Overview of Edge computing
IBM Edge Computing for Devices delivers edge node management that minimizes deployment risks and manages the service software lifecycle on edge nodes fully autonomously. This function creates the capacity to achieve meaningful insights more rapidly from data that is captured closer to its source. IBM Edge Computing is available for infrastructure or servers, including distributed devices.
Intelligent devices are being integrated into the tools that are used to conduct business at an ever-increasing rate. Device compute capacity is creating new opportunities for data analysis where data originates and actions are taken. IBM Edge Computing innovations fuel improved quality, enhance performance, and drive deeper, more meaningful user interactions.
IBM Edge Computing can:
- Solve new business problems by using Artificial Intelligence (AI)
- Increase capacity and resiliency
- Improve security and privacy protections
- Leverage 5G networks to reduce latency
IBM Edge Computing can capture the potential of untapped data that is created by the unprecedented growth of connected devices, which opens new business opportunities, increases operational efficiency, and improves customer experiences. IBM Edge Computing brings Enterprise applications closer to where data is created and actions need to be taken, and it allows Enterprises to leverage AI and analyze data in near-real time.
IBM Edge Computing benefits
IBM Edge Computing helps solve speed and scale challenges by using the computational capacity of edge devices, gateways, and networks. This function retains the principles of dynamic allocation of resources and continuous delivery that are inherent to cloud computing. With IBM Edge Computing, businesses have the potential to virtualize the cloud beyond data centers. Workloads that are created in the cloud can be migrated towards the edge, and where appropriate, data that is generated at the edge can be cleansed and optimized and brought back to the cloud.
IBM Edge Computing for Devices spans industries and multiple tiers that are optimized with open technologies and prevailing standards like Docker and Kubernetes. This includes computing platform, both private cloud and Enterprise environments, network compute spaces and on-premises gateways, controllers and servers, and intelligent devices.
Centrally, the hyper-scale public clouds, hybrid clouds, colocated managed data centers and traditional Enterprise data centers continue to serve as aggregation points for data, analytics, and back-end data processing.
Public, private, and content-delivery networks are transforming from simple pipes to higher-value hosting environments for applications in the form of the edge network cloud.
IBM Edge Computing capabilities
- Hybrid cloud computing
- 5G networking
- Edge server deployment
- Edge servers compute operations capacity
- IoT devices support and optimization
- Mobile device support
IBM Edge Computing risks and resolution
Although IBM Edge Computing creates unique opportunities, it also presents challenges. For example, it transcends cloud data center's physical boundaries, which can expose security, addressability, management, ownership, and compliance issues. More importantly, it multiplies the scaling issues of cloud-based management techniques.
Edge networks increase the number of compute nodes by an order of magnitude. Edge gateways increase that by another order of magnitude. Edge devices increase that number by 3 to 4 orders of magnitude. If DevOps (continuous delivery and continuous deployment) is critical to managing a hyper-scale cloud infrastructure, then zero-ops (operations with no human intervention) is critical to managing at the massive scale that IBM Edge Computing represents.
It is critical to deploy, update, monitor, and recover the edge compute space without human intervention. All of these activities and processes must be fully automated, capable of making decisions independently about work allocation, and able to recognize and recover from changing conditions without intervention. All of these activities must be secure, traceable, and defensible.
Extending multi-cloud deployments to the edge
IBM Multicloud Manager unifies cloud platforms from multiple vendors into a consistent dashboard from on-premises to the edge. IBM Edge Computing for Devices is a natural extension that enables the distribution and management of workloads beyond the edge network to edge gateways and edge devices.
IBM Multicloud Manager recognizes workloads from Enterprise applications with edge components, private and hybrid cloud environments, and public cloud; where IBM Edge Computing provides a new execution environment for distributed AI to reach critical data sources.
IBM Multicloud Manager-CE delivers AI tools for accelerated deep learning, visual and speech recognition, and video and acoustic analytics, which enables inferencing on all resolutions and most formats of video and audio conversation services and discovery.
IBM Multicloud Manager benefits
- Enable transformation in the industries such as telecommunications, manufacturing, retail, and automotive
- Enable AI and analytics deployment to edge devices, gateways, operations controllers, and other compute locations
- Facilitate and position 5G players to capture higher value within their network infrastructure by virtualizing network functions and creating new compute opportunities for Enterprise solutions