Read the following tips and how-to sections to help you achieve your goals with Rackspace Auto Scale.

How Auto Scale works#

Rackspace Auto Scale is written in Python and calls the Rackspace Cloud Servers, Rackspace Cloud Load Balancers, and Rackspace RackConnect v3 APIs. You can use all Rackspace Cloud Server create server configuration parameters with Auto Scale. For more information about Cloud Servers and Auto Scale, see Rackspace Cloud Servers documentation, Auto Scale GitHub documentation, and the Auto Scale GitHub Wiki.

Invalid load balancers can prevent scaling#

If you create a scaling group with more than one load balancer and one of the load balancers is invalid (bad configuration), the scaling group never scales. Auto Scale goes through the following process:

  1. Create servers.

  2. Add them to the load balancers.

  3. Discover that one of the load balancers is invalid.

  4. Delete the servers.

  5. Remove the node from the valid load balancers.

Delete scaling groups with missing servers#

If you have manually deleted servers outside of Auto Scale, and you have existing servers in the group, perform the following actions:

  1. Update both the minEntities and maxEntities values to 0.

  2. Delete the group.

The following example illustrates those steps:

PUT v1.0/tenantId/groups/groupId/config
{"maxEntities": 0, "cooldown": 0, "name": "ready_to_be_deleted", "minEntities": 0, "metadata": {}}
DELETE v1.0/{tenantId}/groups/{groupId}

ServiceNet dependency can cause server creation to fail#

When you configure your Auto Scale scaling group with a load balancer, you need to include the Rackspace ServiceNet network as part of the launch configuration. You cannot have only a private network in the launch configuration.

In a scale-up operation, Auto Scale tries to retrieve the ServiceNet IP address of the server that it built to add it to the load balancer. If ServiceNet is not part of the configuration, this action fails. To recover from this failure, Auto Scale deletes the server that it built, which results in no active servers.

Avoid this problem by adding ServiceNet to the list of networks for the Auto Scale group.

Connect Auto Scale to a single Tsvld[svr] monitoring alarm#

This tip shows you how to use a webhook to trigger an Auto Scale policy. It does not explain how to create a check or an Auto Scale group. For information about creating checks and alarms, see the Rackspace Monitoring Developer Guide or the Rackspace Monitoring Checks and Alarms article.

Modify the example values used for the configurations to meet your needs. These values use the Auto Scale API to first create a webhook policy with the desired capacity of five servers and a cooldown of three minutes, and then create a webhook named Rackspace Monitoring. In steps 3, 4, and 5, you use the Rackspace Monitoring API to do the following tasks:

  • Create a notification by using the webhook URL created in step 2

  • Create a notification plan by using the webhook ID created in step 3

  • Create an alarm that uses the notification plan created in step 4.

You can do steps 3-5 through the Rackspace Intelligence UI.

  1. Create a webhook policy.

     POST/autoscale: v1.0//groups//policies
 [
 {
 "name": "set group to 5 servers",
 "desiredCapacity": 5,
 "cooldown": 1800,
 "type": "webhook"
 }
 }

  2. Create a webhook for Rackspace Monitoring under the webhook policy.

     POST/autoscale: v1.0//groups/policies//webhooks
 [
 {
 "metadata": {},
 "name": "Rackspace Monitoring"
 }
 ]

  3. Create a Rackspace Monitoring notification.

     POST/monitoring: /notifications
 {
 "label": "AutoScale",
 "type": "webhook",
 "details": {
 "url": <webhook_URL_from_AutoScale>
 }
 }

  4. Create a Rackspace Monitoring notification plan.

     POST/monitoring: /notification_plans
 {
 "label": "Notification Plan 1",
 "critical_state": [
 <notification_ID_from_AutoScale>"
 ],

 "warning_state": [
 ],
 }
 "ok_state": [
 ]
 }

  5. Create an alarm in Rackspace Monitoring.

     POST/monitoring: /entities//alarms
 '{
 "check_id": "<check_you_want_to_use>",
 "criteria": "<criteria_you_want_to_use>",
 "notification_plan_id": "<notification_plan_you_just_created>"
 }

How to add or remove servers quickly#

To quickly add servers to or remove servers from a scaling group, send a request to change the value of the minEntities or maxEntities parameter, as documented in the Update scaling group configuration section of the Rackspace Auto Scale API Developer Guide.

