cla-assistant VS Grafana

I was curious about the automated CLA process. It is interesting to me to read the answer about not supporting GitLab:

https://github.com/cla-assistant/cla-assistant/issues/534

Very terse answer that says:

  As you noticed, this would mean a completely different line of code

Open source Contributor License Agreement assistant

I'm currently using https://cla-assistant.io/ just to be sure.

I use CLAAssistant and do not accept PRs without it https://cla-assistant.io/ - not that there are any notable PRs, mostly README typo fixes and such.

Signing the CLA can be automated and I highly recommend you set up this process with the help of this CLA assistant. You can also find some ready-made CLA texts out there just waiting for you to be (responsibly) copied and pasted.

You can do that wirh CLA helpers (used for some very high volume projects). For ex, https://github.com/cla-assistant/cla-assistant (this will only work if you have a Github org though as it uses Github to track people who signed)

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.