shuttle VS Grafana

Moreover, I especially like where Rust is right now in the web space. It really feels like there’s a lot of smart people working on the next generation of web development tools - it feels like the place to be. There are a range of great open-source web dev tools that are just reaching critical levels of maturity. Axum, which I used to build Prodzilla, feels ready for out of the box web dev, and is crazy-performant, as I write about later. More recently available is Loco, a Rails-like framework for building web applications in Rust that's picking up steam. And in dev-tooling and hosting there’s Shuttle, a 1-line hosting solution for Rust backends.

cargo-shuttle is Shuttle's own CLI for interacting with the Shuttle platform. Within the src folder, you will be able to get a better sense of how you can organise your folders/files for a larger CLI project for a live service. There is also use of async here with tokio, so if you're interested in learning how to get started with using clap with async services (for example setting up an async client for a database service), this would be a perfect opportunity to learn to do so!

https://github.com/shuttle-hq/shuttle/tree/main/services/shuttle-axum https://docs.rs/shuttle-axum/0.34.1/src/shuttle_axum/lib.rs.html#1-78

It would be great if there are some kind of code snippet on the README that really demonstrate the "ship backends without writing infra" feature that I think is one of the unique feature of shuttle. I remember seeing one on the official website (https://shuttle.rs) that left me impressed.

Shuttle is currently accepting entries for a competition, with the best projects being featured at our booth at the [EuroRust](eurorust.eu/) conference this year.

Reading here https://shuttle.rs may be nice to try for the future.

At Shuttle, we've teamed up again with Stefan Baumgartner, the organizer of Rust Linz and author of 'Typescript in 50 lessons', to host a free workshop titled "Rust for Javascript Developers: Building apps that utilize LLMs".

The community being built at https://shuttle.rs is extremely open and welcoming. I’ve yet to do anything on the main code base, but I’ve helped with the docs.

At Shuttle we’ve teamed up with Stefan Baumgartner, the organizer of Rust Linz, to create a newsletter series that takes a slightly different approach towards learning Rust.

Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.

To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.

Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.

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

Grafana

Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.

So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:

In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:

Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.