crystal VS Grafana

27. Crystal - $77,104

I like the first code example on https://crystal-lang.org

    # A very basic HTTP server

Obviously as an interpreted language, it's never going to be as fast as something like C, Rust, or Go. Traditionally the ruby maintainers have not designed or optimized for pure speed, but that is changing, and the language is definitely faster these days compared to a decade ago.

If you like the ruby syntax/language but want the speed of a compiled language, it's also worth checking out Crystal[^1]. It's mostly ruby-like in syntax, style, and developer ergonomics.[^2] Although it's an entirely different language. Also a tiny community.

[1]: https://crystal-lang.org/

Crystal is a nice language that's not only simple to read and write but performs very well too. And the documentation is amazing as well.

Ruby is a super fun scripting language. I much prefer it to python when I need something with a little more "ooomph" than bash. It's just...nice...to write in. Ruby performance has come a long way in the last decade as well. There's libraries for pretty much everything.

My modern programming toolkit is basically golang + ruby + bash and I am never left wanting.

I do find Crystal (https://crystal-lang.org/) really interesting and am hoping it has its own "ruby on rails" moment that helps the language reach a tipping point in popularity. All the beauty of ruby with all of the speed of Go (and then some, it often compares favorably to languages like rust in benchmarks).

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.