IOT106 · Cloud Platforms and Dashboards for IoT
About Course
Build the platform side of IoT: ingest device messages, store them as time-series data, transform them with flows and present them on dashboards with alerts that people actually act on, using a free open-source stack on your own computer.
Who it is for
Learners who can publish device data over MQTT and want to turn it into a usable monitoring service for a business.
Prerequisites
IOT105 (MQTT and IoT networking); Docker Desktop installed or willingness to install it.
What you will be able to do
- Compare managed IoT cloud services with a self-hosted open-source stack for a small business.
- Ingest MQTT messages with Node-RED and store them in InfluxDB using sensible tags, fields and retention.
- Build a Grafana dashboard that answers specific operational questions.
- Configure threshold and no-data alerts with clear routing and minimal alert fatigue.
Lessons
- Lesson 1 · IoT platforms: managed cloud and open-source stacks
- Lesson 2 · Time-series data and flows
- Lesson 3 · Dashboards and alerts people act on
- Lesson 4 · Lab and assignment
Lab: A cold-room monitoring stack with Node-RED, InfluxDB and Grafana
You start a four-container stack with Docker Compose, subscribe Node-RED to the telemetry your simulated ESP32 publishes, write readings to InfluxDB and build a Grafana dashboard for three cold rooms. You finish by creating a temperature alert and a device-offline alert.
Free tools: Docker Desktop, Eclipse Mosquitto, Node-RED, InfluxDB OSS 2.x, Grafana OSS (all free, local), Wokwi ESP32 simulator
Assessed assignment
Submit your docker-compose.yml (without secrets), exported Node-RED flow, a Grafana dashboard JSON export and screenshots of both alerts firing and resolving. Write a short operations note for the business owner: what each panel means, what to do when each alert fires and who is responsible. Explain your tag and field design and your retention choice. Compare the cost and effort of running this stack against a managed cloud IoT service for 20 devices.
| Criterion | Weight | What excellent work looks like |
|---|---|---|
| Working data pipeline | 30% | Messages flow from device to broker to Node-RED to InfluxDB without loss, with validation of bad payloads. |
| Dashboard usefulness | 25% | Panels answer clear operational questions, use correct units and highlight safe ranges. |
| Alerting design | 25% | Threshold and no-data alerts work, have sensible durations and clear routing and response steps. |
| Data model and platform reasoning | 20% | Tags, fields and retention are justified; the self-hosted versus managed comparison is realistic. |
Portfolio piece
A reproducible Docker Compose monitoring stack with an exported dashboard and an operations note, ready to demonstrate to a prospective client.
Next step
Continue with IOT107 · IoT Security and Privacy · 8 hours · $56.00
Course Content
IOT106 · Cloud Platforms and Dashboards for IoT (8 h)
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Lesson 1 · IoT platforms: managed cloud and open-source stacks
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Lesson 2 · Time-series data and flows
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Lesson 3 · Dashboards and alerts people act on
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Lesson 4 · Lab and assignment
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IOT106 Assessment · Cloud Platforms and Dashboards for IoT