Cloud Platforms for IoT

The Internet of Things (IoT) is quickly becoming a part of people’s daily lives as more and more devices connect to one another, exchange data, and process it to address certain issues. Users only have access to the “tip of the iceberg” of IoT systems, which are considerably bigger than we can even comprehend. These processes involve gathering data, converting it into the proper format, processing it to extract meanings, transferring and storing information, stressing particular qualities, utilising complicated algorithms, and finally producing the end product that users can understand and use. Because of the infrastructure complexity of contemporary Internet movements, developing it without using an IoT cloud platform is nearly impossible.

What is a cloud platform?

Imagine moving all your computer hardware, software, database, and applications from your physical office to a more secure site, and they are delivered to you over the internet.

This is the simplest definition of cloud computing. To speak a little more technically, the cloud is the provision of computing services over the internet (cloud) to provide easy access to your data, instead of using a local server or a personal computer to store, manage and process your data. Because cloud-based services are provided over the internet, users do not need to have independent computing infrastructure and data centres.

As long as there is an existing internet connection, users can access online services via the cloud. Cloud services are also on-demand services where you only pay for the resources you use in a given period. This helps you lower your operating costs and run your infrastructure more efficiently.

As you can see in the figure below, there are many cloud platform providers on the market.

Pie Chart for market share shows that the leaders in cloud platforms for IoT are AWS, Microsoft Azure, and Google Cloud Platform. Therefore, we’ll take a look at what the three main providers can offer for businesses and developers with a table comparison.

Leading IoT Cloud Platforms & Their Strengths

The dominant platforms—AWS IoT Core, Microsoft Azure IoT Hub, and Google Cloud IoT (legacy)—offer robust capabilities, but vary in strengths:

AWS IoT Core emphasises scalable device communication, integrated security, and a mature developer ecosystem. Greengrass extends cloud capabilities to the edge, ideal for applications needing low-latency or offline functionality.
Azure IoT Hub provides strong enterprise-grade integration, powerful data streaming, and advanced analytics tools like Time Series Insights. It’s especially appealing for businesses already leveraging Microsoft services.
Google Cloud IoT Core (now deprecated) was valued for simplicity and analytics integration. Developers continue using GCP services like Pub/Sub, BigQuery, and Dataflow for building IoT pipelines.

Selecting a platform often comes down to existing tech stack alignment, developer tooling, and which ecosystem best supports the lifecycle of your IoT application—from ingestion to analytics.

Data Compliance & Hosting Considerations

Data security and governance are non-negotiables. Most businesses must comply with strict data protection laws and need clarity on where their data is stored and processed. Cloud providers offer region-specific hosting and access control policies to help meet local compliance obligations.

Certifications such as ISO/IEC 27001, SOC 2, and GDPR-compliance mechanisms are commonly supported. Where sovereignty matters, it’s important to confirm whether your selected platform ensures data residency in regional data centres, particularly for regulated sectors.

Connectivity & Network Architecture

An effective IoT deployment starts with consistent connectivity. Support for protocols like MQTT, HTTPS, and AMQP is standard, but edge computing and local wireless options can significantly improve responsiveness and reduce bandwidth costs.

Technologies such as LTE-M, NB-IoT, and LoRaWAN are widely used for devices that require low-power, long-range communication. Meanwhile, edge compute solutions like Azure IoT Edge or AWS Greengrass enable local processing, decision-making, and reduced latency—critical in use cases like manufacturing, health monitoring, and asset tracking.

Private networks and 5G are also gaining traction, especially in industrial and logistics environments where real-time data is crucial.

Pricing, Flexibility & Cost Optimisation

Cloud pricing models differ by service, but most follow a usage-based approach. That means you pay for what you consume—messages, storage, analytics, or device operations.

Each provider offers a limited free tier for testing:

Azure allows up to 8,000 device-to-cloud messages per day.
AWS provides 250K messages per month for the first year.
Google Cloud services like Pub/Sub and BigQuery offer permanent free tiers for small-scale usage.

For growing deployments, cost forecasting and traffic modeling become important. Some providers also offer billing in multiple currencies, regional invoicing, and pre-paid service plans through local partners or cloud resellers.

Conclusion

Choosing an IoT cloud platform is not a one-size-fits-all decision. It depends on your infrastructure needs, device footprint, compliance obligations, and plans for scalability. While the top platforms offer overlapping capabilities, their ecosystems, support channels, pricing models, and integrations differ—often in ways that can significantly impact success.

Whether you’re optimising a logistics network, enabling smart energy systems, or scaling a consumer device ecosystem, aligning with the right cloud architecture and connectivity model from the start is critical.

Frequently Asked Questions About Cloud Platforms for IoT

Q1: Is device data encrypted during transmission and storage?

Yes. Most platforms support TLS 1.2+ encryption in transit and AES-256 at rest. Ensure your architecture enforces these standards by default.

Q2: What if I need to run IoT applications offline or in remote areas?

Edge computing frameworks like Azure IoT Edge or AWS Greengrass allow local processing and decision-making, syncing with the cloud only when connectivity resumes.

Q3: Can I connect legacy or non-IP devices to modern cloud platforms?

Yes, via protocol gateways, serial-to-IP converters, or local edge gateways that act as intermediaries between devices and the cloud.

Q4: How do I ensure my platform is future-proof?

Choose vendors with strong integration support, active development roadmaps, and backwards compatibility. Also, look for open standards and developer-friendly SDKS.