parca VS Grafana

Continuous profiling tools such as parca may be worth looking into for your use case.

They were bought by Elastic, maybe they'll open source it. There's also https://github.com/parca-dev/parca

an alternative option to pyroscope to do continuos profiling in production could be parca.dev check and here

+1 to Parca.dev https://github.com/parca-dev/parca as continuos profiling tool in production

Parca collects, stores and makes profiles available to be queried over time. It is open source and can be deployed on production environments as Parca focuses on sampling profiling two main types of profiles: tracing and sampling.

Polar signals develops Parca [0] which is another eBPF observability tool, and Isovalent develops Cilium [1] which is built on eBPF as well. Genuinely curious if there are differences, or if eBPF only allows for specific observability functionality and each tool has it all.

[0]: https://github.com/parca-dev/parca

[1]: https://github.com/cilium/cilium

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: