View a markdown version of this page

TELCOOPS09-BP01 Implement comprehensive performance monitoring and baseline testing that accounts for shared infrastructure characteristics - Telco Lens
Implementation guidanceResources

TELCOOPS09-BP01 Implement comprehensive performance monitoring and baseline testing that accounts for shared infrastructure characteristics

To address the challenges of performance baselining in cloud environments with shared resources (like Nitro-based instances), organizations should implement comprehensive monitoring and testing strategies that account for various load conditions. This includes monitoring instance-level metrics, understanding resource allocation limits, and conducting performance tests under different multi-tenant scenarios. Organizations should also leverage available performance metrics and tools to understand resource utilization patterns and verify accurate capacity planning that accounts for shared infrastructure characteristics.

Desired outcome:

  • Accurate performance baselines.

  • Reliable capacity planning.

  • Comprehensive monitoring.

  • Performance predictability.

  • Resource optimization.

  • Early issue detection.

Common anti-patterns:

  • Inconsistent performance metrics.

  • Missing baseline data.

  • Poor monitoring coverage.

  • Inadequate testing scenarios.

  • No consideration of multi-tenancy.

  • Unrealistic benchmarks.

  • Lack of historical analysis.

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

Implementation guidance

Establish a holistic performance monitoring framework that accounts for the unique characteristics of shared cloud infrastructure and telecommunication workloads. Develop comprehensive baseline testing procedures that capture performance metrics across different load conditions, time periods, and infrastructure configurations to create reliable performance profiles. Implement continuous monitoring solutions that track key performance indicators while accounting for multi-tenant impacts and resource contention scenarios. Create analysis frameworks that combine historical trends, real-time metrics, and predictive analytics to enable proactive performance optimization and capacity planning.

Implementation steps

  • Deploy Amazon CloudWatch for metric collection and Amazon Managed Grafana for visualization.

  • Configure AWS X-Ray for distributed tracing and Amazon Managed Service for Prometheus for metric storage.

  • Use Amazon CloudWatch Synthetics for performance testing and AWS Lambda for custom test execution.

  • Implement Amazon OpenSearch Service for log analytics and Quick for performance analytics.

  • Deploy AWS Systems Manager OpsCenter for performance issue management and AWS Compute Optimizer for resource optimization.

Resources

Key AWS services: