SCPERF02-BP03 Use edge compute capabilities for supply chain applications - Supply Chain Lens
Implementation guidance

SCPERF02-BP03 Use edge compute capabilities for supply chain applications

AWS offers a robust suite of edge computing solutions that extend cloud capabilities closer to end users, devices, and on-premises locations. At the core of AWS's edge computing strategy are two main services: AWS Outposts and AWS Local Zones.

Desired outcome: These edge compute capabilities enable a single-digit millisecond latency for applications like supply chain which needs real-time edge data to perform machine learning inferences and action autonomously without pushing the decision making at the cloud.

Benefits of establishing this best practice: Agility, performance, and low latency.

Level of risk exposed if this best practice is not established: High

Implementation guidance

AWS offers a robust suite of edge computing solutions that extend cloud capabilities closer to end users, devices, and on-premises locations. At the core of AWS's edge computing strategy are two main services: AWS Outposts and AWS Local Zones. AWS Outposts brings native AWS services, infrastructure, and operating models to virtually any datacenter or on-premises facility. It's ideal for workloads requiring low latency access to on-premises systems, local data processing, or data residency requirements. AWS Local Zones are infrastructure deployments that place compute, storage, database, and other AWS services closer to large population and industry centers. Local Zones act as an extension of an AWS Region, connected through high-bandwidth, secure connections.

Implementation steps

  1. Assess supply chain operations to identify use cases that require low-latency processing or local data residency.

  2. Deploy AWS Outposts for on-premises workloads that need AWS services with local data processing capabilities.

  3. Implement AWS Local Zones for applications requiring ultra-low latency access to end users or manufacturing facilities.

  4. Configure AWS IoT Greengrass for edge devices to enable local data processing and autonomous decision-making capabilities.

  5. Establish secure connectivity between edge locations and central cloud infrastructure to maintain data synchronization.

  6. Monitor edge computing performance and optimize resource allocation to facilitate efficient operation across distributed locations.