Hybrid Cloud Computing
Improved IT experiences with applications closer to users
Relocating elements of an application to the edge of a network is quickly gaining popularity. This paradigm shift is possible as more robust computing machines on the edge of a network become more viable due to the decreasing cost of hardware. Adopting this paradigm means we can build distributed scalable solutions that host applications on any of the existing public and on-premise platforms. As the volume of data generated by local machines and sensors is increasing exponentially, processing the data on-premise is more affordable, reliable and secure.
We are designing infrastructure and software solutions that improve efficiency by reducing network latency and Internet bandwidth consumption. This aims to increase security and application availability by leveraging current Konica Minolta solution (such as Workplace Hub) and future services (such as Cognitive Hub) on the edge and in cloud layers.
- Real-time and low latency computing capabilities for machine learning applications
- Improving the energy performance of Internet of Things devices, robotics and machine automation services through task offloading
- Maintaining the data on-premise and guaranteeing anonymisation, hashing, and encryption of data sent to the cloud
- Containerisation, planning, deployment, monitoring and management of Cloud Native applications
OPTIMAL ORCHESTRATION OF INTELLIGENCE
IN AN HYPERCONNECTED ERA
Reducing network latency, decreasing energy consumption and the ever-growing need for internet bandwidth, improve the availability of applications and increase systems’ privacy and security. These are the key advantages of employing Distributed Cloud Intelligence (formerly known as LightEdge), the edge computing solution developed by Konica Minolta to further enhance the Cognitive Hub’s architecture.
DISTRIBUTED CLOUD INTELLIGENCE
Distributed Cloud Intelligence orchestrates containers and Virtual machines of microservices-based (e.g., Kubernetes and Docker Swarm) or Virtual Machines (e.g., Kernel-based Virtual Machines) architectures on a cloud edge infrastructure, in an SDN-enabled Cloud-edge Environment.
CLOUD EDGE: OPTIMAL ORCHESTRATION
OF INTELLIGENCE IN A
The Edge computing paradigm is a solution that changes the current cloud-centric design. As an alternative to processing all of the data in the cloud core, it advocates dedicated hardware and software technologies to relocate application elements to the edge of a network closer to users’ premises. Within the development of Konica Minolta’s Cognitive Hub, a platform of Artificial Intelligence (AI) services for the Workplace of the Future, our laboratories are devising an edge computing solution called LightEdge that will constitute the backbone of the system architecture.