"documentCount":5,"publisher":"Koskamo editorial","license":"Original summaries; linked sources retain their own terms.","reviewedAt":"2026-10-04T00:00:00.000Z","readOnly":true,"createdAt":"2026-10-04T00:00:00.000Z","updatedAt":"2026-10-04T00:00:00.000Z"},"total":5,"documents":[{"title":"Performance best practices","sourceUrl":"https://grpc.io/docs/guides/performance/","text":"Always re-use stubs and channels when possible, and use keepalive pings to keep HTTP/2 connections alive during periods of inactivity so initial RPCs start without delay — for example the C++ channel argument GRPC_ARG_KEEPALIVE_TIME_MS. Use streaming RPCs for a long-lived logical flow of data in either or both directions: streams avoid continuous RPC initiation, which includes client-side connection load balancing, starting a new HTTP/2 request at the transport layer, and invoking a user-defined method handler on the server. However, streams cannot be load balanced once started and can be hard to debug when they fail, and they may help at small scale while reducing scalability — use them only when they provide substantial benefit, to optimize the application rather than gRPC itself. Each connection also limits concurrent streams, and excess RPCs queue in the client; high-load applications can create a separate channel per area of high load or use a pool of channels with distinct channel args. Note the streaming guidance does not apply to Python, where streaming RPCs are much slower than unary. Scope: gRPC. Reviewed October 4, 2026.","id":"grpc-best-practices:Performance best practices","version":1,"createdAt":"2026-10-04T00:00:00.000Z","updatedAt":"2026-10-04T00:00:00.000Z"},{"title":"Status codes and error handling","sourceUrl":"https://grpc.io/docs/guides/error/","text":"When a gRPC call completes successfully the server returns an OK status; on failure, gRPC returns one of its error status codes with an optional string error message, and this standard error model is supported by all gRPC client and server libraries independent of the data format. Common codes include CANCELLED when the client application cancelled the request, DEADLINE_EXCEEDED when the deadline expired, UNIMPLEMENTED when the method is not found on the server, UNAVAILABLE when the server is shutting down or the connection breaks after some data was transmitted, UNKNOWN when the server threw an exception, RESOURCE_EXHAUSTED when flow-control resource limits are reached, and UNAUTHENTICATED when credentials fail. With protocol buffers you can adopt the richer error model developed by Google, which carries extra error details as one or more protobuf messages in trailing metadata and is supported in the C++, Go, Java, Python, and Ruby libraries. Weigh it carefully: proxies and loggers cannot see the details, large detail payloads can hit protocol limits, and the grpc-core library will likely never support it. Scope: gRPC. Reviewed October 4, 2026.","id":"grpc-best-practices:Status codes and error handling","version":1,"createdAt":"2026-10-04T00:00:00.000Z","updatedAt":"2026-10-04T00:00:00.000Z"},{"title":"Deadlines and timeouts","sourceUrl":"https://grpc.io/docs/guides/deadlines/","text":"A deadline is a point in time past which a client is unwilling to wait for a response; some language APIs instead take a timeout, a maximum duration, which is converted to a deadline by adding it to the current time when the call starts. By default gRPC does not set a deadline, so a client can end up waiting effectively forever — always set a realistic deadline explicitly, starting from an educated guess based on network latency and server processing time, validated by load testing. Once the deadline passes, the client fails the RPC with the DEADLINE_EXCEEDED status, and the server automatically cancels the call with the CANCELLED status; the server application remains responsible for stopping any activity it spawned, so long-running work should periodically check whether the initiating RPC was cancelled. When your server calls another server, propagate the deadline to the outgoing RPC: some implementations do this by default (Java, Go) and others require explicit enabling (C++). gRPC converts the propagated deadline into a timeout with elapsed time already deducted, which shields the system from clock skew between servers. Scope: gRPC. Reviewed October 4, 2026.","id":"grpc-best-practices:Deadlines and timeouts","version":1,"createdAt":"2026-10-04T00:00:00.000Z","updatedAt":"2026-10-04T00:00:00.000Z"},{"title":"The four kinds of RPC","sourceUrl":"https://grpc.io/docs/what-is-grpc/core-concepts/#rpc-life-cycle","text":"gRPC lets you define four kinds of service method. Unary RPCs are the simplest: the client sends a single request and gets a single response back, just like a normal function call. Server streaming RPCs return a stream in response to one client request; the client reads from the returned stream until there are no more messages, and gRPC guarantees message ordering within an individual call. Client streaming RPCs let the client write a sequence of messages over a stream, then wait for the server to read them and return its single response, again with ordering guaranteed. Bidirectional streaming RPCs give both sides a read-write stream; the two streams operate independently, so client and server can read and write in whatever order they like — waiting for all client messages before responding, or alternating a read and a write in ping-pong fashion — while the order of messages in each stream is preserved. Choose the simplest kind that fits the data flow; preferring unary unless a message sequence is genuinely needed is Koskamo editorial guidance. Scope: gRPC. Reviewed October 4, 2026.","id":"grpc-best-practices:The four kinds of RPC","version":1,"createdAt":"2026-10-04T00:00:00.000Z","updatedAt":"2026-10-04T00:00:00.000Z"},{"title":"Service definitions with protocol buffers","sourceUrl":"https://grpc.io/docs/what-is-grpc/core-concepts/#service-definition","text":"gRPC is based around defining a service: specifying the methods that can be called remotely with their parameters and return types. By default gRPC uses protocol buffers as the Interface Definition Language (IDL) for describing both the service interface and the structure of the payload messages, though other alternatives are possible. A service is declared in a .proto file, for example service HelloService { rpc SayHello(HelloRequest) returns (HelloResponse); }, with each message defined field by field. Starting from that definition, gRPC provides protocol buffer compiler plugins that generate client- and server-side code: on the server side you implement the methods declared by the service and run a gRPC server whose infrastructure decodes requests, executes the methods, and encodes responses; on the client side a local object known as a stub implements the same methods and wraps parameters in the appropriate protocol buffer message type. Treating the .proto definition as the single source of truth that both sides generate from is Koskamo editorial guidance. Scope: gRPC. Reviewed October 4, 2026.","id":"grpc-best-practices:Service definitions with protocol buffers","version":1,"createdAt":"2026-10-04T00:00:00.000Z","updatedAt":"2026-10-04T00:00:00.000Z"}]}