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In many cases, the end of the year gives you time to step back and take stock of the last 12 months. This is when many of us take a hard look at what worked and what did not, complete performance reviews, and formulate plans for the coming year. For me, it is all of those things plus a time when I u...
IoT Network Visibility | @ThingsExpo @SolarWinds #IoT #IIoT #M2M #API
Accelerating complexity is just one challenge in how hybrid IT is affecting IT departments

Why Network Visibility Beyond the Firewall Is Critical in the IoT Era

In the hybrid IT era, complexity is the name of the game. In fact, according to the recent SolarWinds IT Trends Report 2017, IT professionals report the number one challenge of hybrid IT is increased infrastructure complexity. Accelerating complexity is just one challenge in how hybrid IT is affecting IT departments. Internet of things (IoT) implementations are a great example of one more unexpected, emerging technology IT teams must address.

In the report, IT professionals reported the second greatest challenge of hybrid IT is lack of control and visibility into the performance of cloud-based applications and infrastructure. Most IoT devices connect to cloud back ends or edge/fog-distributed endpoints, rather than traditional data centers. Distributed workloads by their nature put admins in a bind, and the multiplicative nature of IoT devices makes the visibility challenge even more difficult. But this isn't all doom and gloom. The path to managing these complexities is found by exploring the ways IoT use cases play out in different implementations, and identifying solutions for IT professionals to better manage the hybrid IT and IoT convergence.

IoT in Practice
To best understand how to manage complexity and gain visibility beyond the firewall in the IoT era, consider common IoT scenarios in hybrid IT organizations.

Cloud-Based IoT
In this scenario, the back end of the IoT infrastructure is in the public cloud. Potentially millions of distributed devices and multiple clustered workload systems are all reporting data back to the cloud, making cloud monitoring extremely critical. IT professionals managing these cloud-based IoT implementations must be able to view the entire network path to ensure end-user performance, or at least synthetic application performance (if the end user is an IoT bot). This can be difficult because the traffic is completely outside of the firewall. Instrumenting the end-user experience is key to troubleshooting issues, and monitoring cloud infrastructure and cloud components of the application at the same time is necessary.

On-Premises IoT
A great example of this scenario would be industrial IoT, where there are multiple IoT devices but production data is captured in the organization's data center. In this case, the IoT devices create massive amounts of data on-premises, effectively creating the complexity of analyzing a multi-tiered Big Data application. Massive processing and storage is required - perhaps Hadoop® and MapReduce are at play - as well as streaming analytics and transformation. And then, of course, there are security considerations, reporting or regulatory requirements that stem from allowing IoT devices to connect with the data delivery network. For example, are there considerations for new protocols like MQ Telemetry Transport Protocol (MQTT) access instead of HTTP and managing Transport Layer Security (TLS) traffic through the firewall?

All of this can place a significant inbound traffic burden on the on-premises data center, a relative tidal wave from the outside world into the on-premises system via firewalls. An added wrinkle is open source. Many IoT solutions and enabling technologies are based on open source, publicly available projects. Too often, developers in a hurry to get to market are quick to download a package off of GitHub without vetting for security. IT professionals and security managers must ensure control and some method of codebase oversight over these new application delivery stack elements to secure the code accessing our networks.

Edge-Based IoT
This is also known as fog-based IoT - computing at the edge. Here, distributed data collection and processing facilities distill data in the field rather than sending in built-to-cloud or on-premises repositories. For example, a municipal government may have sensors watching traffic patterns to optimize traffic light signaling strategies. In their model, processing IoT data in the field is more cost effective, even if it requires distributed compute resources located offsite. However, those distributed elements must still be managed, their network traffic assured, and performance monitored just as if they were safely back home in a rack, but with the challenge of remote access and latency.

Best Practices for Managing IoT Complexity and Visibility
Regardless of whether an IoT implementation is cloud-based, on-premises, or on the edge, there are common practices that should be followed in order to conquer complexity and visibility issues:

  1. The most powerful tool for hybrid IT gives a single view. Troubleshooting across the boundaries of hybrid IT can have massive positive effects on productivity. At the end of the day, successful management of IoT requires cross-environment visibility.
  2. Education and skill-building should be ongoing. IT departments should work with the business to ensure some budget is allocated to education, personal development training, conference passes, and certifications for IT professionals. Investing in the IT team can pay some of the greatest dividends in terms of being able to manage complexity, especially considering that nearly half of today's IT professionals say IT professionals entering the workforce now do not possess the skills necessary to manage hybrid IT environments. Create the skills on teams now instead of waiting for them to come in the future.
  3. Geek out on data. IT professionals should think about how to unlock their inner data scientists. Rather than just pushing data around, it's important for today's IT professionals to bring operations data and hybrid IT data into the lab and experiment with it. Doing this will likely uncover new insights that can help identify performance issues associated with IoT.

Perhaps one day, there will just be cloud, but in no case is that tomorrow. Hybrid IT will only become more complex and difficult to manage at least for the next few years. A little motivational alarm is okay, as long as IT professionals don't get discouraged and continue close skills gaps. IT professionals who take necessary steps today to improve their environments - regardless of IoT scenario - may experience the empowerment that comes with full visibility across on-premises, to the cloud and beyond, wherever workloads may lie.

About Patrick Hubbard
Patrick Hubbard is a head geek and senior technical product marketing manager at SolarWinds, with 20 years of technical expertise and IT customer perspective. His networking management experience includes work with campus, data center, high availability and disaster recovery, and storage networks, and with VoIP, telepresence and VDI in both Fortune 500 companies and startups in the high tech, transportation, financial services and telecom industries.

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