View a markdown version of this page

MIDACOST05-BP02 Implement dynamic resource provisioning - Modern Industrial Data Technology Lens

MIDACOST05-BP02 Implement dynamic resource provisioning

Enable automated resource scaling that matches manufacturing workload demands while optimizing costs. This includes implementing warm pools for faster scaling, considering application warm-up times, and aligning scaling policies with production schedules and peak processing times.

Desired outcome: Automated resource scaling that matches manufacturing workload demands while optimizing costs.

Common anti-patterns:

  • Implementing automatic scaling without considering production schedule requirements

  • Setting scaling thresholds without consulting manufacturing operations teams

  • Using the same scaling policies for both production and non-production workloads

  • Neglecting warm-up times for manufacturing applications when scaling

  • Implementing aggressive scale-in policies that could impact production monitoring

  • Not accounting for data retention requirements when scaling storage resources

  • Ignoring the impact of scaling on integrated manufacturing systems

  • Setting up dynamic provisioning without consideration for compliance requirements

Benefits of establishing this best practice:

  • Optimized resource utilization

  • Reduced manual intervention

  • Cost-efficient scaling

  • Improved responsiveness

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

Implementation guidance

Before you begin, you will need:

  • Detailed production schedules and patterns

  • Peak resource usage data by workload type

  • System warm-up and response time requirements

Key decisions needed:

  • Scaling thresholds for different manufacturing workloads

  • Resource retention periods based on production needs

  • Performance impact limits for critical systems

  • Cost optimization targets by workload type

Design your manufacturing workloads to automatically adjust resource provisioning based on current demand and production schedules. Implement a data-driven approach that correlates IT resource needs with manufacturing operations, providing appropriate safeguards for critical production systems and consideration for startup times and warm pools.

Implementation steps

  1. Define scaling metrics:

    • Production demand indicators

    • Resource utilization thresholds

    • Cost constraints

  2. Configure auto scaling policies:

    • Scale-out conditions

    • Scale-in conditions

    • Cool-down periods

  3. Implement monitoring.

  4. Set up cost tracking.

  5. Perform regular policy review and optimization.

Key AWS services

  • AWS Auto Scaling

  • Amazon EC2 Auto Scaling

  • AWS Lambda

  • Amazon CloudWatch

Resources

Related documents: