We are excited to announce a rapid development environment for creating IoT (Internet of Things) and AI (Artificial Intelligence) apps in the cloud, that can be easily deployed in the cloud or at the edge. The environment is designed to alleviate pressures faced by many enterprise organizations around cumbersome, generic cloud environments, creating complex AI models, and generating meaningful IoT data.
Many enterprise development teams are constantly searching for new ways to reduce any friction they might face with subpar internal IT systems. They often turn to the cloud to quickly spin up resources. However, not all cloud resources were designed with the business logic required to solve the problems at hand. 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.
One thing to keep in mind is that in production edge computing environments, it’s vital to analyze data close to where it’s generated. Take a look at this blog for why. This means that if you want to get started 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 that you want to utilize 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.
Figure: End-to-end IoT and AI-based Solution Running in the Cloud
Xi IoT is designed to remove all of these frictions. With one-click, you’re placed into an environment that allows 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 we leverage 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.
Figure: Xi IoT App Library
To solve this dilemma, we will be adding the application library capability - Xi IoT App Library - to provide not only powerful individual components (e.g., message bus services, time series databases, etc.) but also 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 business problems; all with one-click. This will not only reduce the time to get started, but also reduce the domain expertise required. If the application doesn’t solve the exact problem, the developer can create their own app and try it out on the platform. This will allow 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.
Figure: Image Analysis Applications
Let’s not Forget About the Data...
When designing IoT and AI based applications, we can’t forget about the data. This is what makes the applications come to life. It’s required to not only validate if the application works, but it’s also used to train the models to get started. However, it’s not always easy to figure out how to quickly pipeline 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.
Figure: Datasets for All Development
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 iPhone mobile device and start leveraging the camera to ingest live data and send that directly to Xi IoT.
Figure: Xi IoT Sensor App
This is not just a new trial offer; it’s a new experience to get everyone from the most novice developers to more advanced developers, creating revolutionizing AI and IoT scenarios.
Forward Looking Disclaimer
This blog post includes forward-looking statements concerning our plans and expectations relating to new product features and technology that are under development, including the Xi IoT App Library, the capabilities of such product features and technology and our plans to release product features and technology in future releases. These forward-looking statements are not historical facts, and instead are based on our current expectations, estimates, opinions and beliefs. The accuracy of such forward-looking statements depends upon future events, and involves risks, uncertainties and other factors beyond our control that may cause these statements to be inaccurate and cause our actual results, performance or achievements to differ materially and adversely from those anticipated or implied by such statements, including, among others: the introduction, or acceleration of adoption of, competing solutions, including public cloud infrastructure; a shift in industry or competitive dynamics or customer demand; and other risks detailed in our quarterly report on Form 10-Q for the fiscal quarter ended January 31, 2019, filed with the Securities and Exchange Commission. These forward-looking statements speak only as of the date of this press release and, except as required by law, we assume no obligation to update forward-looking statements to reflect actual results or subsequent events or circumstances.
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