grpc-go VS prometheus

The reflection service is open-sourced (at least for some sdks):

* https://github.com/grpc/grpc-go/blob/master/Documentation/se...

* https://chromium.googlesource.com/external/github.com/grpc/g...

We’re hoping to make this rate at least optional via this pull request but as the time of writing this blog, it’s nothing we can do to circle our way around it.

First, I started with gRPC’s recommended starter repository for learning gRPC, their **helloworld **example, which is a part of the official gRPC repository.

IDE: use whatever make you productive. I personally use vscode. VCS: git, as golang communities use github heavily as base for many libraries. AFAIK Linter: use staticcheck for linting as it looks like mostly used linting tool in go, supported by many also. In Vscode it will be recommended once you install go plugin. Libraries/Framework: actually the standard libraries already included many things you need, decent enough for your day-to-day development cycles(e.g. `net/http`). But here are things for extra: - Struct fields validator: validator - Http server lib: chi router , httprouter , fasthttp (for non standard http implementations, but fast) - Web Framework: echo , gin , fiber , beego , etc - Http client lib: most already covered by stdlib(net/http), so you rarely need extra lib for this, but if you really need some are: resty - CLI: cobra - Config: godotenv , viper - DB Drivers: sqlx , postgre , sqlite , mysql - nosql: redis , mongodb , elasticsearch - ORM: gorm , entgo , sqlc(codegen) - JS Transpiler: gopherjs - GUI: fyne - grpc: grpc - logging: zerolog - test: testify , gomock , dockertest - and many others you can find here

If you read the first comment, you’ll see the API was documented as being experimental.

https://github.com/grpc/grpc-go/issues/3798#issuecomment-670...

The lack of this analysis still results in bugs and CVEs. See how many races are found and fixed in gRPC releases: https://github.com/grpc/grpc-go/releases (search "race"). It's a shame Google does not publish these as CVEs, because many of them qualify.

I like to point people at this release to show that not even Google -- in its own language on its own library for its own RPC protocol -- can write thread-safe Go, so what chance does anyone else have. Maybe we have to stop thinking of Go as a language for mission critical parallel computing and think of it more like a Python 4 made for low-risk prototyping. Mature libraries help for that prototyping, you know how to put them together and get something working, that something just won't be scaleable, efficient, or thread-safe.

I first learned about this technique when gRPC generated code started using it. See the short readme and the long issue discussion. I think a lot more of the rationale from the discussion should have made it into the readme, since this is the only time most Go developers will ever see this technique used, especially since it can't be retrofitted to existing interfaces without breaking existing implementations.

I don't have any experience with goRPC (I'm assuming you're referring to https://github.com/valyala/gorpc), but just to note that that repo hasn't been updated in 7 years and has open issues that are that old, too. https://github.com/grpc/grpc-go has 17.5k stars and is actively maintained. That doesn't say anything about their relative performance - goRPC might be faster - but you probably won't have a fun time if you run into issues.

Found the root cause from https://github.com/grpc/grpc-go/commit/383b1143 (original issue: https://github.com/grpc/grpc-go/issues/75):

    // Note that ServeHTTP uses Go's HTTP/2 server implementation which is

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.

wget https://github.com/prometheus/prometheus/releases/download/v2.46.0/prometheus-2.46.0.linux-amd64.tar.gz

Prometheus: Open-source monitoring system. Often used together with Grafana.