Edge Solutions

Security & Surveillance

Applications that monitor communications data need to be able to consume data at network speed and keep the most granular detail for many months or years while being highly responsive to arbitrary queries.

Communication Retention

Exhaustive and lengthy online retention of all granular communications activity - including probe messages. Avoids the need to ship sensitive data to a central location and respects the privacy of individuals not part of an investigation.

Web Security

Retain a complete history of all web traffic for governance and investigation of anomalous activity.

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Internet of Things

The internet of things (IoT) is leading to ever expanding volumes of data. It is anticipated that by 2020, there will be 50 billion devices and sensors connected to the internet. The anticipated volume of data is so large and the population of devices so distributed that the connectivity, latency and bandwidth limitations of the internet make it impractical to ship all of the device data to a central location or the cloud.

The only solution is for device data to be collected and analyzed closer to the source of the data - Edge Analytics. This architecture requires numerous autonomous and distributed databases, each handling huge data volumes and delivering data directly to applications or making it available for analytics in near-real time.

Industrial Internet

The management and access of data in the following areas: Asset Tracking, connected products, industrial automation, robotics, smart factories, traffic management, lighting, weather, smart buildings, surveillance, predictive maintenance, entertainment, navigation, connected cars, point of sale, footfall counting, loyalty schemes, hospital sensors, elderly care, vital signs, wearables, remote monitoring, loss prevention.

Consumer Internet

Security, alarms, home automation, electrical equipment, tracking, fitness trackers, sensors.

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Monitoring & Optimization

Networks occur in many forms - communications networks, business networks and social networks to name three examples - and wherever they exist there is a desire to monitor what's happening on the network, and a commensurate need to analyze and understand the behavior of the network. Network monitoring (sometimes referred to as network performance monitoring) is designed to detect events of interest when they occur, and then look for related events or understand the underlying cause of the event.

Unfortunately, in many network use cases, the most detailed data underlying the event of interest occurs in such velocity and volume that it cannot be effectively captured and retained just in case it's needed by network monitoring systems. Rather, with the hope the event happens again, in which case the detailed data is available for root-cause analysis. This is clearly less than ideal, resulting at best in delayed analysis of what caused a network fault or other event, and at worse in an inability to duplicate the event, in which case no root cause analysis is possible.

Network Performance Monitoring

Exhaustive and lengthy online retention of all granular activity including probe messages. Avoids the need to ship voluminous data to a central location.

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Distributed Data Lake

The data lake is an essential component of a modern Enterprise Information Management architecture. It radically reduces the cost per-terabyte of data storage and access - a requirement for Big Data Analytics - while simultaneously delivering the agility and responsiveness long sought-after by business users. Edge Intelligence allows huge data lakes to be geo-distributed.

Distributed Data Lake

Spread the lake across the enterprise and collect all data in real-time while overcoming network bandwidth limitations.

Logical Data Warehouse

Implement a data warehouse that contains all of the data to enable exhaustive data exploration without any pre-design or expensive hardware investment.

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