TELCOOPS06-BP01 Verify resource availability for scale-out scenarios in telecommunication workloads
If the cloud providers cannot guarantee instant EC2 instance availability, especially for large instance types commonly used in telco deployments, implement proactive capacity planning. Capacity planning can be broken into two classes: new service and run-rate.
New service planning requires cloud resources where there is no trend data to indicate a future demand profile, and the service team has no visibility to the future demand profile.
Run-rate planning indicates a stable environment where organic growth can be modeled and forecast based on service consumption.
Introduction of new services in an existing deployment requires both approaches as the composite demand is both run-rate and new service. The methods include utilizing capacity reservations, maintaining buffer capacity, and implementing predictive scaling strategies based on historical usage patterns. Organizations should also consider using a mix of instance types and sizes that can support their workloads while increasing the likelihood of resource availability during scale-out events.
Desired outcome:
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Guaranteed resource availability.
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Efficient capacity planning.
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Predictable scaling operations.
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Optimized resource utilization.
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Minimized deployment delays.
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Cost-effective scaling.
Common anti-patterns:
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Reactive capacity planning.
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No resource forecasting.
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Missing buffer capacity.
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Poor utilization tracking.
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Inadequate reservation strategy.
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No scaling limits.
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Unplanned resource constraints.
Level of risk exposed if this best practice is not established: High
Implementation guidance
Implement a comprehensive capacity management strategy that addresses both new service launches and ongoing operational needs. Create predictive scaling models that combine historical usage patterns with forecasted demand to verify adequate resource availability without over-provisioning. Develop buffer capacity policies that maintain appropriate headroom for unexpected demand spikes while considering cost implications and resource constraints. Establish regular capacity review processes that evaluate resource utilization trends, identify potential bottlenecks, and adjust capacity plans to maintain optimal performance and cost efficiency.
Implementation steps
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Use Service Quotas for limit management and AWS Compute Optimizer for resource optimization recommendations.
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Implement AWS Auto Scaling for dynamic resource adjustment and EC2 Fleet for capacity diversity.
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Deploy AWS Systems Manager Automation for scaling procedures and Amazon EventBridge for automated scaling triggers.
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Configure AWS Cost Explorer for resource cost tracking and AWS Budgets for cost management.
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Use AWS Systems Manager OpsCenter for capacity management and Amazon CloudWatch for utilization monitoring.
Resources
Key AWS services:
