Auto Scaling

Automatically Adjusts the Resource Configuration or Cluster Sizing According to the Customizable Policy and Business Requirements to Effectively Support the Real-time Business Needs while Avoiding Cost Overrun
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Auto Scaling
Manual Intervention
Automatic adjustment
Adjusts resource allocation per real-time requirement
Real-time resource monitoring
Manual or scripting adjustment
Time-consuming manual intervention
Error-prone, with potential business disruption
Cost control
Pay-per-usage, and automatic adjustment improves resource utilization and reduces costs.
Advanced resource provisioning in anticipation peak demand leads to resource and cost waste.
Automatically detects and replaces unhealthy hosts to ensure real-time service availability.
Manual response after service interruption can’t reverse negative business impact
Adjusts to workload demands through automatic scaling
Customizable scaling notification for real-time operation status
Manual configuration is costly, complex and inefficient.
Important events related to auto-scaling saved to the og to pinpoint the problem and assist issue resolution.
Problems are not traceable and root cause hard to pinpoint.


Automatic replacement
Hosts are created or deleted based on the health check from the load balancer listener.
Important events saved, and alerts sent through customizable notification channels.
Auto Scaling
Adjusts the IP throughput within a pre-set range based on the public IP monitoring data.
Autonomous expansion
Expand the disk space per the pre-set rules when the disk usage exceeds a certain threshold.
Floating number
Back-end server scaling based on the stress monitoring data from the load balancer listener.

Resource Types

Auto-scaling available to these resources
Public IP Bandwidth
Load Balancer Host
Relational Database

Use Cases

Elastic Web Applications
High-Performance Computing
Big Data

Billing Guide

Related Products

For more information on use cases and technical architecture, please contact our customer service team.
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