Developers & Practitioners
What is Cloud IoT Core?
The ability to gain real-time insights from IoT data can redefine competitiveness for businesses. Intelligence allows connected devices and assets to interact efficiently with applications and with human beings in an intuitive and non-disruptive way. After your IoT project is up and running, many devices will be producing lots of data. You need an efficient, scalable, affordable way to both manage those devices and handle all that information.
IoT Core is a fully managed service for managing IoT devices. It supports registration, authentication, and authorization inside the Google Cloud resource hierarchy as well as device metadata stored in the cloud, and the ability to send device configuration from other GCP or third-party services to devices.
The main components of Cloud IoT Core are the device manager and the protocol bridges:
The device manager registers devices with the service, so you can then monitor and configure them. It provides:
Device identity management
Support for configuring, updating, and controlling individual devices
Role-level access control
Console and APIs for device deployment and monitoring
Two protocol bridges (MQTT and HTTP) can be used by devices to connect to Google Cloud Platform for:
Automatic load balancing
Global data access with Pub/Sub
How does Cloud IoT Core work?
Device telemetry data is forwarded to a Cloud Pub/Sub topic, which can then be used to trigger Cloud Functions as well as other third-party apps to consume the data. You can also perform streaming analysis with Dataflow or custom analysis with your own subscribers.
Cloud IoT Core supports direct device connections as well as gateway-based architectures. In both cases the real time state of the device and the operational data is ingested into Cloud IoT Core and the key and certificates at the edge are also managed by Cloud IoT Core. From Pub/Sub the raw input is fed into Dataflow for transformation, and the cleaned output is populated in Cloud Bigtable for real-time monitoring or BigQuery for warehousing and machine learning. From BigQuery the data can be used for visualization in Looker or Data Studio and it can be used in Vertex AI for creating machine learning models. The models created can be deployed at the edge using Edge Manager (in experimental phase). Device configuration updates or device commands can be triggered by Cloud Functions or Dataflow to Cloud IoT Core, which then updates the device.
Design principles of Cloud IoT Core
As a managed service to securely connect, manage, and ingest data from global device fleets, Cloud IoT COre is designed to be:
- Flexible, providing easy provisioning of device identities and enabling devices to access most of Google Cloud
- IThe industry leader in IoT scalability and performance
- Interoperable, with supports for the most common industry-standard IoT protocols
IoT use cases range across numerous industries. Some typical examples include:
- Asset tracking, visual inspection, and quality control in retail, automotive, industrial, supply chain and logistics
- Remote monitoring and predictive maintenance in oil & gas, utilities, manufacturing, and transportation
- Connected homes and consumer technologies.
- Vision intelligence in retail, security, manufacturing, and industrial sectors
- Smart living in commercial, residential, and smart spaces
- Smart factories with predictive maintenance and real-time plant floor analytics
For a more in-depth look into Cloud IoT Core check out the documentation.