grpc_bench VS gRPC

SayHello, GetUser, and Sum differ only by payload size. Sum is the simplest one - (int, int) -> int, GetUser is (long) -> User (medium payload), and SayHello uses exactly the same payload as this test: https://github.com/LesnyRumcajs/grpc_bench/tree/master/dotnet_grpc_bench

This is correct. The problem is not with the benchmark itself but with the implementation. If you look at the result, you can see that even with 6 "allowed" CPUs, the vertx server utilizes less than 100%. Apparently, the current vertx implementation (the one implemented in https://github.com/LesnyRumcajs/grpc_bench/tree/master/java_vertx_grpc_bench) is single-threaded or has some other limitation.

Another iteration of grpc_bench!

Because it's fast and runs on Windows, Linux, and MacOS

In general though, akka/pekko-streams are known to be one of the fastest implementations out there. Their grpc client for example even beats languages like Rust (see https://www.lightbend.com/blog/akka-grpc-update-delivers-1200-percent-performance-improvement and https://github.com/LesnyRumcajs/grpc_bench/wiki/2022-03-15-bench-results).

The whole point I was making is at least up until 8 months ago (at best, I can't commend on the stability/maturity/performance of shardcake) Akka was the only mature library/ecosystem solving this problem with also a very strong focus on performance (for example still to this day, akka/pekko-grpc is generally one of the fastest grpc implementations I am aware of, its even beating rust if you have at least 2 cores (see https://github.com/LesnyRumcajs/grpc_bench/wiki/2022-03-15-bench-results)

It would be interesting to create a new java benchmark with your implementation.

Also worth checking out the gRPC benchmarks: https://github.com/LesnyRumcajs/grpc_bench/discussions/284

dotnet is up there with Rust.

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