LSPERF15-BP02 Deploy synthetic transaction monitoring and real user monitoring with automated performance optimization
Implement synthetic monitoring methods that continuously simulate critical clinical workflows such as record retrieval, patient monitoring data transmission, and medication order processing to measure end-to-end latency and automatically trigger optimization actions when thresholds are exceeded. Use real user monitoring (RUM) techniques to capture actual network performance experienced by clinicians and implement adaptive optimization that adjusts network configurations based on real-time performance data, such as switching to alternate network paths or increasing bandwidth allocation for degraded connections.
Desired outcome: You have an integrated monitoring system combining synthetic testing and real user monitoring that automatically detects and responds to performance issues in clinical workflows. This enables proactive optimization of network performance and provides reliable operation of critical healthcare applications.
Level of risk exposed if this best practice is not established: Medium
Implementation guidance
Establish comprehensive synthetic monitoring for critical clinical workflows, including automated tests for record retrieval and patient data transmission. Configure monitoring scenarios that simulate real clinical activities with defined performance thresholds. Implement automated response mechanisms that trigger optimization actions when performance degrades below acceptable levels.
Deploy RUM solutions to capture actual performance metrics experienced by clinical users across different locations and devices. Set up data collection for key performance indicators including page load times, API response times, and network latency. Create performance baselines that reflect real-world usage patterns in clinical environments.
Design automated optimization systems that respond to both synthetic and RUM data. Implement intelligent routing algorithms that can automatically adjust network paths based on performance metrics. Establish bandwidth allocation rules that dynamically adapt to changing network conditions and clinical priorities.
Create comprehensive alerting mechanisms that identify performance issues before they impact clinical operations. Implement automated remediation procedures for common performance issues. Establish escalation paths for situations requiring manual intervention.
Implementation steps
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Establish comprehensive synthetic monitoring by deploying Amazon CloudWatch Synthetics with canaries simulating clinical workflows, AWS X-Ray traces for performance tracking, and custom metrics to measure healthcare-specific application performance.
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Implement real user monitoring (RUM) with CloudWatch RUM for real-time clinical application data collection, performance monitoring agents on user devices, and client-side monitoring to track user experience metrics.
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Deploy performance optimization tools including AWS Global Accelerator for automatic path optimization, Application Auto Scaling to adjust resources based on demand, and AWS Transit Gateway for intelligent network traffic routing.
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Create integrated monitoring and alerting with CloudWatch dashboards visualizing synthetic and RUM metrics, Amazon EventBridge rules automating responses to performance issues, and Amazon SNS notifications providing rapid response to critical alerts.
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Document performance baselines specific to clinical workflows and establish escalation procedures for different severity levels of performance degradation.
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Implement regular performance reviews to identify optimization opportunities and validate monitoring coverage across critical healthcare applications.
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Configure automated remediation for common performance issues to minimize impact on clinical operations.