Following is an example request:

PUT //groups//config
{ "name": "workers",
"cooldown": 60,
"minEntities": 5,
"maxEntities": 100,
"metadata": {
"firstkey": "this is a string",
"secondkey": "1", }
}

You can remove a specific server from a scaling group by using the delete server operation. For more information, see the Delete server from scaling group section of the Rackspace Auto Scale API Developer Guide.

maxEntities and minEntities settings affect scaling#

If the number of active servers (desired capacity) in a scaling group is equal to the configured maxEntities value during a scale-up, or equal to the configured minEntities value during a scale-down, the call to execute the scaling policy returns a 400 Bad Request error response code with the message No change in servers.

If the number of active servers in a scaling group is less than the maxEntities value, the call to execute a scale-up policy returns a 200 OK response code and increases the number of servers to the maxEntities value or the amount specified.

If the number of active servers in a scaling group is greater than the minEntities value, the call to execute a scale-down policy returns a 200 OK response code and reduces the number of servers to the minEntities value or the amount specified.

Note: You can change the minEntities and maxEntities values for a scaling group by using the Cloud Control Panel. To do this, select Auto Scale from the Servers menu, select the scaling group, and then, from the Actions menu, select Edit Min / Max Servers.

Create and update the launch configuration setting#

All Auto Scale API update requests completely replace all of the settings of the updated item. The request sets any parameters not specified in the update request to null or the default value. All requests, except update launch configuration operation, validate that all required fields are provided. A failed launch configuration update returns a 400 error response code. The following examples show how to create and update a launch configuration setting. Creates uses a POST operation, and updates uses a PUT operation.

Note: Each user can have multiple Secure Shell (SSH) key pairs (name and key). The launch configuration uses the admin user’s SSH key pair name, usually the first admin user found in the tenant. If there are multiple admin accounts in the tenant, there is no guarantee as to which one is used. So it is best for there to be one admin user in the tenant. You cannot change this restriction currently. There is no option to specify a user to impersonate.

Create a scaling group with the launch configuration setting#

This example creates a scaling group with load balancers, server metadata, networks, and personality.

POST /<tenant_id>/groups
{
"launchConfiguration": {
"args": {
"loadBalancers": [
{
"port": 8080,
"loadBalancerId": 9099
}
],
"server": {
"name": "autoscale_server",
"imageRef": "0d589460-f177-4b0f-81c1-8ab8903ac7d8",
"flavorRef": "performance1-2",
OS-DCF:diskConfig": "AUTO",
"metadata": {
"build_config": "core",
"meta_key_1": "meta_value_1",
"meta_key_2": "meta_value_2"
},
"networks": [
{
"uuid": "11111111-1111-1111-1111-111111111111"
},
],
"uuid": "00000000-0000-0000-0000-000000000000"
"personality": [
{
"path": "/root/.csivh",
"contents": "VGhpcyBpcyBhIHRlc3QgZmlsZS4="
}
]
}
},
"type": "launch_server"
},
"groupConfiguration": {
"maxEntities": 10,
"cooldown": 360,
"name": "testscalinggroup198547",
"minEntities": 0,
"metadata": {
"gc_meta_key_2": "gc_meta_value_2",
"gc_meta_key_1": "gc_meta_value_1"
}
},
"scalingPolicies": [
{
"cooldown": 0,
"type": "webhook",
"name": "scale up by 1",
<"change": 1
}
]
}

Update the launch configuration setting#

This example shows how to update only the flavorRef and name parameters without the remaining fields, and a successful 204 response code.

Note. The update operation overwrites all launch configuration parameters and resets any parameters not specified in the update are to null or the default value.

PUT /<tenant_id>/groups/<group_id>/launch
{<
"type": "launch_server",
"args": {
"server": {
"flavorRef": performance1-4,
"name": "update_launch_config",
"imageRef": "0d589460-f177-4b0f-81c1-8ab8903ac7d8"
}}

Retrieve the launch configuration response. The load balancers, server’s metadata, personality, and networks are overwritten because of the preceding update.

