William To The Internet of Things (IoT), or connected smart devices and sensors, is growing rapidly. One report estimates that IoT connections grew by 18 percent in 2022 to 14.3 billion active assets—a rate of growth that will only continue.
This massive growth in devices and connections is accompanied by an equal increase in data—possibly 80 zettabytes’ (or 80 billion terabytes) worth by 2025. Faced with rising data volumes, devices, and device connections, teams worldwide need a platform to manage their IoT environments.
Enter AWS IoT Core. Since its release in 2015, AWS IoT Core has grown exponentially, counting household names such as United Airlines, NASA, IBM, and Volkswagen Group among their customers. In addition, AWS has since expanded its product family accordingly, adding services for device security, analytics, edge computing, and device software.
This article will discuss AWS IoT Core’s features, benefits, use cases, and provide a tutorial on getting started with AWS IoT Core and Imply.
AWS IoT Core is a fully managed cloud service for IoT devices and teams. This innovative product enables organizations to connect, control, and grow their device fleets—while abstracting away difficult, time-consuming operational tasks such as provisioning servers or configuring encryption protocols.
Think of AWS IoT Core as an engine. In essence, it powers the functionalities of an IoT environment, by facilitating device communication, organizing and processing incoming data, authenticating and authorizing devices and connections, and directing messages and data to the correct destinations.
In this sense, AWS IoT Core provides the essential infrastructure for an IoT environment. It integrates devices into a single network, and plays a role similar to the central nervous system: it enables users to receive, route, and respond to information flowing through the web of IoT devices.
AWS IoT Core also serves as a gateway between IoT devices and the rest of the AWS ecosystem, which includes products to meet almost any computing need. For instance, users can set up data streaming via Amazon Kinesis, which will ingest vast quantities of real-time IoT data from AWS IoT Core. In addition, users can load streaming data into other related AWS services via Kinesis Firehose, or perform instantaneous processing and analysis on streaming data with Kinesis Data Analytics.
Another helpful product is Amazon SageMaker, a fully managed, integrated development environment (IDE) which facilitates the training, deployment, and improvement of machine learning models. IoT teams will find SageMaker especially useful to create algorithms for predictive maintenance or anomaly detection, among other tasks.
Alongside IoT Core, there is also a full suite of other AWS IoT services. These additional features enrich IoT Core, empowering teams across different sectors to leverage industry-specific software, or simply to complete ancillary tasks, such as creating digital twins or ensuring device security.
For instance, a logistics company can use AWS IoT FleetWise in tandem with IoT Core to monitor key vehicle metrics such as EV battery charge or fuel consumption, optimize maintenance schedules, and even train machine learning models for driver assistance systems. Alternatively, a team can use AWS IoT TwinMaker to create a digital twin to provide a realistic, interactive 3D view of physical assets, optimize operations, and improve equipment performance.
At its most basic level, AWS IoT Core is a fully managed service for connecting IoT devices and directing their messages to AWS products. Without AWS IoT Core, users would have to build the required infrastructure from scratch, creating encryption, scaling or provisioning services, constructing a message broker, and coding their own software to integrate with third-party systems such as databases, analytics, visualizations, and more.
The first important component is AWS IoT Core’s built-in Message Queue Telemetry Transport (MQTT) broker, a lightweight, always-on software that can scale to process trillions of messages. MQTT is the standard for machine-to-machine communication, especially under adverse conditions such as poor connectivity, limited bandwidth, or resource constraints.
MQTT utilizes a publish/subscribe architecture, and organizes messages into topics, or hierarchical strings that classify and route messages. Publishers (such as an assembly line speed sensor) will use the MQTT client to publish its reading (say 240 revolutions per minute) to the MQTT broker. In turn, a subscriber, such as a backend control system, will subscribe to the relevant topic, which is speed readings, in order to receive updates. Finally, the MQTT broker will then publish this data to the MQTT client on the backend control system, thus updating it.
