Rackspace Auto Scale overview
Last updated on: 2020-09-28
Authored by: Maria Abrahms
Rackspace Auto Scale automatically scales resources allocated to your application up or down based on user-defined needs. You can base scaling events on scaling rules that you define through your monitoring system or on a simple schedule that you configure.
How Is Auto Scale used?
Scaling is triggered either by webhooks that are placed in monitoring services or by a schedule. An Auto Scale group, or scaling group, consists of the following items:
- Scaling group configuration: Includes the group name, cooldown time limit, and minimum and maximum number of needed servers.
- Launch configuration: Determines the server creation actions to take after an Auto Scale trigger event by specifying which image to start and which load balancer to attach to the server.
- Scaling policy: Defines the action of the policy (for example, scale up by 5 servers).
- Webhook (capability-based URL): Triggers a scaling policy (for example, “When this URL is hit, execute this scaling policy.").
- eCommerce sale Customer W has a one-day sale on their site on Monday, that begins at 12:01 a.m. Monday and ending at 12:00 a.m. Tuesday. The customer predicts substantially increased traffic due to this sale. The customer can create a schedule-based policy to add ten servers to its pool starting at 11:45 p.m. Sunday, giving the system enough time to create, configure, and add the servers to the load balancer. The customer can create a second schedule to decrease the number of servers by ten starting at 12:00 a.m. Tuesday morning, after the sale has ended.
- Marketing campaign Similar to the preceding use case, Customer X is running a week-long marketing campaign and expects 20 percent more traffic to its website. The campaign begins at 7:00 a.m. EST on Monday and ends at 7:00 p.m. EST on Friday. The customer can create a schedule-based policy to increase the number of servers in their pool by 20 percent starting at 6:30 a.m. EST on Monday, giving the system enough time to create, configure, and add the servers to the load balancer. The customer can create a second schedule-based policy to decrease the number of servers by 20 percent at 7:00 p.m. EST on Friday.
- Known traffic fluctuations Customer Y notices that traffic to their website decreases by 15 percent every weekend. That is, traffic decreases every Friday night and returns to normal on Monday morning. The customer can create a recurring schedule-based policy to decrease the number of servers by 15 percent, starting at 6:00 p.m. every Friday. The customer can also create a second schedule-based policy to increase the number of servers by 15 percent every Monday at 6:00 a.m.
- Integration with Monitoring Customer Z has unpredictable traffic when publishing blog posts. The customer already monitors the environment with Nagios®. The customer creates a scaling policy to add ten percent more servers with a webhook. The customer then creates a Nagios alert to trigger the webhook when traffic exceeds 6000 requests per minute. The customer creates a second policy to return the servers to the baseline when the spike decreases.