%% WARNING: DO NOT EDIT, AUTO-GENERATED CODE! %% See https://github.com/aws-beam/aws-codegen for more details. %% @doc Amazon CloudWatch monitors your Amazon Web Services (Amazon Web %% Services) resources and the applications you run on Amazon Web Services in %% real time. %% %% You can use CloudWatch to collect and track metrics, which are the %% variables you want to measure for your resources and applications. %% %% CloudWatch alarms send notifications or automatically change the resources %% you are monitoring based on rules that you define. For example, you can %% monitor the CPU usage and disk reads and writes of your Amazon EC2 %% instances. Then, use this data to determine whether you should launch %% additional instances to handle increased load. You can also use this data %% to stop under-used instances to save money. %% %% In addition to monitoring the built-in metrics that come with Amazon Web %% Services, you can monitor your own custom metrics. With CloudWatch, you %% gain system-wide visibility into resource utilization, application %% performance, and operational health. -module(aws_cloudwatch). -export([delete_alarms/2, delete_alarms/3, delete_anomaly_detector/2, delete_anomaly_detector/3, delete_dashboards/2, delete_dashboards/3, delete_insight_rules/2, delete_insight_rules/3, delete_metric_stream/2, delete_metric_stream/3, describe_alarm_history/2, describe_alarm_history/3, describe_alarms/2, describe_alarms/3, describe_alarms_for_metric/2, describe_alarms_for_metric/3, describe_anomaly_detectors/2, describe_anomaly_detectors/3, describe_insight_rules/2, describe_insight_rules/3, disable_alarm_actions/2, disable_alarm_actions/3, disable_insight_rules/2, disable_insight_rules/3, enable_alarm_actions/2, enable_alarm_actions/3, enable_insight_rules/2, enable_insight_rules/3, get_dashboard/2, get_dashboard/3, get_insight_rule_report/2, get_insight_rule_report/3, get_metric_data/2, get_metric_data/3, get_metric_statistics/2, get_metric_statistics/3, get_metric_stream/2, get_metric_stream/3, get_metric_widget_image/2, get_metric_widget_image/3, list_dashboards/2, list_dashboards/3, list_managed_insight_rules/2, list_managed_insight_rules/3, list_metric_streams/2, list_metric_streams/3, list_metrics/2, list_metrics/3, list_tags_for_resource/2, list_tags_for_resource/3, put_anomaly_detector/2, put_anomaly_detector/3, put_composite_alarm/2, put_composite_alarm/3, put_dashboard/2, put_dashboard/3, put_insight_rule/2, put_insight_rule/3, put_managed_insight_rules/2, put_managed_insight_rules/3, put_metric_alarm/2, put_metric_alarm/3, put_metric_data/2, put_metric_data/3, put_metric_stream/2, put_metric_stream/3, set_alarm_state/2, set_alarm_state/3, start_metric_streams/2, start_metric_streams/3, stop_metric_streams/2, stop_metric_streams/3, tag_resource/2, tag_resource/3, untag_resource/2, untag_resource/3]). -include_lib("hackney/include/hackney_lib.hrl"). %%==================================================================== %% API %%==================================================================== %% @doc Deletes the specified alarms. %% %% You can delete up to 100 alarms in one operation. However, this total can %% include no more than one composite alarm. For example, you could delete 99 %% metric alarms and one composite alarms with one operation, but you can't %% delete two composite alarms with one operation. %% %% In the event of an error, no alarms are deleted. %% %% It is possible to create a loop or cycle of composite alarms, where %% composite alarm A depends on composite alarm B, and composite alarm B also %% depends on composite alarm A. In this scenario, you can't delete any %% composite alarm that is part of the cycle because there is always still a %% composite alarm that depends on that alarm that you want to delete. %% %% To get out of such a situation, you must break the cycle by changing the %% rule of one of the composite alarms in the cycle to remove a dependency %% that creates the cycle. The simplest change to make to break a cycle is to %% change the `AlarmRule' of one of the alarms to `false'. %% %% Additionally, the evaluation of composite alarms stops if CloudWatch %% detects a cycle in the evaluation path. delete_alarms(Client, Input) when is_map(Client), is_map(Input) -> delete_alarms(Client, Input, []). delete_alarms(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DeleteAlarms">>, Input, Options). %% @doc Deletes the specified anomaly detection model from your account. %% %% For more information about how to delete an anomaly detection model, see %% Deleting an anomaly detection model in the CloudWatch User Guide. delete_anomaly_detector(Client, Input) when