MIDASUS01-BP01 Select Regions that offer services required by Manufacturing organizations that maximizes the reduction of your carbon footprint
Choose Regions with lower carbon footprint for your manufacturing workloads while meeting technical, compliance, and performance requirements.
Desired outcome: Manufacturing workloads deployed in regions that minimize carbon footprint while maintaining operational excellence, compliance requirements, and optimizing for latency to manufacturing facilities.
Benefits of establishing this best practice:
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Reduced environmental impact and energy costs for manufacturing IT operations.
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Enhanced sustainability reporting for regulatory compliance and improved brand reputation.
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Strategic alignment with carbon reduction goals prepares the organization for evolving environmental regulations in manufacturing.
Level of risk exposed if this best practice is not established: Medium
Implementation guidance
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Select cloud regions with lower carbon footprint that also satisfy your manufacturing compliance requirements, data sovereignty needs, and performance thresholds.
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Deploy manufacturing workloads on energy-efficient computing systems within these sustainable regions to maximize environmental benefits.
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Configure automatic scaling policies that align with manufacturing production patterns to verify that computing resources are only active when needed.
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Implement edge processing at manufacturing facilities to reduce data transfer volumes between factories and cloud regions.
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Use efficient data transfer mechanisms and compression techniques when moving manufacturing data between regions to minimize network impact.
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Consider hybrid deployment models for manufacturing workloads that must remain geographically close to production facilities while still benefiting from cloud sustainability features.
Implementation steps
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Carbon footprint assessment:
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Conduct an environmental impact assessment of your current manufacturing workload deployment using the AWS Customer Carbon Footprint Tool
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Map manufacturing compliance and technical requirements against available lower-carbon regions
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Create a phased migration plan for manufacturing workloads to greener regions, prioritizing non-critical applications first
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Deploy energy-efficient computing:
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Deploy EC2 Graviton instances with Auto Scaling configurations that align with production schedules and peak processing times
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Configure Amazon EC2 Auto Scaling groups based on manufacturing production patterns
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Optimize edge processing:
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Implement AWS IoT Greengrass at manufacturing facilities to optimize edge processing and reduce unnecessary data transfers
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Configure IoT rules to filter and aggregate manufacturing data at the edge
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Set up AWS DataSync for efficient transfer of required manufacturing data between regions
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Implement hybrid solutions:
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Deploy AWS Outposts or AWS Local Zones for manufacturing workloads requiring low-latency access to production facilities
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Configure AWS Direct Connect for high-throughput, low-latency connectivity between manufacturing sites and sustainable regions
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Implement Amazon S3 Transfer Acceleration for optimized cross-regional data movement when required
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Establish monitoring and governance:
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Create Amazon CloudWatch dashboards to track resource utilization and carbon metrics across regions
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Establish sustainability KPIs and monitoring dashboards to track carbon reduction progress
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Implement quarterly reviews to reassess regional deployment decisions based on sustainability performance metrics
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Continuous optimization:
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Use AWS Cost Explorer and Sustainability reports to identify further optimization opportunities
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Regularly review and update regional deployment strategy as cloud provider sustainability features evolve
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Key AWS services
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AWS Customer Carbon Footprint Tool
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Amazon EC2 Auto Scaling
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AWS Graviton
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AWS DataSync
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AWS IoT Greengrass
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AWS Outposts
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Amazon CloudWatch
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AWS Cost Explorer
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AWS Direct Connect
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AWS Local Zones