gRPC VS asio-grpc

gRPC, built on HTTP/2, inherently supports flow control. The server can push updates, but it must also respect flow control signals from the client, ensuring that it doesn't send data faster than what the client can handle.

Yes, grpc_cli tool uses essentially the same mechanism except implemented as a grpc service rather than as a stubby service. The basic principle of both is implementing the C++ proto library's DescriptorDatabase interface with cached recursive queries of (usually) the server's compiled in FileDescriptorProtos.

See also https://github.com/grpc/grpc/blob/master/doc/server-reflecti...

The primary difference between what grpc does and what stubby does is that grpc uses a stream to ensure that the reflection requests all go to the same server to avoid incompatible version skew and duplicate proto transmissions. With that said, in practice version skew is rarely a problem for grpc_cli style "issue a single RPC" usecases: even if requests do go to two or more different versions of a binary that might have incompatible proto graphs, it is very common for the request and response and RPC to all be in the same proto file so you only need to make one RPC in the first place unless you're using an extension mechanism like proto2 extensions or google.protobuf.Any.

While gRPC and Apache Thrift have served the microservice architecture well, CloudWeGo's advanced features and performance metrics set it apart as a promising open source solution for the future.

The loadBalancingConfig is what we use in order to decide which policy to go for (round_robin in this case). This JSON representation is based on a protobuf message, then why does the name resolver returns it in the JSON format? The main reason is that loadBalancingConfig is a oneof field inside the proto message and so it can not contain values unknown to the gRPC if used in the proto format. The JSON representation does not have this requirement so we can use a custom loadBalancingConfig .

The Dart implementation of gRPC which puts mobile and HTTP/2 first. It's built and maintained by the Dart team. gRPC is a high-performance RPC (remote procedure call) framework that is optimized for efficient data transfer.

gRPC is a high-performance, open-source RPC (Remote Procedure Call) framework initially developed by Google. It uses Protocol Buffers for serialization and supports bidirectional streaming.

In general, tunneling through HTTP2 turns out to be a great choice. There is a RPC protocol built on top of HTTP2: gRPC[1].

This is because HTTP2 is great at exploiting a TCP connection to transmit and receive multiple data structures concurrently - multiplexing.

There may not be a reason to use HTTP3 however, as QUIC already provides multiplexing.

I expect that in the future most communications will be over encrypted HTTP2 and QUIC simply because middleware creators can not resist to discriminate.

[1] <https://grpc.io>

Even in the https://grpc.io blog says this

gRPC

Since I can never remember what arguments to pass to protobuf_generate to create Protobuf and gRPC source files, I wrote an article about it. It provides a copy-paste-able code snippet along with an explanation of all arguments that protobuf_generate accepts, how to format it nicely using cmake-format and how to make things easier with asio-grpc.

Asio-grpc makes exactly that possible by providing an Asio execution_context compatible interface to the CompletionQueue. It supports all types of RPCs (including generic ones), completion tokens, cancellation, as well as libunifex sender/receiver (if you want to try out what might become std::execution). The latest release (v1.7.0) also introduced a GrpcStream class for writing Rust/Golang select-style code.

It hasn't been without issue, however. Problems that may lie in official google-maintained libraries are of course present and required design changes, and I was even prompted to write my own bitset library that outperforms the C++ standard's by a factor of 60. Madness. Right?

Or check out the asio-grpc repository directly if you are looking to write asynchronous gRPC services with the features of Boost.Asio like C++20 coroutines, std::futures, stackless coroutines, callbacks and Boost.Coroutines.