Figure 1: How MQTT works, courtesy of MQTT.org
As with the product itself, AWS IoT Core’s MQTT broker is fully managed, so that users can simply use it out of the box, and supports the latest MQTT 5 specifications while providing backward compatibility for MQTT 3. In addition, AWS IoT Core provides authentication and access policies to guard against malicious activity, and provides testing to assess MQTT compatibility with new IoT devices.
Another interesting feature of AWS IoT Core is Device Shadow, which can store the latest state of an IoT device for applications to read, which is especially useful if said device goes offline due to network outages or a hardware outage. In this case, the last known state of the device will remain in AWS IoT Core, which can be transmitted to applications or users via REST APIs, so that the device will appear as if it was still online.
This provides benefits for offline operation and reliability, so that applications can continue to interact with devices even during communication loss. Device Shadow also removes the need for developers to build interfaces for device interactions, and ensures interoperability across different devices and products.
Some IoT devices record audio data, such as those that are voice controlled, while others may need to support visual- or touch-based interactions (such as tablets, point of sale devices, or smartphones). For these use cases, AWS included Alexa, Amazon’s cloud-native voice service, within AWS IoT Core.
In addition, AWS IoT Core’s Alexa integration can connect IoT devices to the wider Alexa ecosystem, enabling the creation of voice interactions for IoT devices using services such as Alexa Skills and AWS Lambda. Developers can also leverage Alexa’s advanced capabilities, including expanded functionalities, multi-modal experiences, and context awareness.
For instance, a user can command an Alexa-enabled device to “turn off the lights,” without specifying which room they’re referring to. By detecting the user’s location, Alexa can execute the action in the correct place, making interactions more seamless and natural.
Adding Alexa into IoT Core creates an added level of abstraction, which greatly simplifies the developer experience. By removing the need to build voice infrastructure from the ground up, developers can focus on other tasks related to their core product and services.
An abbreviation of Low Power, Wide Area networking, LoRaWAN is a wireless protocol for connecting battery-powered IoT devices in large networks. LoRaWan provides several advantages for IoT teams, including long range connectivity over kilometers or even across physical obstacles like terrain; low-power operation for consistent, efficient performance even with limited battery life; and scalability, to accommodate millions of connected devices.
In fact, LoRaWAN is probably indispensable for any IoT network or fleet at scale. Few other protocols can balance the need for high performance amidst conditions such as demanding geography, finite battery capacity, and sheer number of devices. LoRaWAN is also very versatile, utilized across many use cases such as industrial IoT, smart cities, renewable energy, logistics, and more.
As with other parts of AWS IoT Core, adding support for LoRaWAN also saves developers time—again, they don’t have to spend time building their own LoRaWAN Network Server (LNS).
A shared network for local devices like Amazon Echo, Ring security cameras, Tile trackers, outdoor lights, and more, Amazon Sidewalk connects low-bandwidth devices—even when they’re outside of a user’s WiFi range. In order to extend the effective range of these devices, Sidewalk uses Bluetooth Low Energy (BLE), the 900 megahertz spectrum.
By integrating Sidewalk into IoT Core, users can manage data collected from Sidewalk-enabled devices for machine learning, archival storage, and other purposes. IoT Core also provides scalability and reliability to Sidewalk-connected devices, facilitating management and control.
AWS IoT Core can handle massive scale, ensuring that applications built on IoT Core can accommodate massive numbers of devices without compromising performance or reliability. Whether organizations include hundreds or millions of devices, they can provision and register devices with IoT Core using APIs, SDKs, or the AWS Management Console.
Importantly, AWS IoT Core can also handle large volumes of IoT data, processing and routing messages in real time without latency, and facilitating analytics, monitoring, and decision making. As an example, a fleet management company may gather telemetry data from thousands of vehicles to track location, fuel or battery consumption, and engine health.
AWS IoT Core also supports a wide range of devices, communication protocols, and data formats, thus providing flexibility for many different industries and use cases. Because devices vary by firmware, OS, and type, ranging from wearable fitness trackers to industrial machines, IoT Core is device agnostic, ensuring broad compatibility.
