It adjusts service deployment based on the VM monitoring performance indicators (such as CPU, memory usage rate, inbound and outbound network flow), which can customize the alarm trigger policy. When the workloads drive the indicators to the threshold value, the VM instances will be automatically added or decreased based on the set policy, so as to flexibly respond to workload changes and improve the resource utilization rate.
In the case of predictable workload changes, a scheduled task can be set up to plan for the resources increase/decrease in advance. Periodic tasks can be configured to automatically increase or decrease the VM instances on a scheduled basis, so as to flexible respond to workload changes and improve the resource utilization rate. When periodic demand fluctuates, the alarm scaling mode can also be configured to deal with unpredictable changes.
The VM instances added by alarm and scheduled policies can directly associate with the existing Load Balancer to share the service flow and improve service availability.
This feature enables the users to view all the scaling activities that have been performed by the Scaling Policy (automatically/manually increase or decrease the Virtual Machines), including the cause, status and result details of scaling, with query history by time supported
There are capacity scaling demands at the business logic layer of web service, such as e-commerce website, video website and online education. Client requests reach the application server through Load Balancer. In case of substantial and rapid fluctuations of business visits, the Auto Scaling Service can flexibly increase or decrease the number of servers based on the requests and workloads.
Service computing node expansion and reduction. The computing nodes of distributed big data, data processing and other backend computing clusters, adjust the quantity of cluster servers in real time according to the size of computation, or set periodic timed tasks according to the execution time of scripts preset by the cluster, automatically create a batch of Virtual Machines before executing the scripts, and assure the high efficiency of operation.
Deployment of business server clusters, including RTS, data collection and retrieval; For such business with obvious timeliness, the scaling tasks can be rapidly completed with the Auto Scaling Service.
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