Horizontal Pod Autoscaling (HPA) governs the spinning up of additional pods when the existing resources (CPU and Memory) of the microservice are exhausted. The deletion of the additional pods occurs as and when the resources are free or restored for the microservice. In Adeptia Connect, Autoscaling is by default enabled. You can enable HPA in Adeptia Connect by setting the required parameters in the global values.yaml file.
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Synchronous requests are processed by any random runtime pod that is selected by Kubernetes Service when set to its default iptables proxy mode.
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For Synchronous API requests, Adeptia Connect checks for the readiness of the runtime pod by using the the following two threshold properties.
- readiness.probe.cpu.threshold
- readiness.probe.memory.threshold
| Property | Description |
|---|---|
| readiness.probe.cpu.threshold | Threshold value for CPU utilization (measured against the allocated CPU request) in percentage beyond which the pod will not accept any more requests to process. You can keep the property value blank to skip this threshold check. |
| readiness.probe.memory.threshold | Threshold value for memory utilization (measured against the allocated memory request) in percentage beyond which the pod will not accept any more requests to process. You can keep the property value blank to skip this threshold check. |
You can find these properties at Account >Settings >Microservice Settings >Runtime >Readiness Probe Configuration. To know how to configure these properties, refer to the page Configuring the application properties.
The Asynchronous requests are processed based on the concurrency level you set for the runtime pods of the Deployment. For example, if there are three (3) runtime pods (each having a concurrency of 5) and eight (8) messages in the Queue, here is how they will be routed:
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