is_map(Client), is_map(Input) -> delete_anomaly_detector(Client, Input, []). delete_anomaly_detector(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DeleteAnomalyDetector">>, Input, Options). %% @doc Deletes all dashboards that you specify. %% %% You can specify up to 100 dashboards to delete. If there is an error %% during this call, no dashboards are deleted. delete_dashboards(Client, Input) when is_map(Client), is_map(Input) -> delete_dashboards(Client, Input, []). delete_dashboards(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DeleteDashboards">>, Input, Options). %% @doc Permanently deletes the specified Contributor Insights rules. %% %% If you create a rule, delete it, and then re-create it with the same name, %% historical data from the first time the rule was created might not be %% available. delete_insight_rules(Client, Input) when is_map(Client), is_map(Input) -> delete_insight_rules(Client, Input, []). delete_insight_rules(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DeleteInsightRules">>, Input, Options). %% @doc Permanently deletes the metric stream that you specify. delete_metric_stream(Client, Input) when is_map(Client), is_map(Input) -> delete_metric_stream(Client, Input, []). delete_metric_stream(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DeleteMetricStream">>, Input, Options). %% @doc Retrieves the history for the specified alarm. %% %% You can filter the results by date range or item type. If an alarm name is %% not specified, the histories for either all metric alarms or all composite %% alarms are returned. %% %% CloudWatch retains the history of an alarm even if you delete the alarm. %% %% To use this operation and return information about a composite alarm, you %% must be signed on with the `cloudwatch:DescribeAlarmHistory' permission %% that is scoped to `*'. You can't return information about composite alarms %% if your `cloudwatch:DescribeAlarmHistory' permission has a narrower scope. describe_alarm_history(Client, Input) when is_map(Client), is_map(Input) -> describe_alarm_history(Client, Input, []). describe_alarm_history(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DescribeAlarmHistory">>, Input, Options). %% @doc Retrieves the specified alarms. %% %% You can filter the results by specifying a prefix for the alarm name, the %% alarm state, or a prefix for any action. %% %% To use this operation and return information about composite alarms, you %% must be signed on with the `cloudwatch:DescribeAlarms' permission that is %% scoped to `*'. You can't return information about composite alarms if your %% `cloudwatch:DescribeAlarms' permission has a narrower scope. describe_alarms(Client, Input) when is_map(Client), is_map(Input) -> describe_alarms(Client, Input, []). describe_alarms(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DescribeAlarms">>, Input, Options). %% @doc Retrieves the alarms for the specified metric. %% %% To filter the results, specify a statistic, period, or unit. %% %% This operation retrieves only standard alarms that are based on the %% specified metric. It does not return alarms based on math expressions that %% use the specified metric, or composite alarms that use the specified %% metric. describe_alarms_for_metric(Client, Input) when is_map(Client), is_map(Input) -> describe_alarms_for_metric(Client, Input, []). describe_alarms_for_metric(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DescribeAlarmsForMetric">>, Input, Options). %% @doc Lists the anomaly detection models that you have created in your %% account. %% %% For single metric anomaly detectors, you can list all of the models in %% your account or filter the results to only the models that are related to %% a certain namespace, metric name, or metric dimension. For metric math %% anomaly detectors, you can list them by adding `METRIC_MATH' to the %% `AnomalyDetectorTypes' array. This will return all metric math anomaly %% detectors in your account. describe_anomaly_detectors(Client, Input) when is_map(Client), is_map(Input) -> describe_anomaly_detectors(Client, Input, []). describe_anomaly_detectors(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DescribeAnomalyDetectors">>, Input, Options). %% @doc Returns a list of all the Contributor Insights rules in your account. %% %% For more information about Contributor Insights, see Using Contributor %% Insights to Analyze High-Cardinality Data. describe_insight_rules(Client, Input) when is_map(Client), is_map(Input) -> describe_insight_rules(Client, Input, []). describe_insight_rules(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DescribeInsightRules">>, Input, Options). %% @doc Disables the actions for the specified