GlusterFS VS gRPC

https://github.com/gluster/glusterfs/issues/894

And apparently apart from modern coreutils using that, it is mostly gentoo users hitting the bugs in lseek.

This Product Appendix does not apply to online service offerings managed by Red Hat or generally available open source projects such as www.wildfly.org, www.fedoraproject.org, www.openstack.redhat.com, www.gluster.org, www.centos.org, okd.io, Ansible Project Software or other community projects.

Just because Red Hat will stop selling commercial support for their product, does not mean GlusterFS itself is dying. It's an open source project like any other - https://github.com/gluster/glusterfs

https://www.gluster.org/ Is the way to do this across nodes

This allows us to fetch the desired quality of the video as per the user's request, and once the media file finishes processing, it will be uploaded to a distributed file storage such as HDFS, GlusterFS, or an object storage such as Amazon S3 for later retrieval during streaming.

GlusterFS

But where can we store files at scale? Well, object storage is what we're looking for. Object stores break data files up into pieces called objects. It then stores those objects in a single repository, which can be spread out across multiple networked systems. We can also use distributed file storage such as HDFS or GlusterFS.

GlusterFS - same as above (https://www.gluster.org/)

What you look for is a clustered file system. Like https://www.gluster.org/. As long as all units are closeby with low latency there are a couple solutions that allow you to create distributed storage solutions of various kinds. Key value stores applenty, clustered file systems that pretent to be one file system etc. If you have geographically distributed solutions with high latencies it becomes harder. Most open source systems don't work really well in this scenario. There were a couple attempts like Hydrabase but they didn't go so far. It normally is solved by doing two clusters and then replicate between them.

I'd imagine most managed service providers are going to require a credit card, though most of them have a free tier. If you want to take an unmanaged approach, maybe look into Gluster. I've used it before and never had issue with it, but I also had an infrastructure team that set it up, so I'm not familiar with the challenges that way: https://www.gluster.org/

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