docs: update generated docs (#1053)
Updates for both discovery docs and epydoc API Documentation
Fixes: #1049
diff --git a/docs/dyn/compute_beta.regionAutoscalers.html b/docs/dyn/compute_beta.regionAutoscalers.html
index 38dcb59..e0e2e93 100644
--- a/docs/dyn/compute_beta.regionAutoscalers.html
+++ b/docs/dyn/compute_beta.regionAutoscalers.html
@@ -75,6 +75,9 @@
<h1><a href="compute_beta.html">Compute Engine API</a> . <a href="compute_beta.regionAutoscalers.html">regionAutoscalers</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
+ <code><a href="#close">close()</a></code></p>
+<p class="firstline">Close httplib2 connections.</p>
+<p class="toc_element">
<code><a href="#delete">delete(project, region, autoscaler, requestId=None)</a></code></p>
<p class="firstline">Deletes the specified autoscaler.</p>
<p class="toc_element">
@@ -84,7 +87,7 @@
<code><a href="#insert">insert(project, region, body=None, requestId=None)</a></code></p>
<p class="firstline">Creates an autoscaler in the specified project using the data included in the request.</p>
<p class="toc_element">
- <code><a href="#list">list(project, region, filter=None, maxResults=None, orderBy=None, pageToken=None)</a></code></p>
+ <code><a href="#list">list(project, region, filter=None, maxResults=None, orderBy=None, pageToken=None, returnPartialSuccess=None)</a></code></p>
<p class="firstline">Retrieves a list of autoscalers contained within the specified region.</p>
<p class="toc_element">
<code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p>
@@ -100,6 +103,11 @@
<p class="firstline">Updates an autoscaler in the specified project using the data included in the request.</p>
<h3>Method Details</h3>
<div class="method">
+ <code class="details" id="close">close()</code>
+ <pre>Close httplib2 connections.</pre>
+</div>
+
+<div class="method">
<code class="details" id="delete">delete(project, region, autoscaler, requestId=None)</code>
<pre>Deletes the specified autoscaler.
@@ -206,6 +214,7 @@
#
# Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
"cpuUtilization": { # CPU utilization policy. # Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.
+ "predictiveMethod": "A String", # Indicates which method of prediction is used for CPU utilization metric, if any. Current set of possible values: * NONE: No predictions are made based on the scaling metric when calculating the number of VM instances. * OPTIMIZE_AVAILABILITY: Standard predictive autoscaling predicts the future values of the scaling metric and then scales a MIG to ensure that new VM instances are ready in time to cover the predicted peak. New values might be added in the future. Some of the values might not be available in all API versions.
"utilizationTarget": 3.14, # The target CPU utilization that the autoscaler should maintain. Must be a float value in the range (0, 1]. If not specified, the default is 0.6.
#
# If the CPU level is below the target utilization, the autoscaler scales down the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization.
@@ -339,6 +348,7 @@
#
# Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
"cpuUtilization": { # CPU utilization policy. # Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.
+ "predictiveMethod": "A String", # Indicates which method of prediction is used for CPU utilization metric, if any. Current set of possible values: * NONE: No predictions are made based on the scaling metric when calculating the number of VM instances. * OPTIMIZE_AVAILABILITY: Standard predictive autoscaling predicts the future values of the scaling metric and then scales a MIG to ensure that new VM instances are ready in time to cover the predicted peak. New values might be added in the future. Some of the values might not be available in all API versions.
"utilizationTarget": 3.14, # The target CPU utilization that the autoscaler should maintain. Must be a float value in the range (0, 1]. If not specified, the default is 0.6.
#
# If the CPU level is below the target utilization, the autoscaler scales down the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization.
@@ -513,7 +523,7 @@
</div>
<div class="method">
- <code class="details" id="list">list(project, region, filter=None, maxResults=None, orderBy=None, pageToken=None)</code>
+ <code class="details" id="list">list(project, region, filter=None, maxResults=None, orderBy=None, pageToken=None, returnPartialSuccess=None)</code>
<pre>Retrieves a list of autoscalers contained within the specified region.
Args:
@@ -533,6 +543,7 @@
Currently, only sorting by `name` or `creationTimestamp desc` is supported.
pageToken: string, Specifies a page token to use. Set `pageToken` to the `nextPageToken` returned by a previous list request to get the next page of results.
+ returnPartialSuccess: boolean, Opt-in for partial success behavior which provides partial results in case of failure. The default value is false and the logic is the same as today.
Returns:
An object of the form:
@@ -558,6 +569,7 @@
#
# Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
"cpuUtilization": { # CPU utilization policy. # Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.
+ "predictiveMethod": "A String", # Indicates which method of prediction is used for CPU utilization metric, if any. Current set of possible values: * NONE: No predictions are made based on the scaling metric when calculating the number of VM instances. * OPTIMIZE_AVAILABILITY: Standard predictive autoscaling predicts the future values of the scaling metric and then scales a MIG to ensure that new VM instances are ready in time to cover the predicted peak. New values might be added in the future. Some of the values might not be available in all API versions.
"utilizationTarget": 3.14, # The target CPU utilization that the autoscaler should maintain. Must be a float value in the range (0, 1]. If not specified, the default is 0.6.
#
# If the CPU level is below the target utilization, the autoscaler scales down the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization.
@@ -721,6 +733,7 @@
#
# Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
"cpuUtilization": { # CPU utilization policy. # Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.
+ "predictiveMethod": "A String", # Indicates which method of prediction is used for CPU utilization metric, if any. Current set of possible values: * NONE: No predictions are made based on the scaling metric when calculating the number of VM instances. * OPTIMIZE_AVAILABILITY: Standard predictive autoscaling predicts the future values of the scaling metric and then scales a MIG to ensure that new VM instances are ready in time to cover the predicted peak. New values might be added in the future. Some of the values might not be available in all API versions.
"utilizationTarget": 3.14, # The target CPU utilization that the autoscaler should maintain. Must be a float value in the range (0, 1]. If not specified, the default is 0.6.
#
# If the CPU level is below the target utilization, the autoscaler scales down the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization.
@@ -951,6 +964,7 @@
#
# Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
"cpuUtilization": { # CPU utilization policy. # Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.
+ "predictiveMethod": "A String", # Indicates which method of prediction is used for CPU utilization metric, if any. Current set of possible values: * NONE: No predictions are made based on the scaling metric when calculating the number of VM instances. * OPTIMIZE_AVAILABILITY: Standard predictive autoscaling predicts the future values of the scaling metric and then scales a MIG to ensure that new VM instances are ready in time to cover the predicted peak. New values might be added in the future. Some of the values might not be available in all API versions.
"utilizationTarget": 3.14, # The target CPU utilization that the autoscaler should maintain. Must be a float value in the range (0, 1]. If not specified, the default is 0.6.
#
# If the CPU level is below the target utilization, the autoscaler scales down the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization.