gRPCをRESTや他の代替手段より選ぶべき時

Quick Decision Tree: Which to choose? Public APIs / external clients → REST (simple, widely compatible). Internal service-to-service (microservices) → gRPC (typed, fast, low-latency). Streaming data pipelines → gRPC streaming or SignalR (depending on consumer type). Frontend-heavy apps (Blazor/React) → GraphQL if you want client-driven queries; otherwise REST with projections is simpler. Real-time dashboards, chat, trading feeds → SignalR/WebSockets . Data-heavy querying → consider OData or GraphQL for flexible filters. ✅ My Recommendation for .NET 9: Use REST at the edges (public endpoints, B2B). Use gRPC for internal service-to-service calls between projects (AppHost, backends, workers). Consider GraphQL if your frontends need flexible data shaping. Add SignalR for real-time streaming to browsers . 1. Core Concepts 1.1) REST (Representational State Transfer) Transport: HTTP/1.1 (can also run on HTTP/2/3). Format: Typically JSON (but can be XML, HAL, etc.). Style: Resource-oriented, CRUD-like verbs ( GET/POST/PUT/DELETE ). Strengths: Simple, universally understood, widely supported by tooling. Works well for public APIs and external consumers. Weaknesses: Over-fetching/under-fetching (fixed DTOs). Less efficient serialization compared to binary protocols. No native streaming (must fake it with chunked responses, SignalR, or SSE). 1.2) gRPC Transport: HTTP/2 (HTTP/3 support coming in .NET 9). Format: Protocol Buffers (binary, compact, schema-driven). Style: RPC (Remote Procedure Calls), proto-first design. Strengths: Low latency: Binary serialization and multiplexed HTTP/2 streams reduce overhead. Strong typing: Proto schema compiles into C# types; no runtime surprises. Streaming: Native support for server streaming, client streaming, and bidirectional. Best for internal service-to-service (S2S) calls within a microservice mesh. Weaknesses: Harder for browser/JS clients (though gRPC-Web mitigates this). Tooling is heavier (must manage .proto files and codegen). Debugging is less straightforward than JSON over HTTP. 1.3) Other Alternatives GraphQL : Flexible queries, avoids over/under-fetching. Best for frontend-heavy apps with diverse client needs. Slightly heavier CPU compared to REST projections. SignalR / WebSockets : Real-time bidirectional messaging. Best for notifications, dashboards, chat, trading, telemetry. Not a general-purpose API style. OData : REST with query semantics ( $filter , $select , $expand ). Good for data-heavy apps but complex and less popular today. JSON-RPC : Lightweight RPC over HTTP. Rare in .NET ecosystem compared to gRPC. 2. Key Terms to know about Low latency: gRPC avoids JSON serialization/deserialization overhead by using Protocol Buffers (binary). Typed: Strongly typed contracts generated from .proto files → compile-time safety. Internal S2S calls: Ideal inside a microservice cluster or Aspire-based distributed app, where both ends are .NET or support Protobuf. 2.1) Streaming gRPC natively supports: Unary (request → response, like REST). Server streaming (one request → many responses, e.g. live feed). Client streaming (many requests → one response). Bidirectional streaming (both sides send streams simultaneously). REST needs hacks (polling, SignalR, SSE) for this. 2.2) HTTP/2 Multiplexes multiple streams over a single TCP connection (fewer sockets, less head-of-line blocking). Header compression (HPACK) saves bandwidth. Required by gRPC (classic implementation). 2.3) Proto-first design Define schema in .proto files: service OrderService { rpc GetOrder ( GetOrderRequest ) returns ( OrderResponse ); rpc StreamOrders ( OrderFilter ) returns ( stream OrderResponse ); } From this, C# classes and service stubs are generated. The schema is the contract —language-neutral and stable. Helps maintain backward/forward compatibility (additive fields, field numbers fixed). 3. REST vs gRPC vs Alternatives Aspect REST gRPC GraphQL SignalR/WebSockets Perf (latency/CPU) Higher (JSON parsing, more bytes) Lowest (binary, compact) Medium (parsing & resolver overhead) Low latency Typed contracts JSON schema optional Proto = strongly typed Schema strongly typed Custom, looser typing Streaming No (workarounds needed) Yes, native (uni/bi-directional) Subscription queries (but heavier) Yes, designed for real-time Browser support Native Needs gRPC-Web Native Native Use case fit Public APIs, external consumers Internal microservices, high-perf S2S, streaming Complex client-driven queries Real-time updates .NET 9 support Minimal APIs, controllers, JSON source-gen → very fast First-class gRPC support, HTTP/3 coming HotChocolate GraphQL SignalR (mature) .NET Aspire fit Easy integration with frontends, API gateways Perfect for inter-service calls inside Aspire distributed app Good for complex UI queries in Aspire frontends Aspire dashboard/telemetry