The Secret to Better IoT Performance (and How It Helps)

The Internet of Things (IoT) presents an exciting challenge to enterprises today. They’re full of a great promise of revolutionizing business, but they present significant performance challenges. The amount of data they generate when widely deployed throughout a network can quickly overwhelm traditional networks and architectures.

To cope with the mountains of data, many IoT platforms are based on cloud platforms and increasingly deployed in hybrid cloud environments. — Which can only help to a certain extent. As IoT works best in real-time, you need a network that can ingest, process, and analyze the data at the same rate on the same scale. 

Being able to continually ingest, process, and analyze data from all IoT devices in real-time is vital, but challenging, and potentially, prohibitively expensive. Depending on the number of devices on the network, the cost to optimize them all may be too far out of reach in terms of money and resources available.  

The Secret to a High-Performing IoT Network

That’s why the most practical and cost-effective approach to creating the high-performance data infrastructure IoT devices need is through innovative open source technologies. Advanced in-memory computing (IMC) can offer higher-powered computing capabilities to each device, while built-in machine learning libraries can optimize parallel processing. 

Enterprises that use these open source tools will increase their IoT device performance, optimize data ingestion, and speed up data processing, all while keeping their costs down. 

Why Open Source Technology Is the Way Forward for IoT

Open source technologies like Apache Ignite, Kubernetes, and Canonical’s Ubuntu Core operating system for IoT devices offer several advantages to IoT platform administrators and application developers. 

Cost Savings

Open source software is more cost-effective for organizations who are already spending a lot on IoT hardware, development resources, and storage and computing systems. It’s one area where you can save money while still using proven, reliable software and hardware that meets your organization’s requirements. 

Access to Enterprise Versions

Many open source technologies offer fully supported enterprise versions today. You can control your development and maintenance costs more easily with these versions, while still receiving the support you need to deploy it on an enterprise level. 

Increased Data Processing

IT teams need help processing all of the data IoT devices ingest. Depending on the device and your organization’s needs, you’ll need to capture different data at different times from different devices. An open source AI like Google’s TensorFlow can help your organization “train” your devices and systems to only look at the most relevant data based on your requirements. The devices quickly learn what data to process and transmit, and which to store in raw form for use later. This eliminates the time-consuming tasks IoT management creates for staff and refocuses your enterprise IT resources to the highest value and most relevant data insights possible. 

Focus on Innovation

Open source IoT technologies help organizations keep pace with the rate of innovation going on around them. The rapid evolution and deployment of IoT devices have forced many companies to sideline their innovation projects as they struggled to keep pace with a highly competitive business environment. Because open source technologies have large and active communities supporting them, you can rest assured that you’ll always have access to the latest and greatest technologies for your IoT devices. 

Integrating open source technologies into an IoT deployment can help organizations enjoy the maximum ROI from their investment. These proven, reliable open source IoT systems can lower development, deployment, and maintenance costs. These cost savings can then be redirected to other areas of the organization, leaving your teams free to innovate. Open source IoT technology is proven, reliable, and often available in enterprise versions, making it a natural choice for those organizations looking to take their IoT fleet to the next level.