awesome-jsonschema VS gRPC

Truth. Zod is comparable to JSON Schema plus AJV, and it doesn't compare well at all. Your Zod code is all locked inside TypeScript so not only can it not be shared to any other language in your stack but it also cannot be serialized, which introduces many limitations. You also miss out on all the JSON Schema ecosystem tooling. (1, 2) For example the intellisense you get in VS Code for config files is powered by JSON Schema and schemastore.

The very first line of text below the header on the json-schema.org homepage is:

The framework's official website mentions a number of pros of FastAPI. In my opinion, the most useful features from a microservice perspective are: the simplicity of code (easy to use and avoid boilerplate), high operational capacity thanks to Starlette and Pydantic and compatibility with industry standards - OpenAPI and JSON Schema.

I've used Felte to reduce form boilerplate. Felte supports several different validation libraries like Zod. I actually used a custom validation function with ajv (which uses JSON schema).

(There is already a JSON Schema definition at https://json-schema.org/)

Like you said - standard XML isn't terrible. Adding on an XSD isn't terrible, because now you can enforce structure and datatypes on files provided by outside parties. Creating an XSLT is much more of a mental challenge, and probably should be left to tools to define.

Anything beyond those technologies is someone polishing up their resume.

While the aws-sdk is being installed to simulate DynamoDB locally, let me explain a few things about this command. First Comment will be the name of the model the scaffold creates. This model will be codified under app/models/schemas/comment.mjs as a JSON Schema object. Each of the parameters after Comment will be split into a property name and type (e.g. property name “subject”, property type “string”). This JSON Schema document will be used to validate the form data both on the client and server sides.

What you are looking is called Json-schema. Have a look at the implementations page, which will give you an idea of what you can do with json-schema, which also includes UI rendering.

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