alarms. %% %% When an alarm's actions are disabled, the alarm actions do not execute %% when the alarm state changes. disable_alarm_actions(Client, Input) when is_map(Client), is_map(Input) -> disable_alarm_actions(Client, Input, []). disable_alarm_actions(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DisableAlarmActions">>, Input, Options). %% @doc Disables the specified Contributor Insights rules. %% %% When rules are disabled, they do not analyze log groups and do not incur %% costs. disable_insight_rules(Client, Input) when is_map(Client), is_map(Input) -> disable_insight_rules(Client, Input, []). disable_insight_rules(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"DisableInsightRules">>, Input, Options). %% @doc Enables the actions for the specified alarms. enable_alarm_actions(Client, Input) when is_map(Client), is_map(Input) -> enable_alarm_actions(Client, Input, []). enable_alarm_actions(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"EnableAlarmActions">>, Input, Options). %% @doc Enables the specified Contributor Insights rules. %% %% When rules are enabled, they immediately begin analyzing log data. enable_insight_rules(Client, Input) when is_map(Client), is_map(Input) -> enable_insight_rules(Client, Input, []). enable_insight_rules(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"EnableInsightRules">>, Input, Options). %% @doc Displays the details of the dashboard that you specify. %% %% To copy an existing dashboard, use `GetDashboard', and then use the data %% returned within `DashboardBody' as the template for the new dashboard when %% you call `PutDashboard' to create the copy. get_dashboard(Client, Input) when is_map(Client), is_map(Input) -> get_dashboard(Client, Input, []). get_dashboard(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetDashboard">>, Input, Options). %% @doc This operation returns the time series data collected by a %% Contributor Insights rule. %% %% The data includes the identity and number of contributors to the log %% group. %% %% You can also optionally return one or more statistics about each data %% point in the time series. These statistics can include the following: %% %% get_insight_rule_report(Client, Input) when is_map(Client), is_map(Input) -> get_insight_rule_report(Client, Input, []). get_insight_rule_report(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetInsightRuleReport">>, Input, Options). %% @doc You can use the `GetMetricData' API to retrieve CloudWatch metric %% values. %% %% The operation can also include a CloudWatch Metrics Insights query, and %% one or more metric math functions. %% %% A `GetMetricData' operation that does not include a query can retrieve as %% many as 500 different metrics in a single request, with a total of as many %% as 100,800 data points. You can also optionally perform metric math %% expressions on the values of the returned statistics, to create new time %% series that represent new insights into your data. For example, using %% Lambda metrics, you could divide the Errors metric by the Invocations %% metric to get an error rate time series. For more information about metric %% math expressions, see Metric Math Syntax and Functions in the Amazon %% CloudWatch User Guide. %% %% If you include a Metrics Insights query, each `GetMetricData' operation %% can include only one query. But the same `GetMetricData' operation can %% also retrieve other metrics. Metrics Insights queries can query only the %% most recent three hours of metric data. For more information about Metrics %% Insights, see Query your metrics with CloudWatch Metrics Insights. %% %% Calls to the `GetMetricData' API have a different pricing structure than %% calls to `GetMetricStatistics'. For more information about pricing, see %% Amazon CloudWatch Pricing. %% %% Amazon CloudWatch retains metric data as follows: %% %% Data points that are initially published with a shorter period %% are aggregated together for long-term storage. For example, if you collect %% data using a period of 1 minute, the data remains available for 15 days %% with 1-minute resolution. After 15 days, this data is still available, but %% is aggregated and retrievable only with a resolution of 5 minutes. After %% 63 days, the data is further aggregated and is available with a resolution %% of 1 hour. %% %% If you omit `Unit' in your request, all data that was collected with any %% unit is returned, along with the corresponding units that were specified %% when the data was reported to CloudWatch. If you specify a unit, the %% operation returns only data that was collected with that unit specified. %% If you specify a unit that does not match the data collected, the results %% of the operation are null. CloudWatch does not perform unit conversions. %% %% Using Metrics Insights queries with metric math %% %% You can't mix a Metric Insights query and metric math syntax in the same %% expression, but you can reference results from a Metrics Insights query %% within other Metric math expressions. A Metrics Insights query without a %% GROUP BY clause returns a single time-series (TS), and can be used as %% input for a metric math expression that expects a single time series. A %% Metrics Insights query with a GROUP BY clause returns an array of %% time-series (TS[]), and can be used as input for a metric math expression %% that expects an array of time series. get_metric_data(Client, Input) when is_map(Client), is_map(Input) -> get_metric_data(Client, Input, []). get_metric_data(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetMetricData">>, Input, Options). %% @doc Gets statistics for the specified metric. %% %% The maximum number of data points returned from a single call is 1,440. If %% you request more than 1,440 data points, CloudWatch returns an error. To %% reduce the number of data points, you can narrow the specified time range %% and make multiple requests across adjacent time ranges, or you can %% increase the specified period. Data points are not returned in %% chronological order. %% %% CloudWatch aggregates data points based on the length of the period that %% you specify. For example, if you request statistics with a one-hour %% period, CloudWatch aggregates all data points with time stamps that fall %% within each one-hour period. Therefore, the number of values aggregated by %% CloudWatch is larger than the number of data points returned. %% %% CloudWatch needs raw data points to calculate percentile statistics. If %% you publish data using a statistic set instead, you can only retrieve %% percentile statistics for this data if one of the following conditions is %% true: %% %% Percentile statistics are not available for metrics when any %% of the metric values are negative numbers. %% %% Amazon CloudWatch retains metric data as follows: %% %% Data points that are initially published with a shorter period %% are aggregated together for long-term storage. For example, if you collect %% data using a period of 1 minute, the data remains available for 15 days %% with 1-minute resolution. After 15 days, this data is still available, but %% is aggregated and retrievable only with a resolution of 5 minutes. After %% 63 days, the data is further aggregated and is available with a resolution %% of 1 hour. %% %% CloudWatch started retaining 5-minute and 1-hour metric data as of July 9, %% 2016. %% %% For information about metrics and dimensions supported by Amazon Web %% Services services, see the Amazon CloudWatch Metrics and Dimensions %% Reference in the Amazon CloudWatch User Guide. get_metric_statistics(Client, Input) when is_map(Client), is_map(Input) -> get_metric_statistics(Client, Input, []). get_metric_statistics(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetMetricStatistics">>, Input, Options). %% @doc Returns information about the metric stream that you specify. get_metric_stream(Client, Input) when is_map(Client), is_map(Input) -> get_metric_stream(Client, Input, []). get_metric_stream(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetMetricStream">>, Input, Options). %% @doc You can use the `GetMetricWidgetImage' API to retrieve a snapshot %% graph of one or more Amazon CloudWatch metrics as a bitmap image. %% %% You can then embed this image into your services and products, such as %% wiki pages, reports, and documents. You could also retrieve images %% regularly, such as every minute, and create your own custom live %% dashboard. %% %% The graph you retrieve can include all CloudWatch metric graph features, %% including metric math and horizontal and vertical annotations. %% %% There is a limit of 20 transactions per second for this API. Each %% `GetMetricWidgetImage' action has the following limits: %% %% get_metric_widget_image(Client, Input) when is_map(Client), is_map(Input) -> get_metric_widget_image(Client, Input, []). get_metric_widget_image(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"GetMetricWidgetImage">>, Input, Options). %% @doc Returns a list of the dashboards for your account. %% %% If you include `DashboardNamePrefix', only those dashboards with names %% starting with the prefix are listed. Otherwise, all dashboards in your %% account are listed. %% %% `ListDashboards' returns up to 1000 results on one page. If there are more %% than 1000 dashboards, you can call `ListDashboards' again and include the %% value you received for `NextToken' in the first call, to receive the next %% 1000 results. list_dashboards(Client, Input) when is_map(Client), is_map(Input) -> list_dashboards(Client, Input, []). list_dashboards(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"ListDashboards">>, Input, Options). %% @doc Returns a list that contains the number of managed Contributor %% Insights rules in your account. list_managed_insight_rules(Client, Input) when is_map(Client), is_map(Input) -> list_managed_insight_rules(Client, Input, []). list_managed_insight_rules(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"ListManagedInsightRules">>, Input, Options). %% @doc Returns a list of metric streams in this account. list_metric_streams(Client, Input) when is_map(Client), is_map(Input) -> list_metric_streams(Client, Input, []). list_metric_streams(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"ListMetricStreams">>, Input, Options). %% @doc List the specified metrics. %% %% You can use the returned metrics with GetMetricData or GetMetricStatistics %% to get statistical data. %% %% Up to 500 results are returned for any one call. To retrieve additional %% results, use the returned token with subsequent calls. %% %% After you create a metric, allow up to 15 minutes for the metric to %% appear. To see metric statistics sooner, use GetMetricData or %% GetMetricStatistics. %% %% If you are using CloudWatch cross-account observability, you can use this %% operation in a monitoring account and view metrics from the linked source %% accounts. For more information, see CloudWatch cross-account %% observability. %% %% `ListMetrics' doesn't return information about metrics if those metrics %% haven't reported data in the past two weeks. To retrieve those metrics, %% use GetMetricData or GetMetricStatistics. list_metrics(Client, Input) when is_map(Client), is_map(Input) -> list_metrics(Client, Input, []). list_metrics(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"ListMetrics">>, Input, Options). %% @doc Displays the tags associated with a CloudWatch resource. %% %% Currently, alarms and Contributor Insights rules support tagging. list_tags_for_resource(Client, Input) when is_map(Client), is_map(Input) -> list_tags_for_resource(Client, Input, []). list_tags_for_resource(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"ListTagsForResource">>, Input, Options). %% @doc Creates an anomaly detection model for a CloudWatch metric. %% %% You can use the model to display a band of expected normal values when the %% metric is graphed. %% %% For more information, see CloudWatch Anomaly Detection. put_anomaly_detector(Client, Input) when is_map(Client), is_map(Input) -> put_anomaly_detector(Client, Input, []). put_anomaly_detector(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"PutAnomalyDetector">>, Input, Options). %% @doc Creates or updates a composite alarm. %% %% When you create a composite alarm, you specify a rule expression for the %% alarm that takes into account the alarm states of other alarms that you %% have created. The composite alarm goes into ALARM state only if all %% conditions of the rule are met. %% %% The alarms specified in a composite alarm's rule expression can include %% metric alarms and other composite alarms. The rule expression of a %% composite alarm can include as many as 100 underlying alarms. Any single %% alarm can be included in the rule expressions of as many as 150 composite %% alarms. %% %% Using composite alarms can reduce alarm noise. You can create multiple %% metric alarms, and also create a composite alarm and set up alerts only %% for the composite alarm. For example, you could create a composite alarm %% that goes into ALARM state only when more than one of the underlying %% metric alarms are in ALARM state. %% %% Currently, the only alarm actions that can be taken by composite alarms %% are notifying SNS topics. %% %% It is possible to create a loop or cycle of composite alarms, where %% composite alarm A depends on composite alarm B, and composite alarm B also %% depends on composite alarm A. In this scenario, you can't delete any %% composite alarm that is part of the cycle because there is always still a %% composite alarm that depends on that alarm that you want to delete. %% %% To get out of such a situation, you must break the cycle by changing the %% rule of one of the composite alarms in the cycle to remove a dependency %% that creates the cycle. The simplest change to make to break a cycle is to %% change the `AlarmRule' of one of the alarms to `false'. %% %% Additionally, the evaluation of composite alarms stops if CloudWatch %% detects a cycle in the evaluation path. %% %% When this operation