BullSequana Edge delivers powerful AI inference and real-time analytics at the edge while keeping data safe and secure
Analysts estimate that by the end of 2020, 20 billion IoT devices will be deployed worldwide
Edge computing is becoming a priority in the Internet of Things. The exponential growth of intelligent sensors and devices is generating an unprecedent amount of data.
It is a new IT revolution, meaning a combination of traditional data centers and edge computing are necessary to provide powerful analytics and machine learning inference capabilities where needed.
BullSequana Edge has been designed to meet these challenges, delivering powerful AI inference and streaming analytics capabilities at the edge while ensuring that all data remains safe and secure.
Analysts expect that by 2022, up to 75% of data will be produced and processed right at the edge of the networks
10 reasons why BullSequana Edge is your best choice for edge computing
Optimal physical and logical security
The BullSequana Edge is equipped with an Intrusion Sensor which disables the system when opened. There is no physical console port to which a local intruder could connect a screen. A secure boot process can be put in place including signed firmware, bootloader, OS and applications, protected by a FIPS140-2 certified TPM and encrypted disks.
Designed to accelerate Edge Data Analytics with hyperconverged infrastructures
BullSequana Edge has been designed to enable open source based hyperconverged infrastructure solutions which enable flexible resource sharing between nodes, centralized management and security hardening.
Streaming Analytics solutions such as Spark and Kafka can flexibly be deployed on this stack. Through its powerful GPUs BullSequana Edge also supports accelerated machine learning algorithms enabled by RAPIDS and similar frameworks.
Low latency and response times for complex AI video inference models
Video & IoT analysis in real-time thanks to powerful AI inference. The server is equipped of 2 Nvidia Tesla 4 GPUs and a powerful 16 core Intel® Xeon® D processor for fast analysis.
It features extended temperature from 0° to 48°, shocks and vibration, while keeping its performance.
Outstanding energy efficiency for AI inference
9 TFLOP/Watt thanks to the careful choice of optimized components.
The server is designed to fit perfectly in any type of environment. It can be placed in stand alone, in a rack or on a wall (DIN rail or VESA wall).
The BullSequana Edge can communicate via radio, 4G, LTE or Wi-Fi and can thus be be fully independent from wired networks.
No dependence on cloud and datacenter availability and connectivity, ensures that apps are not disrupted in case of limited or intermittent network connectivity from undergrounds to offshore platforms.
Both multi-source and multi-format data can be analyzed in real-time. 9 TFLOP/Watt thanks to the careful choice of optimized components.
Reduced datacenter infrastructure and networking costs.
Edge computing solutions
Edge Computer Vision
The Atos Edge Computer Vision is a complete environment running on BullSequana Edge and dedicated to deliver computer vision capabilities.
Edge Data Analytics
Atos Edge Data Analytics enables organizations to improve their IoT business models with predictive and prescriptive solutions.
Edge Data Container
Atos Edge Data Container is an all-in-one solution, serving as a decentralized IT system, running at the edge.
Edge computing management and services
Atos provides end-to-end service management for BullSequana Edge, including Edge Computer Vision, Edge Data Analytics, and Edge Data Containers.
This end-to-end service enables, maintains Edge devices and provides secure access locally on both human and machine-interface level. Atos makes sure that functionality and secure connectivity are up-to-date by automatic monitoring of edge devices and identifying unusual events in real time. When needed, software updates are carried out. Most Edge services are delivered remotely.
- Requirement planning – to determine device placements, connectivity, infrastructure requirements, device SLAs, data sync, and retention policies
- Assessment – includes site assessment, security assessment, asset management, local and remote connectivity planning, and power assessment
- Edge provisioning – device and Edge identification and internetworking, remote connectivity provisioning, security,firewall and network rule configurations, device provisioning, site commissioning, and provisioning power/HVAC infrastructure
- IoT platform connectivity – secure connection to IoT platform, edge analytics, and data synchronization
- Edge management – monitoring the health of edge devices and connectivity, firmware updates, verify security measures, remote support and diagnostics, device data management, edge backups, and SLA management
- Support – on-site support, device re/de-provisioning, device calibration, network re-configuration, hardware upgrades, and spare part replacements
Mehdi Kasmi – Head of Global Offerings BullSequana Edge