etcd VS gRPC

sudo dnf -y install curl wget vim ETCD_RELEASE=$(curl -s https://api.github.com/repos/etcd-io/etcd/releases/latest|grep tag_name | cut -d '"' -f 4) echo $ETCD_RELEASE wget https://github.com/etcd-io/etcd/releases/download/${ETCD_RELEASE}/etcd-${ETCD_RELEASE}-linux-amd64.tar.gz tar xvf etcd-${ETCD_RELEASE}-linux-amd64.tar.gz cd etcd-${ETCD_RELEASE}-linux-amd64 sudo mv etcd* /usr/local/bin ls /usr/local/bin /usr/local/bin/etcd --version

Reading the standard library will give you ideas/insight about various Go idiomatic patterns/approaches, and you can see a full website/API implementation in the pkg.go.dev repository (https://github.com/golang/pkgsite). Projects like https://github.com/etcd-io/etcd may be interesting too.

Failure Detection and Recovery It’s not enough to have backup systems. It’s also crucial to detect failures quickly. Modern systems employ monitoring tools and rely on distributed coordination systems such as Zookeeper or etcd to identify faults in real-time: once detected, recovery mechanisms are triggered to restore the service.

Service Discovery: Microservices need to discover and communicate with each other dynamically. Service discovery tools like etcd, Consul, or Kubernetes built-in service discovery mechanisms help locate and connect to microservices running on different nodes within the infrastructure.

APISIX uses etcd to store and synchronize configurations.

etcd is an excellent key-value distributed database used internally by Kubernetes and managed by the CNCF. It's a great option, and that's the reason why Apache APISIX uses it too. Yet, it's not devoid of issues.

Someone on HN (https://news.ycombinator.com/item?id=36682595) suggested etcd (https://etcd.io)

In traditional mode, APISIX stores its configuration in etcd. APISIX offers a rich API to access and update the configuration, the Admin API. In standalone mode, the configuration is just plain YAML. It's the approach for GitOps practitioners: you'd store your configuration in a Git repo, watch it via your favorite tool (e.g., Argo CD or Tekton), and the latter would propagate the changes to APISIX nodes upon changes. APISIX reloads its configuration every second or so.

I am not sure neither. But this might overcome the etcd's soft storage limit of 8GB? [1]

[1] https://github.com/etcd-io/etcd/issues/9771

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