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Old MacDonald had a Farm .. E-I-E-IoT
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Problem to Solve: My company has invested in an IoT platform. For such a vast network of data collection, how can we assure service delivery and performance for the whole platform?

E-I-E-IoTSo what does an old school nursery rhyme have to do with the Internet of Things (IoT)? Not much other than if this nursery rhyme were to come out today, old MacDonald would have some flavor of IoT probably running at the farm.

The new Internet of Things version of Old MacDonald would be more like:

a “device device” here ..

and “cloud cloud” there ..

here an “app”, there a “protocol”

everywhere an “Analytics Analytics”

Old MacDonald had a farm,  E-I-E-IoT

So now we are all clear why I did not become a professional nursery rhyme writer. However, when it comes to IoT and the backend service delivery chain involved, I do have some thoughts.

IoT Service Delivery Chain

Think about what an IoT Service Delivery chain actually looks like from the end device collection, all the way through to the back end analytics systems. It includes things like the device, transport of data, data collection, Big Data Analytics, Cloud, and integration with corporate systems.

Device

Information is king, and that is why companies are investing in IoT platforms. The end device “widget” has all kinds of interesting data and metrics about itself.  End devices come in all sizes and shapes, things like ATMs, Smart Meters, Google Glass, Medical Devices, Light Bulbs, Batteries, etc. The metrics for these devices will vary based on what the “widget” is, but examples are things like temperature reading, location/GPS, voltage, errors, etc. The data collected from the widget gets turned into business information at the end of the service delivery chain. Some customers are even looking at embedding “applets” (small application footprints) on the end device itself.

Transport

So once you have a device and data, you have to provide some method for getting the data “off of the device”. Transport methodologies vary from RF, cellular, wireless, long haul ethernet to accomplish the harvesting and transport of the collected data. Transport protocols vary from custom developed, HTTP, MDM, Bluetooth, Zigby, MQTT, etc. Many of them are based on IPv6 due to the extreme number of IP addresses involved.

Data Collection

The data from the end device gets transmitted back to a data collection hub. These hubs could be deployed as Cloud options (i.e. Amazon Web Services or  Azure IoT Hub), co-location facilities, distributed data centers, or just be back hauled all the way back to the corporate data center. At this layer, the raw data is usually aggregated and processed through to the format that will likely be pushed into a Big Data Analytics solution. Many times this information from the Analytics solution will communicate back to a corporate ERP or CRM system.

Big Data Analytics

There are many types of analytics platforms to help create information from the data. Looking for trends inside the data for usage, failures, metrics, maintenance, population to glean information to make better business decisions is the goal. Creating a competitive advantage into new business markets (i.e.Blue Ocean Strategy  https://en.wikipedia.org/wiki/Blue_Ocean_Strategy) from your own collected data is a tremendous opportunity.

The Big IoT Questions to Ask

The first question that needs to be answered is “what is the strategic value of implementing IoT at our company?”. Forgive the blunt delivery, but if there is no tangible business reason for introducing this technology, then why is it being implemented? From my experience with customers, the data is of strategic value because IoT projects are taking off like wild fire, and being driven by the business leaders.
 
The second question should be “what is the impact to our business if we cannot collect, gather, analyze, communicate, process, or interface with the IoT data?”.  Again, assuming the information gathered from the IoT is a strategic asset with value, what happens if there is a service disruption to the IoT service delivery chain? What happens to the business when this happens?
 
Question number three then becomes “how do I mitigate this risk for IoT service delivery?”. This is where you can leverage Application Performance Management / Network Performance Management (APM / NPM) solutions in a much more strategic manner. IoT services include devices that leverage various communications methods, transport protocols, public and private clouds, applications, API’s, and interfaces. APM / NPM solutions are well versed to monitor interfaces, communications & transport protocols, multi tier applications, latency, custom applications, as well as things that IoT deployments are hugely dependent. Service enabler protocols such as DHCP, DNS, LDAP authentication can have a huge impact on IoT service delivery if there is a failure. APM / NPM solutions are extremely well suited to monitor these types of deployment models. 

APM / NPM for IoT

The difference with APM / NPM solutions is that the monitoring is not just for keeping corporate systems up and available, as is a common use case for APM / NPM solutions today. Now, APM / NPM can be used for assuring that the company’s strategic IoT service delivery chain is performing optimally. The Internet of Things is a vast environment of devices and certainly will require a solution that can scale. But even taking into consideration the vast number of devices, protocols, and applications involved, the fundamental architecture behind IoT is a very large and complex Multi Tier application. See one of my previous articles about Multi Tier applications here at this link  Don’t let a Multi-Tier Application Make You Multi Tear Up. 
In general, a monitoring solution that provides service assurance specifically to address strategic company objectives like IoT, can put CIO’s and IT in general much closer to the company business. This solution empowers IT to assist in true digital transformation for the organization.