HP Enterprise extended last week its Edgeline line with the introduction of HPE Edgeline EL1000 and HPE Edgeline EL4000 converged Internet of Things systems that capture and analyze big data at the network edge.
With IoT becoming a key growth area for OEMs, opportunities are abound in virtually every industry, including manufacturing, energy, telecommunications, retail and transportation. Next-generation systems will automate industrial control processes and optimize workflows improving productivity, decision making and business results. But the vast scale of the Internet of Things poses complex architectural challenges for OEM system designers.
HPE has plenty of experience helping OEMs create large-scale systems for industrial automation, energy management, transportation and telecommunications, apart from realizing why a distributed system architecture is essential for eliminating data bottlenecks and achieving massive scalability.
The company last year launched its Edgeline EL10 and EL20 IoT gateways that execute data processing and control functions at the edge of the network. Ideal for energy, telecommunications, transportation and industrial applications, the EL1000 and EL4000 are specifically designed for deployment in unattended, remote sites where space and power are a premium. They are small in size and use fewer components, for greater reliability and energy efficiency.
These gateways are built to withstand shock, vibration and extreme temperatures, for operation in harsh industrial environments or outdoor settings. They support Integrated Lights-Out (iLO) management for remote monitoring and troubleshooting and fewer site visits, and feature a modular product design for easy component replacement in the field.
The HPE Edgeline EL1000 and HPE Edgeline EL4000 Systems deliver data center-level compute and control to the edge through HPE IoT technology, leading the move from data center to the edge, enabling IoT insights and action, which may not have been possible before.
These rugged, compact systems provide immediate data insights from the IoT devices, enabling businesses to make real-time decisions, adding value to their operational processes that result in better business outcomes.
As these systems are engineered to handle data center-level compute, which enable
immediate access to insights—on premise, where decisions need to be made. HPE IoT
Edgeline computing addresses latency, bandwidth, cost, security, duplication, corruption and compliance issues, enabling three critical components of savings and
success—time, money, and time to action.
The converged function in the Edgeline EL1000 and Edgeline EL4000 Systems brings new and distinct business values to the edge, offering integrated components which can afford higher speed operations and compute; deep open x86 compute, precision data capture and control with open PXI standards, and enterprise class systems and device management.
It also includes HPE Vertica in-database machine-learning algorithms which deliver a range of IoT data analytics use cases. Its compact size and footprint fits in physically constrained space environments, while its ruggedized form factor is designed for
usage in harsher environments.
The line consumes lower energy as it uses shared infrastructure in a converged box that reduces energy consumption; higher quality as fewer components means
less chance of failure and reduced cost since shared infrastructure in a
converged box lowers the product cost.
The Edgeline EL1000 and Edgeline EL4000 systems deliver high-density compute and storage functionality at the edge of the network for improved performance and resiliency. These compact, converged platforms capture and analyze massive data sets, execute business logic and exert intelligent control over IoT endpoints—without communicating with central applications running in the cloud or data center.
By eliminating wide area network (WAN) latency, the EL1000 and EL4000 enable rapid response and control. For example, in an intelligent transportation control system application, a field controller can instantaneously decelerate a train based on a series of track-side sensor readings. The autonomous system design also enables continued local operation in the event of WAN outages or data center problems.