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Add (beta) filter to autoscaler properties
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emilymye authored and modular-magician committed Oct 25, 2018
1 parent 45c037f commit 372d3a0
Showing 4 changed files with 100 additions and 0 deletions.
20 changes: 20 additions & 0 deletions google-beta/resource_compute_autoscaler.go
Original file line number Diff line number Diff line change
@@ -108,6 +108,10 @@ func resourceComputeAutoscaler() *schema.Resource {
Required: true,
ValidateFunc: validation.StringInSlice([]string{"GAUGE", "DELTA_PER_SECOND", "DELTA_PER_MINUTE"}, false),
},
"filter": {
Type: schema.TypeString,
Optional: true,
},
},
},
},
@@ -484,6 +488,7 @@ func flattenComputeAutoscalerAutoscalingPolicyMetric(v interface{}) interface{}
"name": flattenComputeAutoscalerAutoscalingPolicyMetricName(original["metric"]),
"target": flattenComputeAutoscalerAutoscalingPolicyMetricTarget(original["utilizationTarget"]),
"type": flattenComputeAutoscalerAutoscalingPolicyMetricType(original["utilizationTargetType"]),
"filter": flattenComputeAutoscalerAutoscalingPolicyMetricFilter(original["filter"]),
})
}
return transformed
@@ -500,6 +505,10 @@ func flattenComputeAutoscalerAutoscalingPolicyMetricType(v interface{}) interfac
return v
}

func flattenComputeAutoscalerAutoscalingPolicyMetricFilter(v interface{}) interface{} {
return v
}

func flattenComputeAutoscalerAutoscalingPolicyLoadBalancingUtilization(v interface{}) interface{} {
if v == nil {
return nil
@@ -656,6 +665,13 @@ func expandComputeAutoscalerAutoscalingPolicyMetric(v interface{}, d *schema.Res
transformed["utilizationTargetType"] = transformedType
}

transformedFilter, err := expandComputeAutoscalerAutoscalingPolicyMetricFilter(original["filter"], d, config)
if err != nil {
return nil, err
} else if val := reflect.ValueOf(transformedFilter); val.IsValid() && !isEmptyValue(val) {
transformed["filter"] = transformedFilter
}

req = append(req, transformed)
}
return req, nil
@@ -673,6 +689,10 @@ func expandComputeAutoscalerAutoscalingPolicyMetricType(v interface{}, d *schema
return v, nil
}

func expandComputeAutoscalerAutoscalingPolicyMetricFilter(v interface{}, d *schema.ResourceData, config *Config) (interface{}, error) {
return v, nil
}

func expandComputeAutoscalerAutoscalingPolicyLoadBalancingUtilization(v interface{}, d *schema.ResourceData, config *Config) (interface{}, error) {
l := v.([]interface{})
if len(l) == 0 || l[0] == nil {
20 changes: 20 additions & 0 deletions google-beta/resource_compute_region_autoscaler.go
Original file line number Diff line number Diff line change
@@ -108,6 +108,10 @@ func resourceComputeRegionAutoscaler() *schema.Resource {
Required: true,
ValidateFunc: validation.StringInSlice([]string{"GAUGE", "DELTA_PER_SECOND", "DELTA_PER_MINUTE"}, false),
},
"filter": {
Type: schema.TypeString,
Optional: true,
},
},
},
},
@@ -483,6 +487,7 @@ func flattenComputeRegionAutoscalerAutoscalingPolicyMetric(v interface{}) interf
"name": flattenComputeRegionAutoscalerAutoscalingPolicyMetricName(original["metric"]),
"target": flattenComputeRegionAutoscalerAutoscalingPolicyMetricTarget(original["utilizationTarget"]),
"type": flattenComputeRegionAutoscalerAutoscalingPolicyMetricType(original["utilizationTargetType"]),
"filter": flattenComputeRegionAutoscalerAutoscalingPolicyMetricFilter(original["filter"]),
})
}
return transformed
@@ -499,6 +504,10 @@ func flattenComputeRegionAutoscalerAutoscalingPolicyMetricType(v interface{}) in
return v
}

func flattenComputeRegionAutoscalerAutoscalingPolicyMetricFilter(v interface{}) interface{} {
return v
}

func flattenComputeRegionAutoscalerAutoscalingPolicyLoadBalancingUtilization(v interface{}) interface{} {
if v == nil {
return nil
@@ -652,6 +661,13 @@ func expandComputeRegionAutoscalerAutoscalingPolicyMetric(v interface{}, d *sche
transformed["utilizationTargetType"] = transformedType
}

