docs: add sample for managed autoscaler (#1111)

* docs: add sample for managed autoscaler * incorporate suggestions --------- Co-authored-by: Sri Harsha CH <57220027+harshachinta@users.noreply.github.com>

Author: rahul2393

samples/samples/snippets.py

@@ -3043,8 +3043,8 @@ def directed_read_options(
 def set_custom_timeout_and_retry(instance_id, database_id):
  """Executes a snapshot read with custom timeout and retry."""
  # [START spanner_set_custom_timeout_and_retry]
- from google.api_core import retry
  from google.api_core import exceptions as core_exceptions
+ from google.api_core import retry
 
  # instance_id = "your-spanner-instance"
  # database_id = "your-spanner-db-id"
@@ -3085,6 +3085,65 @@ def set_custom_timeout_and_retry(instance_id, database_id):
  # [END spanner_set_custom_timeout_and_retry]
 
 
+# [START spanner_create_instance_with_autoscaling_config]
+def create_instance_with_autoscaling_config(instance_id):
+ """Creates a Cloud Spanner instance with an autoscaling configuration."""
+ from google.cloud.spanner_admin_instance_v1.types import \
+ spanner_instance_admin
+
+ spanner_client = spanner.Client()
+
+ config_name = "{}/instanceConfigs/regional-us-central1".format(
+ spanner_client.project_name
+ )
+
+ autoscaling_config = spanner_instance_admin.AutoscalingConfig(
+ # Only one of minNodes/maxNodes or minProcessingUnits/maxProcessingUnits can be set.
+ autoscaling_limits=spanner_instance_admin.AutoscalingConfig.AutoscalingLimits(
+ min_nodes=1,
+ max_nodes=2,
+ ),
+ # highPriorityCpuUtilizationPercent and storageUtilizationPercent are both
+ # percentages and must lie between 0 and 100.
+ autoscaling_targets=spanner_instance_admin.AutoscalingConfig.AutoscalingTargets(
+ high_priority_cpu_utilization_percent=65,
+ storage_utilization_percent=95,
+ ),
+ )
+
+ # Creates a new instance with autoscaling configuration
+ # When autoscalingConfig is enabled, nodeCount and processingUnits fields
+ # need not be specified.
+ request = spanner_instance_admin.CreateInstanceRequest(
+ parent=spanner_client.project_name,
+ instance_id=instance_id,
+ instance=spanner_instance_admin.Instance(
+ config=config_name,
+ display_name="This is a display name.",
+ autoscaling_config=autoscaling_config,
+ labels={
+ "cloud_spanner_samples": "true",
+ "sample_name": "snippets-create_instance_with_autoscaling_config",
+ "created": str(int(time.time())),
+ },
+ ),
+ )
+
+ operation = spanner_client.instance_admin_api.create_instance(request=request)
+
+ print("Waiting for operation to complete...")
+ instance = operation.result(OPERATION_TIMEOUT_SECONDS)
+
+ print(
+ "Created instance {} with {} autoscaling config".format(
+ instance_id, instance.autoscaling_config
+ )
+ )
+
+
+# [END spanner_create_instance_with_autoscaling_config]
+
+
 if __name__ == "__main__": # noqa: C901
  parser = argparse.ArgumentParser(
  description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
@@ -3366,3 +3425,5 @@ def set_custom_timeout_and_retry(instance_id, database_id):
  directed_read_options(args.instance_id, args.database_id)
  elif args.command == "set_custom_timeout_and_retry":
  set_custom_timeout_and_retry(args.instance_id, args.database_id)
+ elif args.command == "create_instance_with_autoscaling_config":
+ create_instance_with_autoscaling_config(args.instance_id)

samples/samples/snippets_test.py

@@ -154,6 +154,18 @@ def test_create_instance_with_processing_units(capsys, lci_instance_id):
  retry_429(instance.delete)()
 
 
+def test_create_instance_with_autoscaling_config(capsys, lci_instance_id):
+ retry_429(snippets.create_instance_with_autoscaling_config)(
+ lci_instance_id,
+ )
+ out, _ = capsys.readouterr()
+ assert lci_instance_id in out
+ assert "autoscaling config" in out
+ spanner_client = spanner.Client()
+ instance = spanner_client.instance(lci_instance_id)
+ retry_429(instance.delete)()
+
+
 def test_update_database(capsys, instance_id, sample_database):
  snippets.update_database(instance_id, sample_database.database_id)
  out, _ = capsys.readouterr()