Mopidy VS Grafana

Lots and lots of FOSS music players use libspotify or can otherwise connect to your Spotify account.

Here's just one. It's BYO frontend. https://mopidy.com/

Probably a good time to give a shout out to Mopidy: https://mopidy.com/

Though as for myself, I'm still running Squeezebox - nothing like being able to SSH into your smart speaker and mess around with the Perl system that's running it.

Have you tried Mopidy or MPD daemon? There's even a mopidy-party extension that is

I've tried several times to get mpd working over a network. The only way I got it to work was with mopidy. At some point it broke and I moved on to jellyfin instead. Too bad, because I love ncmpcpp as a client.

I have a music library on my home server that I use mopidy to play via the iris plugin integrated into my home assistant UI. It plays over Snapcast which streams over the network to multiple devices in the home with independent volume control. I can fire up the Snapcast client in my phone to get it going there as well, which does work over vpn if I'm away, though I generally just fire up the files from my phones SD card for out-of-home listening. I recently started using whipper on Linux to extract audio from craigslist cds.

https://mopidy.com/

https://mopidy.com/ext/iris/

https://github.com/badaix/snapcast

https://github.com/whipper-team/whipper

Could instead use Mopidy as the music player, which has plugins for Spotify and Airplay support.

Thanks! I use it on a daily basis, but I don’t think it’s ready for a wider adoption yet — for example, a pause button is still missing ... I’d be curious to know your experience with it though! For something more stable, you might like Mopidy.

Right now I'm reading about mopidy and iris (I have a server with some docker services and it would be nice using it as a Spotify connect device), I think this setup could be extended with extra algorithms, maybe they already exist as modipy extensions. I've never gone into detail about these but I'll do it!

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.