%% WARNING: DO NOT EDIT, AUTO-GENERATED CODE! %% See https://github.com/aws-beam/aws-codegen for more details. %% @doc AWS Compute Optimizer is a service that analyzes the configuration %% and utilization metrics of your AWS compute resources, such as EC2 %% instances, Auto Scaling groups, AWS Lambda functions, and Amazon EBS %% volumes. %% %% It reports whether your resources are optimal, and generates optimization %% recommendations to reduce the cost and improve the performance of your %% workloads. Compute Optimizer also provides recent utilization metric data, %% as well as projected utilization metric data for the recommendations, %% which you can use to evaluate which recommendation provides the best %% price-performance trade-off. The analysis of your usage patterns can help %% you decide when to move or resize your running resources, and still meet %% your performance and capacity requirements. For more information about %% Compute Optimizer, including the required permissions to use the service, %% see the AWS Compute Optimizer User Guide. -module(aws_compute_optimizer). -export([describe_recommendation_export_jobs/2, describe_recommendation_export_jobs/3, export_auto_scaling_group_recommendations/2, export_auto_scaling_group_recommendations/3, export_ec2_instance_recommendations/2, export_ec2_instance_recommendations/3, get_auto_scaling_group_recommendations/2, get_auto_scaling_group_recommendations/3, get_ebs_volume_recommendations/2, get_ebs_volume_recommendations/3, get_ec2_instance_recommendations/2, get_ec2_instance_recommendations/3, get_ec2_recommendation_projected_metrics/2, get_ec2_recommendation_projected_metrics/3, get_enrollment_status/2, get_enrollment_status/3, get_lambda_function_recommendations/2, get_lambda_function_recommendations/3, get_recommendation_summaries/2, get_recommendation_summaries/3, update_enrollment_status/2, update_enrollment_status/3]). -include_lib("hackney/include/hackney_lib.hrl"). %%==================================================================== %% API %%==================================================================== %% @doc Describes recommendation export jobs created in the last seven days. %% %% Use the `ExportAutoScalingGroupRecommendations' or %% `ExportEC2InstanceRecommendations' actions to request an export of your %% recommendations. Then use the `DescribeRecommendationExportJobs' action to %% view your export jobs. describe_recommendation_export_jobs(Client, Input) when is_map(Client), is_map(Input) -> describe_recommendation_export_jobs(Client, Input, []). describe_recommendation_export_jobs(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DescribeRecommendationExportJobs">>, Input, Options). %% @doc Exports optimization recommendations for Auto Scaling groups. %% %% Recommendations are exported in a comma-separated values (.csv) file, and %% its metadata in a JavaScript Object Notation (.json) file, to an existing %% Amazon Simple Storage Service (Amazon S3) bucket that you specify. For %% more information, see Exporting Recommendations in the Compute Optimizer %% User Guide. %% %% You can have only one Auto Scaling group export job in progress per AWS %% Region. export_auto_scaling_group_recommendations(Client, Input) when is_map(Client), is_map(Input) -> export_auto_scaling_group_recommendations(Client, Input, []). export_auto_scaling_group_recommendations(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"ExportAutoScalingGroupRecommendations">>, Input, Options). %% @doc Exports optimization recommendations for Amazon EC2 instances. %% %% Recommendations are exported in a comma-separated values (.csv) file, and %% its metadata in a JavaScript Object Notation (.json) file, to an existing %% Amazon Simple Storage Service (Amazon S3) bucket that you specify. For %% more information, see Exporting Recommendations in the Compute Optimizer %% User Guide. %% %% You can have only one Amazon EC2 instance export job in progress per AWS %% Region. export_ec2_instance_recommendations(Client, Input) when is_map(Client), is_map(Input) -> export_ec2_instance_recommendations(Client, Input, []). export_ec2_instance_recommendations(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"ExportEC2InstanceRecommendations">>, Input, Options). %% @doc Returns Auto Scaling group recommendations. %% %% AWS Compute Optimizer generates recommendations for Amazon EC2 Auto %% Scaling groups that meet a specific set of requirements. For more %% information, see the Supported resources and requirements in the AWS %% Compute Optimizer User Guide. get_auto_scaling_group_recommendations(Client, Input) when is_map(Client), is_map(Input) -> get_auto_scaling_group_recommendations(Client, Input, []). get_auto_scaling_group_recommendations(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetAutoScalingGroupRecommendations">>, Input, Options). %% @doc Returns Amazon Elastic Block Store (Amazon EBS) volume %% recommendations. %% %% AWS Compute Optimizer generates recommendations for Amazon EBS volumes %% that meet a specific set of requirements. For more information, see the %% Supported resources and requirements in the AWS Compute Optimizer User %% Guide. get_ebs_volume_recommendations(Client, Input) when is_map(Client), is_map(Input) -> get_ebs_volume_recommendations(Client, Input, []). get_ebs_volume_recommendations(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetEBSVolumeRecommendations">>, Input, Options). %% @doc Returns Amazon EC2 instance recommendations. %% %% AWS Compute Optimizer generates recommendations