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Copy file name to clipboardExpand all lines: articles/healthcare-apis/fhir/fhir-service-autoscale.md
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@@ -15,7 +15,7 @@ Azure Health Data Services provides a managed service for persisting FHIR-compli
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Autoscaling is a capability to dynamically scale your FHIR service based on the load reported. The FHIR service in Azure Health Data Services provides the built-in autoscale capability and the process is automated. The capability provides elasticity and enables provisioning of additional instances for customers FHIR service on demand.
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The autoscaling feature adjusts computing resources automatically to optimize service scalability. There is no action required from customers.
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The autoscaling feature adjusts computing resources automatically to optimize service scalability. There's no action required from customers.
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The autoscaling feature for FHIR service is available in all regions where the FHIR service is supported.
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> [!NOTE]
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* Scaling mechanism
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Scaling Mechanism describes how scaling will be performed when it is triggered. Mechanism is only applied when the conditions from the trigger are met.
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Scaling Mechanism describes how scaling will be performed when it's triggered. Mechanism is only applied when the conditions from the trigger are met.
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There are three factors that determine when the service will be scaled:
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* Lower load threshold is a value that determines when the service will be scaled in. If the average load of all instances is lower than 20% of CPU usage then the service will be scaled in.
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* Scaling interval
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Scaling Interval is used determines how often the trigger will be checked. Once the trigger is checked, if scaling is needed the mechanism will be applied. If
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scaling is not needed, then no action will be taken. In both cases, trigger will not be checked again before scaling interval expires again. Scaling interval is
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scaling isn't needed, then no action will be taken. In both cases, trigger won't be checked again before scaling interval expires again. Scaling interval is
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