Over a million developers have joined DZone.

One-Click IoT- and AI-Based Application Environment

DZone 's Guide to

One-Click IoT- and AI-Based Application Environment

These types of environments remove the friction of setting up an IoT infrastructure.

· IoT Zone ·
Free Resource

I had the opportunity to speak with Rohit Goyal, Principal Product Marketing Manager, and Greg Smith, V.P. Product Marketing, at Nutanix about the Xi IoT rapid development environment for creating IoT (Internet of Things) and AI (Artificial Intelligence) apps in the cloud, which can be deployed in the cloud or at the edge. The environment is designed to alleviate friction faced by many enterprise organizations and their developers around generic cloud environments, creating complex AI models and generating meaningful IoT data.

Enterprise development teams are constantly searching for new ways to reduce friction with subpar IT systems and infrastructure. They often turn to the cloud to spin up resources. However, not all cloud resources were designed with the business logic required to solve the most immediate problems.

For example, if you wanted to run IoT and AI-based applications, you may have to leverage many different services, which isn’t a trivial process at the edge. Additionally, developers often have to build applications from scratch because they don’t have access to an existing set of IoT and AI applications. Lastly, in order to validate if the application or function works, it’s important to have data sources to test; otherwise, it’s like testing out a new car without the fuel. Xi IoT addresses each of these challenges to accelerate time-to-market for innovative edge solutions.

Generic Cloud-Based Development Environments Aren’t Sufficient

Existing cloud-based systems aren’t always sufficient. Developers typically love to dive deep into problem-solving and let their fingers do the talking. However, they quickly get frustrated if the development environment isn’t ready to go. Developers shouldn’t spend time setting up basic networking, operating systems, or containers — they should be focused on solving business logic problems through applications. It’s more efficient to develop applications in the cloud and then push those applications to the edge from a centralized location. It really shines at scale, as you can easily push multiple applications, across multiple sites and locations through easy to use APIs.

Image title

In production edge computing environments, it’s important to analyze data close to where it’s generated.  If you want to start developing IoT and AI apps, you typically require an edge resource. To complicate matters, the diversity of platform services and APIs also differs between the edge and cloud stacks. Imagine you want to use Containers-as-a-Service (CaaS) and Functions-as-a-Service (FaaS), but they are not available at the edge and are only available in the cloud. Developing IoT and AI applications quickly become very difficult. You may be required to change your code based on the deployment location. This wouldn’t be very efficient and would slow down the development and rollout process.

Xi IoT is designed to remove all this friction. With one-click, you access an environment that allows the deployment of IoT and AI-based applications in the cloud, exactly the same way they’re deployed on the edge at a physical location. This is possible because Xi IoT leverages the same SaaS operational goodness you find in a production environment. Enhanced with the capability of running a Xi IoT Cloud Instance, it removes the need to deploy an edge at the physical location for dev/test. Now, you don’t have to worry about platform services or APIs being different from your development and production environments. They’re the same. You will also get a taste of how to run thousands of edge locations from a single infrastructure and lifecycle management plane. You’ll no longer waste time and resources procuring edge hardware for testing application concepts.

Applications Libraries for AI-Based Solutions

Most enterprises are always looking for ways to reduce the time it takes to solve business problems while reducing investment costs. It’s not always easy to find both. It’s actually really difficult. When you break down a typical IoT and AI-based application environment, there are many components to consider. For example, it sometimes requires an ecosystem of partners to get started because not all enterprises are blessed with development teams. Even if you happen to be one of the lucky ones, you probably don’t have the spare time to build new IoT and AI-based applications from scratch.

Image title

To solve this dilemma, Nutanix will add to the application library capability — Xi IoT App Library — to provide powerful individual components (e.g., message bus services, time series databases, etc.), as well as full solutions. Developers will be able to browse through a library of application solutions to select and deploy the ones that make the most sense to solve their business problems; with one-click. This will reduce the time to get started and reduce the domain expertise required. If the application doesn’t solve the exact problem, the developer can create their own app and try it on the platform. This allows enterprise teams to dream up new ways to increase business. Nutanix Xi IoT App Library provider partners, like Deepomatic, will be key in catapulting the enterprise to.

Image title

Source: https://research.google.com/youtube8m/                                    

Figure: Datasets for All Development

Don't Forget About the Data...

When designing IoT and AI-based applications, data is critical. Data drives the application. It’s necessary to validate if the application works and is also used to train the models to get started. However, it’s not always easy to figure out how to quickly move the data from a sensor to the edge where applications reside. Even when you figure out that piece, doing it in the cloud without building out your own proprietary environment doesn’t sound like a good use of development time.

There are many types of data sources; however, we’ve found that most enterprises are interested in leveraging vision-based datasets. So, we set out to figure out a way to solve that problem.

If your vision dataset is proprietary and don’t want to post on YouTube, you can send it directly to the virtual edge. This will give you the power of instant analysis at your fingertips. It no longer requires heavy lifting to test out new AI-based algorithms. However, we didn’t stop there.

A vast library of existing videos is nice, but what about live data? Since most people have smartphones today, Xi IoT now makes that easy too. Just download Xi IoT Sensor app for your Android and iPhone mobile device and start leveraging the camera to ingest live data and send that directly to Xi IoT.

Image title

Image title

Figure: Xi IoT Sensor App


Xi IoT a new experience to get everyone from the most novice developers to more advanced developers, creating revolutionizing AI and IoT scenarios.

You can get a 10-day free trial and give it try. There are tutorials to help you get started. Visit Nutanix.com/iot and developer.nutanix.com/iot to learn more.

iot ,ai ,machine learning ,one-click ,app ,iot apps ,ai apps

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}