Challenges of Existing Platforms and Processes

Enterprises are experiencing a number of challenges as they attempt to fully leverage data available to them.

This is natural because the realization of how powerful data can be has just recently become clear. Now, enterprises are feverishly updating their platforms and processes to ensure they can benefit from the intelligent edge era. Some challenges enterprises face include: 

• Existing systems have been built on a legacy model of data center-focused networks. The rise and mainstream adoption of cloud services, edge data sources and IoT device proliferation are leading organizations to consider new “edge-to-cloud” architectures. The key to this new design is enabling efficient and secure connections at the edge where data is generated and processed, and the cloud where global views and data models can be developed.  
• Manual, reactive, ad-hoc and/or siloed management of these systems in a distributed environment is untenable given the volume, velocity and variety of data being processed. Organizations can no longer rely on fixing issues when they become broken; they must be able to predict when systems will fail to prevent any impact to customers, users or the business. 
• Pervasive network administration culture is conservative, which inhibits adoption of innovations such as machine learning and artificial intelligence; these enhanced automation tools benefit organizations greatly in recognizing trends, identifying issues and making changes quickly.
• Security must evolve in this new paradigm as well. Having perimeter-based security policies does not work in a highly distributed system. Security should be based on a zero-trust system that continuously monitors and enforces security dynamically at the user and device level, at all points of the network. 

Network spending makes up largest share of intelligent edge infrastructure spending

Worldwide Internet of Things Edge Infrastructure Spending by Segment, 2017-2023 ($B)