transformedFilter, err := expandComputeRegionAutoscalerAutoscalingPolicyMetricFilter(original["filter"], d, config)
if err != nil {
return nil, err
} else if val := reflect.ValueOf(transformedFilter); val.IsValid() && !isEmptyValue(val) {
transformed["filter"] = transformedFilter
}

req = append(req, transformed)
}
return req, nil
@@ -669,6 +685,10 @@ func expandComputeRegionAutoscalerAutoscalingPolicyMetricType(v interface{}, d *
return v, nil
}

func expandComputeRegionAutoscalerAutoscalingPolicyMetricFilter(v interface{}, d *schema.ResourceData, config *Config) (interface{}, error) {
return v, nil
}

func expandComputeRegionAutoscalerAutoscalingPolicyLoadBalancingUtilization(v interface{}, d *schema.ResourceData, config *Config) (interface{}, error) {
l := v.([]interface{})
if len(l) == 0 || l[0] == nil {
30 changes: 30 additions & 0 deletions website/docs/r/compute_autoscaler.html.markdown
Original file line number Diff line number Diff line change
@@ -217,6 +217,36 @@ The `metric` block supports:
Stackdriver Monitoring metric. Either GAUGE, DELTA_PER_SECOND,
or DELTA_PER_MINUTE.

* `filter` -
(Optional)
A filter string to be used as the filter string for
a Stackdriver Monitoring TimeSeries.list API call.
This filter is used to select a specific TimeSeries for
the purpose of autoscaling and to determine whether the metric
is exporting per-instance or per-group data.
You can only use the AND operator for joining selectors.
You can only use direct equality comparison operator (=) without
any functions for each selector.
You can specify the metric in both the filter string and in the
metric field. However, if specified in both places, the metric must
be identical.
The monitored resource type determines what kind of values are
expected for the metric. If it is a gce_instance, the autoscaler
expects the metric to include a separate TimeSeries for each
instance in a group. In such a case, you cannot filter on resource
labels.
If the resource type is any other value, the autoscaler expects
this metric to contain values that apply to the entire autoscaled
instance group and resource label filtering can be performed to
point autoscaler at the correct TimeSeries to scale upon.
This is called a per-group metric for the purpose of autoscaling.
If not specified, the type defaults to gce_instance.
You should provide a filter that is selective enough to pick just
one TimeSeries for the autoscaled group or for each of the instances
(if you are using gce_instance resource type). If multiple
TimeSeries are returned upon the query execution, the autoscaler
will sum their respective values to obtain its scaling value.

The `load_balancing_utilization` block supports:

* `target` -
30 changes: 30 additions & 0 deletions website/docs/r/compute_region_autoscaler.html.markdown
Original file line number Diff line number Diff line change
@@ -217,6 +217,36 @@ The `metric` block supports:
Stackdriver Monitoring metric. Either GAUGE, DELTA_PER_SECOND,
or DELTA_PER_MINUTE.

* `filter` -
(Optional)
A filter string to be used as the filter string for
a Stackdriver Monitoring TimeSeries.list API call.
This filter is used to select a specific TimeSeries for
the purpose of autoscaling and to determine whether the metric
is exporting per-instance or per-group data.
You can only use the AND operator for joining selectors.
You can only use direct equality comparison operator (=) without
any functions for each selector.
You can specify the metric in both the filter string and in the
metric field. However, if specified in both places, the metric must
be identical.
The monitored resource type determines what kind of values are
expected for the metric. If it is a gce_instance, the autoscaler
expects the metric to include a separate TimeSeries for each
instance in a group. In such a case, you cannot filter on resource
labels.
If the resource type is any other value, the autoscaler expects
this metric to contain values that apply to the entire autoscaled
instance group and resource label filtering can be performed to
point autoscaler at the correct TimeSeries to scale upon.
This is called a per-group metric for the purpose of autoscaling.
If not specified, the type defaults to gce_instance.
You should provide a filter that is selective enough to pick just
one TimeSeries for the autoscaled group or for each of the instances
(if you are using gce_instance resource type). If multiple
TimeSeries are returned upon the query execution, the autoscaler
will sum their respective values to obtain its scaling value.

The `load_balancing_utilization` block supports:

* `target` -

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