--- title: "Streaming on the edge: hype or handy?" description: Discover how real-time streaming data at the edge boosts machine performance and empowers R&D teams to make precise, data-driven decisions faster. image: https://blogs.itility.nl/hubfs/2151977854-2.jpg --- [![itility](https://blogs.itility.nl/hubfs/blog/img/itility%20logo-01.png)](https://www.itility.nl) - Your industry - [Agriculture](https://www.itility.nl/agriculture) - [Energy](https://www.itility.nl/energy) - [Manufacturing](https://itility.nl/manufacturing) - Our expertise - [Business transformations](https://www.itility.nl/business-transformations) - [Software and data](https://www.itility.nl/software-development/) - [IT foundation](https://www.itility.nl/it-foundation) - [Managed services](https://www.itility.nl/managed-services) - [(Generative) AI](https://www.itility.nl/ai/) - [Who we are](https://www.itility.nl/who-we-are) - [Working at Itility](https://careers.itility.nl) - [About](https://itility.nl/about) - [About Itility](https://itility.nl/about) - [Offices](https://itility.nl/about#office-locations) - [Tech partners](https://itility.nl/tech-partners) - [Responsibility](https://itility.nl/responsibility) - [Contact](https://www.itility.nl/#contact) - Your industry - [Agriculture](https://www.itility.nl/agriculture) - [Energy](https://www.itility.nl/energy) - [Manufacturing](https://itility.nl/manufacturing) - Our expertise - [Business transformations](https://www.itility.nl/business-transformations) - [Software and data](https://www.itility.nl/software-development/) - [IT foundation](https://www.itility.nl/it-foundation) - [Managed services](https://www.itility.nl/managed-services) - [(Generative) AI](https://www.itility.nl/ai/) - [Who we are](https://www.itility.nl/who-we-are) - [Working at Itility](https://careers.itility.nl) - [About](https://itility.nl/about) - [About Itility](https://itility.nl/about) - [Offices](https://itility.nl/about#office-locations) - [Tech partners](https://itility.nl/tech-partners) - [Responsibility](https://itility.nl/responsibility) - [Contact](https://www.itility.nl/#contact) [![Picture of Itility](https://blogs.itility.nl/hubfs/Avatar-Itility.png)](https://blogs.itility.nl/en/author/itility?hsLang=en) Written by:   ## [Itility](https://blogs.itility.nl/en/author/itility?hsLang=en) # Streaming on the edge: hype or handy? **Improving machine performance with real-time streaming data** At one of our customers, the Research & Development engineers need to analyze data from their machines - in order to constantly improve performance of these machines that are being developed and finetuned for their customers. These R&D engineers are closely involved in the development, testing, integration, and lifecycle of critical system components. For this, they require fact-based decision making – based on real-time data. Previously, these engineers had limited access to the actual machine data. Instead, they needed to rely on outdated data with limited density and not enough signal details. Data collection and data processing was cumbersome and required a lot of manual work; including many excel sheets. Resulting in a high workload (and cost) for data processing before even being able to start analyzing. A process that was person-dependent and error-prone. How to solve this? Together we have built an edge solution that directly connects to the machine on the factory floor. It allows to stream data in real-time, with a very high density, and with many more sensor signals than was possible before. Even signals with a high frequency, normally too heavy to process. For the solution, a physical Google Edge was used, connected to one of the test machines in the lab. We handled it end-to-end, including everything from installing and configuration of the physical Google edge device in the customer network, to the application to stream and process the data. A high-core, high-memory, high-bandwidth single stack, with a containerization layer on top of it that handles large amounts of data at a very low latency of milliseconds – processing and preparing it for further analysis with pre-built KPI’s and analysis-ready access to the data. This is an ideal solution for low-latency, high-frequency data demands. 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