creates an alarm, the alarm state is immediately set %% to `INSUFFICIENT_DATA'. The alarm is then evaluated and its state is set %% appropriately. Any actions associated with the new state are then %% executed. For a composite alarm, this initial time after creation is the %% only time that the alarm can be in `INSUFFICIENT_DATA' state. %% %% When you update an existing alarm, its state is left unchanged, but the %% update completely overwrites the previous configuration of the alarm. %% %% To use this operation, you must be signed on with the %% `cloudwatch:PutCompositeAlarm' permission that is scoped to `*'. You can't %% create a composite alarms if your `cloudwatch:PutCompositeAlarm' %% permission has a narrower scope. %% %% If you are an IAM user, you must have `iam:CreateServiceLinkedRole' to %% create a composite alarm that has Systems Manager OpsItem actions. put_composite_alarm(Client, Input) when is_map(Client), is_map(Input) -> put_composite_alarm(Client, Input, []). put_composite_alarm(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"PutCompositeAlarm">>, Input, Options). %% @doc Creates a dashboard if it does not already exist, or updates an %% existing dashboard. %% %% If you update a dashboard, the entire contents are replaced with what you %% specify here. %% %% All dashboards in your account are global, not region-specific. %% %% A simple way to create a dashboard using `PutDashboard' is to copy an %% existing dashboard. To copy an existing dashboard using the console, you %% can load the dashboard and then use the View/edit source command in the %% Actions menu to display the JSON block for that dashboard. Another way to %% copy a dashboard is to use `GetDashboard', and then use the data returned %% within `DashboardBody' as the template for the new dashboard when you call %% `PutDashboard'. %% %% When you create a dashboard with `PutDashboard', a good practice is to add %% a text widget at the top of the dashboard with a message that the %% dashboard was created by script and should not be changed in the console. %% This message could also point console users to the location of the %% `DashboardBody' script or the CloudFormation template used to create the %% dashboard. put_dashboard(Client, Input) when is_map(Client), is_map(Input) -> put_dashboard(Client, Input, []). put_dashboard(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"PutDashboard">>, Input, Options). %% @doc Creates a Contributor Insights rule. %% %% Rules evaluate log events in a CloudWatch Logs log group, enabling you to %% find contributor data for the log events in that log group. For more %% information, see Using Contributor Insights to Analyze High-Cardinality %% Data. %% %% If you create a rule, delete it, and then re-create it with the same name, %% historical data from the first time the rule was created might not be %% available. put_insight_rule(Client, Input) when is_map(Client), is_map(Input) -> put_insight_rule(Client, Input, []). put_insight_rule(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"PutInsightRule">>, Input, Options). %% @doc Creates a managed Contributor Insights rule for a specified Amazon %% Web Services resource. %% %% When you enable a managed rule, you create a Contributor Insights rule %% that collects data from Amazon Web Services services. You cannot edit %% these rules with `PutInsightRule'. The rules can be enabled, disabled, and %% deleted using `EnableInsightRules', `DisableInsightRules', and %% `DeleteInsightRules'. If a previously created managed rule is currently %% disabled, a subsequent call to this API will re-enable it. Use %% `ListManagedInsightRules' to describe all available rules. put_managed_insight_rules(Client, Input) when is_map(Client), is_map(Input) -> put_managed_insight_rules(Client, Input, []). put_managed_insight_rules(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"PutManagedInsightRules">>, Input, Options). %% @doc Creates or updates an alarm and associates it with the specified %% metric, metric math expression, anomaly detection model, or Metrics %% Insights query. %% %% For more information about using a Metrics Insights query for an alarm, %% see Create alarms on Metrics Insights queries. %% %% Alarms based on anomaly detection models cannot have Auto Scaling actions. %% %% When this operation creates an alarm, the alarm state is immediately set %% to `INSUFFICIENT_DATA'. The alarm is then evaluated and its state is set %% appropriately. Any actions associated with the new state are then %% executed. %% %% When you update an existing alarm, its state is left unchanged, but the %% update completely overwrites the previous configuration of the alarm. %% %% If