08/13/2026
๐๐ผ๐ ๐บ๐ฎ๐ป๐ ๐ฐ๐ผ๐บ๐ฝ๐ผ๐ป๐ฒ๐ป๐๐ ๐ฑ๐ผ๐ฒ๐ ๐ถ๐ ๐๐ฎ๐ธ๐ฒ ๐๐ผ ๐๐ถ๐๐๐ฎ๐น๐ถ๐๐ฒ ๐ ๐ค๐ง๐ง ๐ฑ๐ฎ๐๐ฎ?
For many IoT projects, the answer is still: ๐ ๐ค๐ง๐ง ๐๐ฟ๐ผ๐ธ๐ฒ๐ฟ โ ๐๐ฎ๐ณ๐ธ๐ฎ โ ๐๐ง๐ โ ๐ง๐ถ๐บ๐ฒ-๐ฆ๐ฒ๐ฟ๐ถ๐ฒ๐ ๐๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ โ ๐๐ฟ๐ฎ๐ณ๐ฎ๐ป๐ฎ.
But for most telemetry workloads, that architecture is often more complex than necessary.
In this tutorial, we show how to build real-time IoT dashboards with ๐๐ ๐ค๐ซ ๐ง๐ฎ๐ฏ๐น๐ฒ๐ ๐ฎ๐ป๐ฑ ๐๐ฟ๐ฎ๐ณ๐ฎ๐ป๐ฎ, enabling you to:
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Store MQTT telemetry directly in a built-in time-series database
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Query data instantly with standard SQL
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Connect Grafana using the PostgreSQL data source
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Build live dashboards without Kafka or ETL pipelines
Whether you're monitoring factory equipment, energy assets, or connected devices, this approach shortens the data path and simplifies your entire observability stack.
๐ ๐ฅ๐ฒ๐ฎ๐ฑ ๐๐ต๐ฒ ๐ณ๐๐น๐น ๐๐๐๐ผ๐ฟ๐ถ๐ฎ๐น: https://buff.ly/HKpcsFk