One reason for its broad interoperability is IoT Core’s adherence to open standards. By supporting popular industry standards such as MQTT, HTTP, and WebSocket, IoT Core ensures that there are no blind spots, and that applications, devices, and more can communicate with each other.
AWS also provides SDKs and libraries for different programming languages, including Python, Java, JavaScript, C++, and Android or iOS, which allows organizations to quickly build IoT applications and services to use with IoT Core. As an example, a home automation company might use an IoT Device SDK to develop custom firmware for smart lightbulbs or thermostats.
As with other connected technologies, IoT networks are susceptible to malicious attacks, from hacks to being used as an unwilling botnet for Distributed Denial of Service (DDoS) attacks. To protect against this, IoT Core implements security protocols such as TLS, MQTT, and X.509 certificates, encrypting data in transit and at rest.
In addition, IoT Core can be used with AWS IoT Device Defender, which can carry out specialized security functions such as monitoring device authentication events and enforcing role-based access control. To complement IoT Core’s support for security protocols, IoT Device Defender can also build a pattern of device communications in order to detect any anomalies that may indicate suspicious activity.
IoT Device Defender also provides continuous monitoring and auditing in order to detect and respond to security threats in real time. It automatically analyzes device behavior and network traffic, and can alert teams to possible security events. In addition, IoT Device Defender also provides tools for incident response, allowing organizations to investigate security incidents, analyze root causes, and mitigate security risks with corrective actions such as revoking device access, quarantining compromised devices, or automatically triggering remediation processes.
Because IoT Core is fully managed, compatible with a huge range of AWS products, and includes extensive support for common IoT standards like MQTT or LoRaWAN, it significantly reduces the time and effort required to bring IoT solutions to market. Importantly, it removes the need for teams to build these features on their own.
IoT Core’s SDKs and development libraries also speed up development and integration by providing tools for customizing business logic. Rather than creating their own integrations or systems from the ground up, teams can simplify a lot of the complexities around device connectivity and communication. In turn, this time saved can then be used on other tasks, specifically rapidly prototyping and iterating IoT solutions.
Another key advantage is IoT Core’s access to the wider AWS ecosystem, including Amazon S3, AWS Lambda, Alexa, and Amazon SageMaker, among others. With these fully managed services, teams no longer have to build their own custom solutions for machine learning training or recognizing voice or multi-modal inputs, for instance.
AWS IoT Core operates globally, across multiple AWS Availability Zones, to ensure high availability and fault tolerance. This distributed architecture reduces the risk of service outages and downtime by providing redundancy and failover capabilities, so that IoT applications can continue to operate even during hardware failures or network disruptions.
IoT Core automatically scales resources based on demand, ensuring that IoT applications can handle fluctuating workloads or unexpected events such as sudden improvements in network connectivity (resulting in increases in connected devices). Autoscaling also enables organizations to meet performance requirements without over-provisioning resources or incurring unnecessary costs.
Lastly, AWS IoT Core provides monitoring and alerting capabilities to detect and respond to issues in real-time. Organizations can set up alarms and notifications based on predefined metrics, such as device connectivity, message throughput, and resource utilization. This also enables teams to identify and address potential issues before they escalate into downtime or service disruptions.
Since its founding in 2015, AWS IoT Core has been adopted by customer organizations across almost every industry and subset of IoT.
With 170,000 employees producing vehicles for 140+ markets, Volkswagen Group is one of the largest and best-known automotive manufacturers today. Its portfolio includes such well-known (and well-loved) brands like Audi, Bentley, Cupra, Porsche, Lamborghini, Jetta, and more, many of which are household names.
The backbone of their manufacturing and logistics operations, Volkswagen Industrial Cloud is built on AWS IoT Core and other related services. Intended to serve as a single, centralized architecture for operating their 124 factory sites, the Industrial Cloud will improve production flexibility, vehicle quality, and factory efficiency and uptime, among others.
To learn more about how Volkswagen Group uses AWS IoT services, check out their case studies and videos here.
