Enterprises are delivering intelligent and immersive experiences that require high bandwidth, ultra-low latency networks. To deliver these experiences, you require an agile app development platform that can adapt to your requirements and business logic.
In addition, you need the flexibility to place applications and workloads across multi-cloud that are optimally placed to meet the business requirements along with autonomous operations, security and governance.
Enterprises can build, run, manage, connect and protect their industry specific edge-native applications at the Near and Far Edge while leveraging the consistent infrastructure and consistent operations across their Data Centers and Cloud.
Protect distributed users, data and applications against threats at all levels. Security is built into the platform for superior protection and is specific to every application and workload.
Simplify operations and management across multi-cloud with consistent, centralized policies for operational consistency.
Retail stores can implement interactive digital media to improve the customer experience, including enhancing customer buying behavior and recommendations as well as secure cashless cashier and payment processing.
Edge computing can be used to run applications, including mixed reality mirrors that require real-time human interaction, and other applications that require low latency and analytics processing.
Manufacturers require solutions that will help improve efficiency, cost control and quality along with the need for near real-time analytics of machine performance.
Edge computing will enable manufacturers to power digital twin solutions that enable near real-time monitoring and control of machines and processes. Manufactures can monitor and control in near real-time machines and processes, as well as incorporate AI / ML for overlay of complex models on products.
Gain greater understanding of emergency events using streaming data analytics to respond to events in real time.
Empowering first responders and disaster workers with time-sensitive data is critical to their success. The massive amounts of data feeds from cameras, drones, satellites and vehicles coupled with analytics require processing at the edge to give rapid and actionable analytics in emergency situations.