scenarios Quick Decision Tree: Which to choose? Public APIs / external clients → REST (simple, widely compatible). Internal service-to-service (microservices) → gRPC (typed, fast, low-latency). Streaming data pipelines → gRPC streaming or SignalR (depending on consumer type). Frontend-heavy apps (Blazor/React) → GraphQL if you want client-driven queries; otherwise REST with projections is simpler. Real-time dashboards, chat, trading feeds → SignalR/WebSockets . Data-heavy querying → consider OData or GraphQL for flexible filters. ✅ My Recommendation for .NET 9: Use REST at the edges (public endpoints, B2B). Use gRPC for internal service-to-service calls between projects (AppHost, backends, workers). Consider GraphQL if your frontends need flexible data shaping. Add SignalR for real-time streaming to browsers . 1. Core Concepts 1.1) REST (Representational State Transfer) Transport: HTTP/1.1 (can also run on HTTP/2/3). Format: Typically JSON (but can be XML, HAL, etc.). Style: Resource-oriented, CRUD-like verbs ( GET/POST/PUT/DELETE ). Strengths: Simple, universally understood, widely supported by tooling. Works well for public APIs and external consumers. Weaknesses: Over-fetching/under-fetching (fixed DTOs). Less efficient serialization compared to binary protocols. No native streaming (must fake it with chunked responses, SignalR, or SSE). 1.2) gRPC Transport: HTTP/2 (HTTP/3 support coming in .NET 9). Format: Protocol Buffers (binary, compact, schema-driven). Style: RPC (Remote Procedure Calls), proto-first design. Strengths: Low latency: Binary serialization and multiplexed HTTP/2 streams reduce overhead. Strong typing: Proto schema compiles into C# types; no runtime surprises. Streaming: Native support for server streaming, client streaming, and bidirectional. Best for internal service-to-service (S2S) calls within a microservice mesh. Weaknesses: Harder for browser/JS clients (though gRPC-Web mitigates this). Tooling is heavier (must manage .proto files and codegen). Debugging is less straightforward than JSON over HTTP. 1.3) Other Alternatives GraphQL : Flexible queries, avoids over/under-fetching. Best for frontend-heavy apps with diverse client needs. Slightly heavier CPU compared to REST projections. SignalR / WebSockets : Real-time bidirectional messaging. Best for notifications, dashboards, chat, trading, telemetry. Not a general-purpose API style. OData : REST with query semantics ( $filter , $select , $expand ). Good for data-heavy apps but complex and less popular today. JSON-RPC : Lightweight RPC over HTTP. Rare in .NET ecosystem compared to gRPC. 2. Key Terms to know about Low latency: gRPC avoids JSON serialization/deserialization overhead by using Protocol Buffers (binary). Typed: Strongly typed contracts generated from .proto files → compile-time safety. Internal S2S calls: Ideal inside a microservice cluster or Aspire-based distributed app, where both ends are .NET or support Protobuf. 2.1) Streaming gRPC natively supports: Unary (request → response, like REST). Server streaming (one request → many responses, e.g. live feed). Client streaming (many requests → one response). Bidirectional streaming (both sides send streams simultaneously). REST needs hacks (polling, SignalR, SSE) for this. 2.2) HTTP/2 Multiplexes multiple streams over a single TCP connection (fewer sockets, less head-of-line blocking). Header compression (HPACK) saves bandwidth. Required by gRPC (classic implementation). 2.3) Proto-first design Define schema in .proto files: service OrderService { rpc GetOrder ( GetOrderRequest ) returns ( OrderResponse ); rpc StreamOrders ( OrderFilter ) returns ( stream OrderResponse ); } From this, C# classes and service stubs are generated. The schema is the contract —language-neutral and stable. Helps maintain backward/forward compatibility (additive fields, field numbers fixed). 3. REST vs gRPC vs Alternatives Aspect REST gRPC GraphQL SignalR/WebSockets Perf (latency/CPU) Higher (JSON parsing, more bytes) Lowest (binary, compact) Medium (parsing & resolver overhead) Low latency Typed contracts JSON schema optional Proto = strongly typed Schema strongly typed Custom, looser typing Streaming No (workarounds needed) Yes, native (uni/bi-directional) Subscription queries (but heavier) Yes, designed for real-time Browser support Native Needs gRPC-Web Native Native Use case fit Public APIs, external consumers Internal microservices, high-perf S2S, streaming Complex client-driven queries Real-time updates .NET 9 support Minimal APIs, controllers, JSON source-gen → very fast First-class gRPC support, HTTP/3 coming HotChocolate GraphQL SignalR (mature) .NET Aspire fit Easy integration with frontends, API gateways Perfect for inter-service calls inside Aspire distributed app Good for complex UI queries in Aspire frontends Aspire dashboard/telemetry scenarios