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Obtain resources upon detection that more resources are needed for a workload

Designing workloads that can dynamically scale in response to demand fluctuations is essential for maintaining performance and availability. By proactively acquiring resources based on workload demands, organizations can ensure a seamless user experience while optimizing resource utilization and cost.

Best Practices

  • Automated Scaling Policies: Implementing automated scaling policies allows workloads to respond instantaneously to changes in demand. Tools such as AWS Auto Scaling can be configured to monitor key metrics and add or remove instances as required, aligning resource levels with actual usage.

Supporting Questions

  • Do you have monitoring systems in place to detect changes in demand?

Roles and Responsibilities

  • Cloud Architect: Responsible for designing scalable systems that can adapt to demand changes, cloud architects ensure that resource provisioning aligns with the workload requirements, optimizing both performance and cost.

Artifacts

  • Scaling Policy Document: A document outlining the specific scaling strategies, metrics to monitor, and thresholds that trigger scaling actions, ensuring that workloads respond effectively to changes in demand.

Cloud Services

AWS

  • AWS Auto Scaling: AWS Auto Scaling allows users to automatically adjust the number of Amazon EC2 instances in a group based on demand. It simplifies the management of capacity, ensuring that applications are able to handle fluctuating workloads efficiently.

Question: How do you design your workload to adapt to changes in demand?
Pillar: Reliability (Code: REL)

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