gokrazy VS Grafana

Switching to gokrazy[0] was the best thing I did for my Raspberry Pi uptimes. I think a lot of that is because it defaults to using read-only partitions so the common issue of SD cards falling over when you run apt upgrade no longer happens.

But I also think that gokrazy's simplicity and design helps it be just a solid, reliable foundation to build on top of.

[0]: https://gokrazy.org/

The idea there sounds a lot like https://gokrazy.org/, which builds a minimal go userland, wrapping one or more user provided go applications, and bundles in a linux kernel.

Targets mostly at single board computers, and I think it downloads pre-built kernels (and bootloaters if needed), rather than trying to build them directly, since getting a working cross compilation toolchain set up and plumbed into the kernel compilation process is still a pain.

I've personally only used yocto/open-embedded for that which does nicely handle building the cross-compilation toolchain, kernel image, and modules. But it is kinda overkill for that task, being designed to build a whole userland too.

reminds me of https://github.com/gokrazy/gokrazy which does similar things.

https://gokrazy.org/ would like a word

Fun! We have support for running on gokrazy (https://gokrazy.org/) already, and that's probably where Unikernel Linux is more applicable for us, for when people just want a "Tailscale appliance" image.

I'll email you.

gokrazy exists! https://github.com/gokrazy/gokrazy

https://github.com/gokrazy/gokrazy for one example

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.