The Internet of Things represents an important strategic alliance within the organization - a chance to bridge the gap between line-of-business technology and IT.
When it's done right, IoT enables an organization to collect and leverage data from key areas of the business, across the entire organization. But that's the real question: How often is it done right? Many observers point out that IoT often divorced from IT, creating technology and business challenges that could be addressed if both stakeholders are part of the process.
When operations adopt a self-contained - or horizontal -- IoT solution to improve energy usage or vehicle fleet efficiency, for example, what is the role of IT? When a third-party provider handles the installation and sometimes even management of the solution, how does IT build a stronger partnership with the business? Especially when considerations of security and scale may not have been part of the original deployment?
The answer is innovation and agility. Business operates in real time, so access to information immediately is key. If an IoT system is delivering information to a console or dashboard someplace, that's a good place to start. By leveraging these services and network components, you can provide real-time insight to processes and tasks on-premises or in the cloud.
IoT has become a conduit of information, channeling millions of bits of data on a daily basis. The shelf life of data is dependent on how quickly it becomes useful and accessible. A key component for the IT professional is to take advantage of the opportunities IoT provides and recognize its impact to the business. Organizations are thinking differently about how they obtain and use data, and this technology shift will extend to the IT pro. It's time to think less about maintaining servers and more about solving business problems and predicting performance with data.
Digital transformation is the profound and accelerating shift of business activities, processes, competencies, and models to leverage the changes and opportunities of digital technologies in a strategic and prioritized way, with evolution always in mind.
IoT and the analytics applied to its disparate data streams are prime agents of transformation. Properly instrumented devices - even cameras and smartphones -- can collect information and send it in a feed to analytics engines on-premises or in the cloud. Data-driven adjustments can be pushed to any device within the IoT, as well.
Microsoft provides a broad range of capabilities that bring together IoT and Advanced Analytics, either as a cloud-based service, for hybrid scenarios, or at the edge to allows customer to create their own framework for managing connected assets. In fact, you can find preconfigured solutions for the most common IoT tasks remote monitoring, industrial device instrumentation, and even predictive maintenance. Familiarize yourself with these overviews and reference architectures, and you'll soon figure out how these tools can be of service to your operation.
Broad language support
The prominent features of AMQP are message orientation, queuing, routing (including point-to-point and publish-and-subscribe), reliability and security. Encrypted messaging between devices is another feature of IoT that can be implemented across devices.
Microsoft has a rich community of IoT users and developers to exchange ideas with for creating services, as well as SDKs with sample code. With the power of the Microsoft Azure behind IoT, an organization can securely store, manage and update data on millions of devices.
Security of IoT
Most security incidents are discovered and reacted to, not predicted. Smart organizations conduct thorough post-mortems after a breach has been remediated. During the post-mortem, you can assess shortcomings and gain a deeper understanding of how the event occurred and the steps taken to resolve it. This type of modeling is effective is preventing a similar incident in the future.
Microsoft's IoT framework uses a similar method of modeling to determine potential threats that may compromise security. This type of modeling enables IT to partner with business and provide a critical service. IT pros can build threat models based on IoT processes, data stores, data flow, and external entities.
This model must expand to include data as well as any external source or target that is connecting to the system. The model must address access control and lock down storage, so that it reduces the risk for unauthorized entry or data corruption.
We'll dive deeper into IoT security concerns in a future blog. In the meantime, you can learn more about Microsoft Azure IoT Hub here.