AS Advantages

Automatic Resource Scaling

AS adds ECS instances for your applications when the access volume increases and removes unneeded resources when the access volume drops, ensuring system stability and availability.

• Scaling ECS Instances on Demand

  AS scales ECS instances for applications based on demand, improving cost management. ECS instances can be scaled dynamically, on a schedule, or manually:

  • Dynamic scaling

    Dynamic scaling allows scale resources in response to changing demand using alarm-based policies. For details, see Dynamic Scaling.

  • Scheduled scaling

    Scheduled scaling helps you set up your scaling schedule according to predictable load changes by creating periodic or scheduled policies. For details, see Scheduled Scaling.

  • Manual scaling

    You can either manually change the expected number of instances of your AS group, or add or remove instances to or from the AS group. For details, see Manual Scaling.

  Consider a train ticket booking application running on the cloud. The load of the application may be relatively low during Q2 and Q3 because there are not many travelers, but relatively high during Q1 and Q4. Traditionally, there are two ways to plan for these changes in load. The first option is to provide enough servers so that the application always has enough capacity to meet demand, as shown in Figure 1. The second option is to provision servers according to the average load of the application, as shown in Figure 2. However, these two options may waste resources or be unable to meet demand during peak seasons. By enabling AS for this application, you have a third option available. AS helps you scale servers to keep up with changes in demand. This allows the application to maintain steady, predictable performance without wasting money on any unnecessary resources, as shown in Figure 3.

  Figure 1 Over-provisioned capacity
  
  Figure 2 Insufficient capacity
  
  Figure 3 Auto-scaled capacity
  
• Scaling Bandwidth on Demand

  AS adjusts bandwidth for an application based on demand, reducing bandwidth costs.

  There are three types of scaling policies you can use to adjust the IP bandwidth on demand:

  • Alarm-based policies

    You can configure triggers based on metrics such as outbound traffic and bandwidth. When the system detects that the triggering conditions are met, the system automatically adjusts the bandwidth.

  • Scheduled policies

    The system automatically increases, decreases, or adjusts the bandwidth to a fixed value on a fixed schedule.

  • Periodic policies

    The system periodically adjusts the bandwidth based on a configured periodic cycle.

  For example, you can use an alarm-based policy to regulate the bandwidth for a livestreaming website.

  For a livestreaming website, service load is difficult to predict. In this example, the bandwidth needs to be dynamically adjusted between 10 Mbit/s and 30 Mbit/s based on metrics such as outbound traffic and inbound traffic. AS can automatically adjust the bandwidth to meet requirements. You just need to select the relevant EIP and create two alarm policies. One policy is to increase the bandwidth by 2 Mbit/s when the outbound traffic is greater than X bytes, with the limit set to 30 Mbit/s. The other policy is to decrease the bandwidth by 2 Mbit/s when the outbound traffic is less than X bytes, with the limit set to 10 Mbit/s.

Enhanced Cost Management

AS enables you to use ECS instances on demand by automatically scaling resources for your applications, eliminating waste of resources and reducing costs.

Higher Availability

AS ensures that you always have the right amount of resources available to handle the fluctuating load of your applications.

Using ELB with AS

Working with ELB, AS automatically scales ECS instances based on changes in demand while ensuring that the load of all the instances in an AS group stays balanced.

After ELB is enabled for an AS group, AS automatically associates a load balancing listener with any instances added to the AS group. Then, ELB automatically distributes traffic to all healthy instances in the AS group through the listener, which improves system availability. If the instances in the AS group are running a range of different types of applications, you can bind multiple load balancing listeners to the AS group to listen to each of these applications, improving service scalability.

High Fault Tolerance

AS monitors instances in an AS group, and replaces any unhealthy instances it detects with new ones.