GET /{tenant_id}/groups/{group_id}/launch (The load balancers, server's metadata, personality, and networks, are overwritten due to no load balancer, server metadata, personality, or networks, parameters being included in the update request)
{
"type": "launch_server",
"args": {
"server": {
"flavorRef": performance1-4,
"name": "update_launch_config",
"imageRef": "0d589460-f177-4b0f-81c1-8ab8903ac7d8"
}}}

Update the launch configuration eviction policy#

When a launch configuration setting is updated, the servers that scale up after the update use the latest launch configuration settings.

A scale-down that occurs after the launch configuration setting has been updated deletes servers with the older launch configuration setting first. The only exception to this is when servers are building. Auto Scale attempts to first delete servers being built (pending) in a scale-down policy execution, then servers with the older launch configuration setting, and lastly, any other servers required by the scale-down policy.

Delete servers#

Deleting servers requires an Auto Scale Python call to the Rackspace Cloud Servers Nova-based API. This section discusses how the Cloud Servers API deletes servers and how to delete a specific server from a scaling group.

About the server “Active” state when deleting servers#

When a scale-down policy executes, servers in the Active state are deleted immediately because Nova, the software behind Rackspace Cloud Servers, is aware of those servers. Auto Scale issues deletes for Pending servers first, but Nova executes deletes for Active servers first. Thus, for a time, you might see servers in the Control Panel that you have deleted; the inter-programming communication and executions cause a lag. For example, if a scale-up policy is executing to build five servers and, while the servers are still building, a scale-down policy executes to scale down by two servers, you might see five servers in the Control Panel until they finish building and go into the Active state. Then, the system deletes the two servers.

Delete a specific server from a scaling group#

You can remove a specific server from a scaling group by using the delete server operation. For more information, see the Delete server from scaling group section Rackspace Auto Scale API Developer Guide.

Choose the flavor of a server for a scaling group#

If you create an image of a server and use that image to create a scaling group, you must choose a flavor in the scaling group that is equal to, or greater than, the capacity of the flavor of the server used to create the image. For more information about available server flavors, see Flavors in the Cloud Servers API documentation.

Cloud bursting with Auto Scale and RackConnect#

Auto Scale and RackConnect allow bursting into the public cloud from events in a dedicated environment. Provision RackConnect by setting a metadata flag for a RackConnect group in the Auto Scale launch configuration metadata section (see the following example). When you set that section properly and Auto Scale scales up a group, RackConnnect modifies the new server to disable its public interface, and it begins receiving Private Cloud traffic from the RackConnect load balancer. For more details, see Cloud Bursting using Auto Scale RackConnect and F5 Load Balancers.

Example RackConnect metadata key and value pair for Auto Scale:

"metadata": {
"RackConnectLBPool": "MyRCPoolName"
}

Use Auto Scale to change the size of your General Purpose or work-optimized server#

General Purpose and work-optimized servers do not resize as simply as Standard servers. You have to go through a process to resize, detailed in Upgrading resources for General Purpose or I/O optimized Cloud Servers, to resize, and your server does not keep its IP address. You can use Auto Scale to accomplish server resizing, keeping your IP address, and have it happen dynamically in response to load. You pay for the higher-flavor servers (for example, General Purpose and work-optimized) only when you need them. When you don’t need them, you can scale back down to lower-flavor servers (for example, Standard), or keep the higher-flavor servers and just scale back the number of servers in your group.

When you’re ready to set up your scaling system to resize servers dynamically, use the following guidelines.

  1. Create two scaling groups: One with a lower flavor for the server setting in the launchConfiguration option and another with a higher flavor server setting in the launchConfiguration option. Configure both scaling groups with the same image and load balancer.

  2. Create two policies for each scaling group:

    • One policy with desiredCapacity=0

    • One with desiredCapacity=2 or 3 (that is, scale up by 2 or 3)

When you want a higher-flavor server, execute the scale-up policy on with the higher-flavor scaling group and the desiredCapacity=0 policy on the lower-flavor group. Do the opposite when switching from a higher flavor to a lower flavor.

This technique works well for single-server deployments. In fact, for smaller deployments, the scale-up policy might just be +1 instead of 2 or 3.

One disadvantage of this technique is being charged for a load balancer when you don’t need it. However, you can offset that cost by the scaling down, using lower-flavor (and less expensive) servers when the load is lighter.