Enterprises Can Simplify Device Detection Deployment and Scaling with WURFL Microservice for Docker

RESTON, Va., Feb. 01, 2018 -- ScientiaMobile launches WURFL Microservice for Docker to support enterprises that deploy device detection services using Docker containers. These enterprises can easily integrate WURFL into their microservice architecture and seamlessly deploy to servers using Docker’s container framework.

Learn how to use WURFL device detection from this Getting Started video. WURFL Microservice for Docker delivers high performance device detection via a Docker container image. Users can quickly deploy the latest WURFL from ScientiaMobile's Docker registry to a production server, virtual machine, or even a laptop. Docker users can integrate WURFL on an HTTP server via Java, PHP, .NET (C#), Node.js, or GoLang to supply device detection for their entire organization.

“Docker has grown over 40 percent during the last year among firms that require scalable production environments. ScientiaMobile is rapidly growing its customer base among these types of organizations. We see a great opportunity in the industry, and particularly in the advertising and eCommerce sectors,” says Krishna Guda, Chief Executive Officer, ScientiaMobile.

Jiale Hu, project lead at Implus Technology, a rapidly growing mobile programmatic advertising company, commented, “We needed mobile device detection in a Docker container that meshed with our microservice architecture strategy. WURFL Microservice for Docker is a big win for our development and operations (DevOps) team. Now, we can rapidly deploy new images and drive ads using accurate mobile device subsystems from several hubs around the world.”

ScientiaMobile’s Chief Operating Officer, Steve Kamerman, added, “Our own DevOps team has expertise using Docker to manage hundreds of WURFL instances. This is why we completely understand our customers’ need to easily maintain updated device detection with the same tools they use for continuous delivery. An enterprise-grade Docker registry helps our customers achieve exactly that.”

Benefits:

• Ease of use: Select from Java, Golang, .NET (C#), PHP, or Node.js APIs to easily feed mobile device intelligence into applications.
• Accuracy: Achieve 99.9 percent accuracy in device detection through automatic weekly updates of the industry’s most extensive library, containing 55,000 device models of smartphones, tablets, desktops, smart TVs, and game consoles.
• Customization: Choose from over 500 device capabilities, including form factor and manufacturer's suggested retail price (MSRP), ideal for mobile optimization, advertising, and analytics use-cases.

In addition to WURFL Microservice for Docker, ScientiaMobile offers similar microservices based on Amazon’s Machine Image (AMI) via the AWS Marketplace.

About ScientiaMobile
ScientiaMobile’s customers, including Google and Facebook, use WURFL device intelligence solutions to deliver great web experiences, faster image downloads, and improve sales conversions from mobile customers. ScientiaMobile leads the industry in terms of accuracy, speed, and innovation. ScientiaMobile’s suite of device intelligence products (WURFL OnSite, WURFL InFuze, WURFL Microservice, WURFL.js, ImageEngine, and WURFL InSight) helps Fortune 500 enterprises effectively design and analyze web experiences for an ever-growing range of smartphones, tablets, smart TVs, IoT devices, and game consoles.

Contact Information:
Bethany Libus
[email protected]
Direct: 703-310-6650 Ext. 118
ScientiaMobile HQ
11180 Sunrise Valley Drive
Suite 220
Reston, VA 20191