Davra Storms MQ
DevOps may be blessed with a common working understanding, but this definition is still hard to box in. Although the framework is focused on IT, it also has an intentionally broad scope that includes your IoT platform.
How is your DevOps strategy dependant on your IoT toolbox? Can you build a system that helps RoI, data visibility and project success ascend to loftier vantage points? Here’s how to ease your approach — and keep your enterprise in one piece — with better IoT middleware.
Organizational IoT implementations and DevOps practices are extremely well-suited to each other. This fine pairing arises partially because both fields are so extensive, although their broadness manifests in distinct ways.
DevOps professional certifications and standards are growing increasingly widespread. Still, this discipline is far from concrete, and many of its tenets are loose by design. Since DevOps addresses corporate cultural factors, for example, it has to account for no small amount of variance.
Off-stage DevOps techniques, such as continuous delivery and version control, can often set the tone for how talented workers interact with each other, which affects your organizational viability and cooperative tendencies. While most pull-request arguments don’t typically spill over into customer service land, there are real ties between your behind-the-scenes dev practices and the ability to deliver usable IT products.
IoT’s massive scope is partially due to how distributed computing tools are implemented. Companies, states, service providers and other groups build the solutions they need, so real-world examples run the full gamut of features and functionality. Even if there were a one-size-fits-all design, it would require intelligent, per-application tweaks and modifications.
IoT landscapes are naturally diverse at the enterprise level because different objectives call for various hardware and software tools. For instance, you might not be able to locate one supplier that makes all of the varied types of sensors you need, or you may prefer to mix and match for more fine-grained data feed oversight. Such realities can make it hard to find help when you’re trying to steer towards an as-yet uncharted project goal.
The DevOps focus on business-relevant concepts aids connected computing in a few key ways:
Version-controlled software deployment accommodates stable automated testing that makes it way easier to catch bugs and prevent poorly-planned rollouts from compromising your services. This also extends to testing custom IoT applications in virtualized hardware environments before deploying them in live business ecosystems.
Continuous delivery and version control make it simpler for all employees to verify that they’re on the same page, or working from the latest code.
As more IoT systems connect to employee-operated industrial devices and linked consumer systems, privacy concerns grow in kind because more personal user data gets involved. Commonplace DevOps tools, such as dependency alerts for software engineers and automated firmware update notifications for users, make it simpler to tackle vulnerabilities and threats from the top down.
Flexible development practices get DevOps strategies off the ground faster. Think of it like putting a puzzle together — You might need a bunch of different APIs, libraries, toolchain components and other pieces to get the job done.
If you were lucky enough to have help, you might also recall that completing a puzzle alongside like-minded friends lowered the barrier to entry. Just as different perspectives made things go more smoothly, building an IoT-centric strategy from scratch can feel more comfortable when your DevOps practices accommodate different working styles and unique viewpoints with targeted information.
Flexible IoT platforms help companies build more effective IoT implementations. Instead of constraining enterprises, these platforms facilitate their preferred workflow management styles just as easily as they accommodate their Intel sensor load outs and Inmarsat fleet broadband devices. This makes sense considering that the ties between versatile software development tools and IT productivity are well-documented, so working with the IoT seems to be no exception.
DevOps principles support IoT applications on geographically and socially broad scales as well. For instance, the power to automate complicated industrial processes through the use of cloud-based microservice platforms, such as Azure, made smart manufacturing and intelligent business practices far more accessible to more companies. Unfortunately, this has also muddied the waters for some firms and organizations.
IoT industry experts have tried to address the confusion. One group even put forth a three-tiered DevOps model specifically for handling urban IoT tasks. In this case, the framework was applied to track a city’s electric vehicle usage and management stats using data from a unique mix of mobile and embedded devices.
Platform-based workflows let you shape your strategy to match any technology. Although trial and error are always useful, you shouldn’t have to experiment with the grinding fundamentals such as hardware compatibility. The right IoT Platform takes care of all that for you so that you can concentrate on creating the most effective workflows.
Although the IoT builds on complex technology, it’s also highly convenient and accessible. Getting up and running is fast. Even if you decide to tackle highly involved tasks, such as creating DevOps service contracts for your IoT microservices, there are plenty of examples of how to get started.
This state of affairs means that IoT development often walks a line between desired functionality and over-customization. DevOps fights these tendencies with goal-oriented workflows, and in this contest, it’s not alone. IoT Platforms help by supporting high-level project conceptualization and feature planning as well as fine-grained tasks, such as editing custom dashboards. They also make it simpler to evolve your workspaces on the fly and build the specialized tools you need for maximum productivity.
Today’s machine intelligence may fall short of the futuristic sci-fi image most people are crossing their fingers for, but it’s undoubtedly proficient in one area. It can emulate complex behaviors with uncanny effectiveness given the right training.
IoT Platforms make important human decisions simpler to automate, which is critical for DevOps tasks. Which charts, options, buttons and other UI elements should you keep when you deploy a new version of your production line control app? Your platform’s dashboard might spell out the answer by instantly zeroing in on the most salient bits of user feedback. Will your new smart building control tweak have a favorable impact on coder productivity? Intelligent IoT Platforms not only help you find out but also suggest well-reasoned solutions to ergonomic and usability challenges.
DevOps has few limitations, and neither does an efficient IoT platform. Although picking a software solution can be tricky, smart infrastructure managers, production leaders and IT specialists know mission-critical systems demand stability and established quality. The best decision-makers depend on well-known industry leaders.
Davra is among a scant few IoT Platform providers that received Gartner IoT Magic Quadrant recognition in 2019. With a focus on supporting organizations that serve and cater to others, it delivers integrated IoT solutions that let enterprises get more done – Get in touch to find out how.
Joe Quinn, Davra, CTO