Thingsboard VS Grafana

Until recently I was still using TB v3.2.1, now I've set about updating the installation to the latest version. I proceeded as described at https://github.com/thingsboard/thingsboard/tree/master/docker:

You might find something more attuned to that use case to be more helpful out of the box (like thingsboard.io) but if you're committed to django, set up an API endpoint to receive json updates ('events') sent from the arduino.

Introduction：As a 100% open source IoT platform that can be hosted as a SaaS or PaaS solution, Thingsboard can provide device management, data collection, processing and visualization for your IoT project. The standard protocols that provide device connectivity such as MQTT, CoAP, and HTTP are all available on ThingsBoard. In addition, it supports cloud and local deployment and provides more than 30 customizable components that allow you to build end-user custom dashboards for most IoT cases. GitHub: https://github.com/thingsboardThingsboard: http://thingsboard.io/ Features:

Then host a ThingsBoard server and use the HTTP API to push data from the device. You can send alerts with Pushover.

**Source** [thingsboard (a foreign iot platform)](https://thingsboard.io/)

ThingsBoard is an open-source IoT platform for data collection, processing, visualization and device management. It supports device connectivity via protocols, such as MQTT, CoAP and HTTP, and supports both cloud and private deployments. Deliver, monitor and control your IoT entities in a secure way using rich server-side APIs that define the relationships between your devices, assets, customers, or any other entities. Collect and store telemetry data in a scalable and fault-tolerant manner, visualize your data with built-in or custom widgets and flexible dashboards, and share the Dashboard interface with your customers.

The company I work for uses https://thingsboard.io and the team from Ukraine that built it are awesome and the company is still responding even though they are going through this hell of a war.

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.