mosquitto VS Grafana

mosquitto_transport, an experiment of writing SObjectizer-based wrapper around mosquitto library;

References: Felipe Flop’s website https://www.filipeflop.com/blog/controle-monitoramento-iot-nodemcu-e-mqtt/ accessed on 01/27/2018. Eclipse server for MQTT Broker https://iot.eclipse.org/ accessed on 01/27/2018. Mosquitto https://mosquitto.org/ accessed on 01/27/2018. Cloud MQTT https://www.cloudmqtt.com/ accessed on 01/27/2018. DuckDNS https://www.duckdns.org/ accessed on 01/27/2018. Proftpd http://www.proftpd.org/ accessed on 01/27/2018. Filezilla https://filezilla-project.org/ accessed on 01/27/2018. Fritzing https://fritzing.org/ accessed on 05/25/2022. Appendices:

This is a perfect use case for MQTT, e.g. this library for ESP boards. Create a broker on the network (e.g. a Raspberry Pi running Mosquitto, and have all the ESP boards subscribe to a topic. When you want to play a sound, publish a message to the topic, and all of the ESPs should see it very quickly. You don't need to synchronize clocks any more because it's simply based on the timing of publishing a message.

While working on a personal project Komponist, I was due to update Mosquitto MQTT Broker due to a CVE and found some interesting changes that will impact me in the future when it comes to configuring the Broker. This post provides a solution to make the Broker compatible with future versions using new and less visited concepts in Docker Compose v2, namely:

Optional: Mosquitto, an open-source message broker that implements the MQTT protocol; this tutorial uses the public test server

I think he means implementation of MQTT protocol, like https://mosquitto.org/

Could MQTT work for you? You'd need a broker like Mosquitto, and then any of a number of MQTT clients.

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.