Founded in Barcelona, Spain, in 2015, Wallbox has sold almost 500,000 smart devices across 100+ countries. Today, Wallbox is at the forefront of the renewable energy transition, providing advanced charging infrastructure for battery-powered vehicles.
Since its founding, Wallbox has been a heavy user of AWS technologies, and thus transitioning to AWS IoT Core was a simple decision. After migrating its legacy database architecture to AWS IoT Core, Wallbox was able to reduce operational costs by 50 percent per charger, while improving the scalability, security, and reliability of its device connections.
In addition, Wallbox migrated to AWS IoT Core’s managed MQTT for its connectivity solution for transmitting data to (and receiving data from) smart chargers. MQTT provided a significant improvement over their previous choice, which would regularly disconnect at two hour intervals.
To learn more about Wallbox and its use of AWS IoT Core and other services, check out their dedicated AWS page.
Bosch Thermotechnology North America (Bosch TTNA) is the heating, ventilation, and air conditioning (HVAC) systems of Bosch, a German multinational technology company founded in 1886. With a total revenue of 91.6 billion euros in 2023, Bosch employs 90,100 associates across 136 locations worldwide.
As a newcomer to the design and manufacturing of smart devices, Bosch TTNA wanted to scale its infrastructure quickly while minimizing the associated costs and employee hours. As a result, Bosch TTNA turned to AWS serverless services and AWS IoT Core to connect their sprawling network of smart devices, route massive amounts of device messages to their AWS services, and grow seamlessly—without configuring, provisioning, or troubleshooting infrastructure.
Learn more about how Bosch TTNA uses AWS IoT Core (and other AWS products) here.
Built on Apache Druid, Imply is a database for executing rapid analytics on massive amounts of real-time data. It has several strengths that make it an ideal choice for an IoT database:
Because of these features and tools, Imply provides several important benefits for any IoT organizations and teams.
Thanks to its speed, Imply is an ideal choice for getting real-time insights from IoT device data—minimizing latency and preserving freshness. When used alongside AWS IoT Core, which can ingest and process data in real time, Imply’s ability to instantaneously analyze data facilitates downstream applications and processes, such as anomaly detection, automated triggers, and pattern identification.
Due to its unique architecture, Imply can efficiently store and query massive amounts of IoT data—without incurring significant infrastructure or operational overhead. Given that a single IoT device can generate multiple events per second (and an entire IoT network can likely generate thousands or millions of events per hour), keeping storage costs down is a continuing challenge.
Designed to scale with the growing volume and complexity of IoT data, Imply can integrate with AWS IoT Core and other AWS services to accommodate increasing data ingestion rates, processing requirements, and analytical workloads. This enables organizations to adapt to changing business conditions and accommodate future growth without compromising performance or reliability.
Imply integrates seamlessly with the broader AWS ecosystem, including AWS IoT Core, Amazon S3, and others. This allows organizations to tap into AWS products for their needs, continue using familiar AWS tools, and streamline the implementation and deployment of IoT analytics solutions. Importantly, this means that developers do not need to transition to new software, nor do they need to build any new infrastructure from scratch.
To learn more about how to set up Imply with AWS IoT Core, read this step-by-step tutorial.
As a fully managed cloud service for IoT devices and teams, AWS IoT Core facilitates IoT operations for teams that want to grow and connect their device networks—without creating their own infrastructure from the ground up. By abstracting away the minutiae of operational tasks (such as provisioning servers or configuring encryption protocols), implementing IoT Core in an IoT environment frees up engineers to spend more time working on their core product and improving their business model.
By integrating Imply alongside AWS IoT Core, teams can add a real-time element to their IoT data, providing a more accurate picture of operations and actionable insights for optimizing efficiency, predictive maintenance, and many more use cases. Imply’s advanced analytical tools, scalability, and seamless integration with AWS services make it an ideal companion for AWS IoT Core, enabling organizations to unlock the full potential of their IoT deployments.
To learn more about how AWS IoT Core and Imply complement each other, check out this use cases page.
For the easiest way to get started with Apache Druid, sign up for a free trial of Imply Polaris, the fully managed, Druid database-as-a-service.
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