you are an IAM user, you must have Amazon EC2 permissions for some %% alarm operations: %% %% The first time you create an alarm in the Amazon Web Services %% Management Console, the CLI, or by using the PutMetricAlarm API, %% CloudWatch creates the necessary service-linked role for you. The %% service-linked roles are called `AWSServiceRoleForCloudWatchEvents' and %% `AWSServiceRoleForCloudWatchAlarms_ActionSSM'. For more information, see %% Amazon Web Services service-linked role. %% %% Cross-account alarms %% %% You can set an alarm on metrics in the current account, or in another %% account. To create a cross-account alarm that watches a metric in a %% different account, you must have completed the following pre-requisites: %% %% put_metric_alarm(Client, Input) when is_map(Client), is_map(Input) -> put_metric_alarm(Client, Input, []). put_metric_alarm(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"PutMetricAlarm">>, Input, Options). %% @doc Publishes metric data points to Amazon CloudWatch. %% %% CloudWatch associates the data points with the specified metric. If the %% specified metric does not exist, CloudWatch creates the metric. When %% CloudWatch creates a metric, it can take up to fifteen minutes for the %% metric to appear in calls to ListMetrics. %% %% You can publish either individual data points in the `Value' field, or %% arrays of values and the number of times each value occurred during the %% period by using the `Values' and `Counts' fields in the `MetricDatum' %% structure. Using the `Values' and `Counts' method enables you to publish %% up to 150 values per metric with one `PutMetricData' request, and supports %% retrieving percentile statistics on this data. %% %% Each `PutMetricData' request is limited to 1 MB in size for HTTP POST %% requests. You can send a payload compressed by gzip. Each request is also %% limited to no more than 1000 different metrics. %% %% Although the `Value' parameter accepts numbers of type `Double', %% CloudWatch rejects values that are either too small or too large. Values %% must be in the range of -2^360 to 2^360. In addition, special values (for %% example, NaN, +Infinity, -Infinity) are not supported. %% %% You can use up to 30 dimensions per metric to further clarify what data %% the metric collects. Each dimension consists of a Name and Value pair. For %% more information about specifying dimensions, see Publishing Metrics in %% the Amazon CloudWatch User Guide. %% %% You specify the time stamp to be associated with each data point. You can %% specify time stamps that are as much as two weeks before the current date, %% and as much as 2 hours after the current day and time. %% %% Data points with time stamps from 24 hours ago or longer can take at least %% 48 hours to become available for GetMetricData or GetMetricStatistics from %% the time they are submitted. Data points with time stamps between 3 and 24 %% hours ago can take as much as 2 hours to become available for for %% GetMetricData or GetMetricStatistics. %% %% CloudWatch needs raw data points to calculate percentile statistics. If %% you publish data using a statistic set instead, you can only retrieve %% percentile statistics for this data if one of the following conditions is %% true: %% %% put_metric_data(Client, Input) when is_map(Client), is_map(Input) -> put_metric_data(Client, Input, []). put_metric_data(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"PutMetricData">>, Input, Options). %% @doc Creates or updates a metric stream. %% %% Metric streams can automatically stream CloudWatch metrics to Amazon Web %% Services destinations, including Amazon S3, and to many third-party %% solutions. %% %% For more information, see Using Metric Streams. %% %% To create a metric stream, you must be signed in to an account that has %% the `iam:PassRole' permission and either the `CloudWatchFullAccess' policy %% or the `cloudwatch:PutMetricStream' permission. %% %% When you create or update a metric stream, you choose one of the %% following: %% %% By default, a metric stream always sends the `MAX', `MIN', %% `SUM', and `SAMPLECOUNT' statistics for each metric that is streamed. You %% can use the `StatisticsConfigurations' parameter to have the metric stream %% send additional statistics in the stream. Streaming additional statistics %% incurs additional costs. For more information, see Amazon CloudWatch %% Pricing. %% %% When you use `PutMetricStream' to create a new metric stream, the stream %% is created in the `running' state. If you use it to update an existing %% stream, the state of the stream is not changed. %% %% If you are using CloudWatch cross-account observability and you create a %% metric stream in a monitoring account, you can choose whether to include %% metrics from source accounts in the stream. For more information, see %% CloudWatch cross-account observability. put_metric_stream(Client, Input) when is_map(Client), is_map(Input) -> put_metric_stream(Client, Input, []). put_metric_stream(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"PutMetricStream">>, Input, Options). %% @doc Temporarily sets the state of an alarm for testing purposes. %% %% When the updated state differs from the previous value, the action %% configured for the appropriate state is invoked. For example, if your %% alarm is configured to send an Amazon SNS message when an alarm is %% triggered, temporarily changing the alarm state to `ALARM' sends an SNS %% message. %% %% Metric alarms returns to their actual state quickly, often within seconds. %% Because the metric alarm state change happens quickly, it is typically %% only visible in the alarm's History tab in the Amazon CloudWatch console %% or through DescribeAlarmHistory. %% %% If you use `SetAlarmState' on a composite alarm, the composite alarm is %% not guaranteed to return to its actual state. It returns to its actual %% state only once any of its children alarms change state. It is also %% reevaluated if you update its configuration. %% %% If an alarm triggers EC2 Auto Scaling policies or application Auto Scaling %% policies, you must include information in the `StateReasonData' parameter %% to enable the policy to take the correct action. set_alarm_state(Client, Input) when is_map(Client), is_map(Input) -> set_alarm_state(Client, Input, []). set_alarm_state(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"SetAlarmState">>, Input, Options). %% @doc Starts the streaming of metrics for one or more of your metric %% streams. start_metric_streams(Client, Input) when is_map(Client), is_map(Input) -> start_metric_streams(Client, Input, []). start_metric_streams(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"StartMetricStreams">>, Input, Options). %% @doc Stops the streaming of metrics for one or more of your metric %% streams. stop_metric_streams(Client, Input) when is_map(Client), is_map(Input) -> stop_metric_streams(Client, Input, []). stop_metric_streams(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"StopMetricStreams">>, Input, Options). %% @doc Assigns one or more tags (key-value pairs) to the specified %% CloudWatch resource. %% %% Currently, the only CloudWatch resources that can be tagged are alarms and %% Contributor Insights rules. %% %% Tags can help you organize and categorize your resources. You can also use %% them to scope user permissions by granting a user permission to access or %% change only resources with certain tag values. %% %% Tags don't have any semantic meaning to Amazon Web Services and are %% interpreted strictly as strings of characters. %% %% You can use the `TagResource' action with an alarm that already has tags. %% If you specify a new tag key for the alarm, this tag is appended to the %% list of tags associated with the alarm. If you specify a tag key that is %% already associated with the alarm, the new tag value that you specify %% replaces the previous value for that tag. %% %% You can associate as many as 50 tags with a CloudWatch resource. tag_resource(Client, Input) when is_map(Client), is_map(Input) -> tag_resource(Client, Input, []). tag_resource(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"TagResource">>, Input, Options). %% @doc Removes one or more tags from the specified resource. untag_resource(Client, Input) when is_map(Client), is_map(Input) -> untag_resource(Client, Input, []). untag_resource(Client, Input, Options) when is_map(Client), is_map(Input), is_list(Options) -> request(Client, <<"UntagResource">>, 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, Input, Options) -> RequestFun = fun() -> do_request(Client, Action, Input, Options) end, aws_request:request(RequestFun, Options). do_request(Client, Action, Input0, Options) -> Client1 = Client#{service => <<"monitoring">>}, Host = build_host(<<"monitoring">>, Client1), URL = build_url(Host, Client1), Headers = [ {<<"Host">>, Host}, {<<"Content-Type">>, <<"application/x-www-form-urlencoded">>} ], Input = Input0#{ <<"Action">> => Action , <<"Version">> => <<"2010-08-01">> }, Payload = aws_util:encode_query(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 = aws_util:decode_xml(Body), {ok, Result, {200, ResponseHeaders, Client}} end; handle_response({ok, StatusCode, ResponseHeaders, Client}) -> {ok, Body} = hackney:body(Client), Error = aws_util:decode_xml(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, <<"/">>], <<"">>).