speedtest_exporter VS prometheus

Hi All, Earlier I was using Speedtest-Tracker ( henrywhitaker3/Speedtest-Tracker: Continuously track your internet speed (github.com) ) to track my internet speed, but unfortunately, it is no working properly, and there is no update since 2021, so, i was looking for an alternative for my Raspberry Pi and I came across this wonderful implementation from ( danopstech/speedtest_exporter: 🏎️ Prometheus exporter that runs speedtest and exposes results (github.com) ) danopstech, but is is also not updated since 2021 and no longer working, then while checking all the forks, I found one by olqs ( olqs/speedtest_exporter: 🏎️ Prometheus exporter that runs speedtest and exposes results (github.com) ), and I have created my own fork with ARM64 support, and fortunately it is working fine after build. If you are interested, please feel free to use this.

This uses my Starlink exporter I shared a while ago, along with a speedtest exporter and ping tester blackbox exporter. It also starts a Prometheus and Grafana container for you.

Two Prometheus exporters: https://github.com/danopstech/starlink_exporter https://github.com/danopstech/speedtest_exporter

It's like Prometheus, but for logs. Okay it's not really to do with the Norse or Greek gods, instead Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by the open source project Prometheus. Built by Grafana Labs, Loki is designed for ease of use. Instead of indexing the contents of the logs, Loki provides a set of labels for each log stream. The latest update includes query acceleration with Bloom filters, native OTel support, Helm charts, and more. Check out the changelog for all the major changes and deprecations.

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.