consul-template VS gRPC

The Hashicorp corporation has made a huge impact in providing valuable tools and platforms in the cloud ecosystem. The advantage of using the tools they provide, such as Terraform, Vault, and Packer, is that they all have the same language, Hashicorp Configuration Language (HCL). This means you can easily pick up any of these tools by learning HCL, which is similar to JSON. This approach can be useful when choosing tools to learn or use for a project.

Terraform is an open-source infrastructure as a code tool. It is designed by HashiCorp and written in Go Programming Language. Terraform is used to automate the creation of DevOps infrastructure and tasks. Terraform provisions and configures your DevOps infrastructure. It spins up new servers, creates load balancers, and node groups, and performs network configurations. Terraform is mostly applied to provision resources on cloud providers like AWS, Google Cloud, and Microsoft Azure. It can automate and provision infrastructure on any cloud platform. We will use Terraform to set up an Azure Kubernetes Service Cluster that has all the necessary cloud resources.

It can be time-consuming to create and manage the infrastructure that drives your software applications as they grow and become larger. Also, what about ongoing updates and releases of new features? Luckily, there is a solution to this problem in the form of a tool designed by Hashicorp called Terraform. This allows us to define our infrastructure in a central configuration file without having to create it on every provider platform we use.

HashiCorp Sentinel: Sentinel is a PAC tool developed by HashiCorp that can be used in tools such as Terraform, Vault, and Nomad. Sentinel supports writing rules in programming languages such as HCL to automate the enforcement of security and compliance policies.

Terraform is an infrastructure as code tool (IAC) created by HashiCorp that lets you automate cloud and on-prem resources. It uses configuration files written in HashiCorp Configuration Language (HCL) to declare resources (infrastructure objects) and define dependencies between them. To put it simply, this tool allows you to write a few configuration files and build a whole system’s architecture on the cloud by running a couple of commands. I found this to be a more efficient alternative to clicking through a console to create resources manually.

It was clear back in 2021 that Lob needed to consolidate how we run code and none of our current tools were up to the task; it wasn’t a matter of if Lob would upgrade to something new, but when. The Platform team kicked off a research project to find Lob’s next service platform. Forever ago (back in 2019) we investigated migrating to Kubernetes, a popular but notoriously difficult-to-manage tool for this sort of thing, but that project fizzled out for many reasons, forcing us to consider something else. We chose Nomad which offers a comparable feature set to Kubernetes in a much more streamlined package. Nomad is developed by HashiCorp, a leader in the DevOps space, and is used by companies like Pandora, Cloudflare, Internet Archive, and Roblox.

If however, you have an application service that needs support for 2+ ports, because you know, Kubernetes supports this, I would recommend avoiding Consul Connect, as it is not functional to meet minimum requirements for a service mesh. Perhaps someday, when Hashicorp prioritizes basic functionality and usability in future version, this product can be considered.

Looks a lot like Hashicorp (a technology company), maybe too similar, and not particularly evocative IMO.

AWS VPC is a simple example. This feature really shines when building reusable infrastructure-as-code for Network Firewall or even Network ACLs. Anything that simplifies something and reduces or eliminates any hacks required to reach a logical outcome is super valuable. Great work finally driving this one home HashiCorp.

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