for Amazon Elastic Compute %% Cloud (Amazon EC2) instances that meet a specific set of requirements. For %% more information, see the Supported resources and requirements in the AWS %% Compute Optimizer User Guide. get_ec2_instance_recommendations(Client, Input) when is_map(Client), is_map(Input) -> get_ec2_instance_recommendations(Client, Input, []). get_ec2_instance_recommendations(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetEC2InstanceRecommendations">>, Input, Options). %% @doc Returns the projected utilization metrics of Amazon EC2 instance %% recommendations. %% %% The `Cpu' and `Memory' metrics are the only projected utilization metrics %% returned when you run this action. Additionally, the `Memory' metric is %% returned only for resources that have the unified CloudWatch agent %% installed on them. For more information, see Enabling Memory Utilization %% with the CloudWatch Agent. get_ec2_recommendation_projected_metrics(Client, Input) when is_map(Client), is_map(Input) -> get_ec2_recommendation_projected_metrics(Client, Input, []). get_ec2_recommendation_projected_metrics(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetEC2RecommendationProjectedMetrics">>, Input, Options). %% @doc Returns the enrollment (opt in) status of an account to the AWS %% Compute Optimizer service. %% %% If the account is the management account of an organization, this action %% also confirms the enrollment status of member accounts within the %% organization. get_enrollment_status(Client, Input) when is_map(Client), is_map(Input) -> get_enrollment_status(Client, Input, []). get_enrollment_status(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetEnrollmentStatus">>, Input, Options). %% @doc Returns AWS Lambda function recommendations. %% %% AWS Compute Optimizer generates recommendations for functions that meet a %% specific set of requirements. For more information, see the Supported %% resources and requirements in the AWS Compute Optimizer User Guide. get_lambda_function_recommendations(Client, Input) when is_map(Client), is_map(Input) -> get_lambda_function_recommendations(Client, Input, []). get_lambda_function_recommendations(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetLambdaFunctionRecommendations">>, Input, Options). %% @doc Returns the optimization findings for an account. %% %% It returns the number of: %% %% get_recommendation_summaries(Client, Input) when is_map(Client), is_map(Input) -> get_recommendation_summaries(Client, Input, []). get_recommendation_summaries(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetRecommendationSummaries">>, Input, Options). %% @doc Updates the enrollment (opt in and opt out) status of an account to %% the AWS Compute Optimizer service. %% %% If the account is a management account of an organization, this action can %% also be used to enroll member accounts within the organization. %% %% You must have the appropriate permissions to opt in to Compute Optimizer, %% to view its recommendations, and to opt out. For more information, see %% Controlling access with AWS Identity and Access Management in the Compute %% Optimizer User Guide. %% %% When you opt in, Compute Optimizer automatically creates a Service-Linked %% Role in your account to access its data. For more information, see Using %% Service-Linked Roles for AWS Compute Optimizer in the Compute Optimizer %% User Guide. update_enrollment_status(Client, Input) when is_map(Client), is_map(Input) -> update_enrollment_status(Client, Input, []). update_enrollment_status(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"UpdateEnrollmentStatus">>, Input, Options). %%==================================================================== %% Internal functions %%==================================================================== -spec request(aws_client:aws_client(), binary(), map(), list()) -> {ok, Result, {integer(), list(), hackney:client()}} | {error, Error, {integer(), list(), hackney:client()}} | {error, term()} when Result :: map() | undefined, Error :: map(). request(Client, Action, Input0, Options) -> Client1 = Client#{service => <<"compute-optimizer">>}, Host = build_host(<<"compute-optimizer">>, Client1), URL = build_url(Host, Client1), Headers = [ {<<"Host">>, Host}, {<<"Content-Type">>, <<"application/x-amz-json-1.0">>}, {<<"X-Amz-Target">>, <<"ComputeOptimizerService.", Action/binary>>} ], Input = Input0, Payload = jsx:encode(Input), SignedHeaders = aws_request:sign_request(Client1, <<"POST">>, URL, Headers, Payload), Response = hackney:request(post, URL, SignedHeaders, Payload, Options), handle_response(Response). handle_response({ok, 200, ResponseHeaders, Client}) -> case hackney:body(Client) of {ok, <<>>} -> {ok, undefined, {200, ResponseHeaders, Client}}; {ok, Body} -> Result = jsx:decode(Body), {ok, Result, {200, ResponseHeaders, Client}} end; handle_response({ok, StatusCode, ResponseHeaders, Client}) -> {ok, Body} = hackney:body(Client), Error = jsx:decode(Body), {error, Error, {StatusCode, ResponseHeaders, Client}}; handle_response({error, Reason}) -> {error, Reason}. build_host(_EndpointPrefix, #{region := <<"local">>, endpoint := Endpoint}) -> Endpoint; build_host(_EndpointPrefix, #{region := <<"local">>}) -> <<"localhost">>; build_host(EndpointPrefix, #{region := Region, endpoint := Endpoint}) -> aws_util:binary_join([EndpointPrefix, Region, Endpoint], <<".">>). build_url(Host, Client) -> Proto = maps:get(proto, Client), Port = maps:get(port, Client), aws_util:binary_join([Proto, <<"://">>, Host, <<":">>, Port, <<"/">>], <<"">>).