Package 'paws.management'

Description

With Application Auto Scaling, you can configure automatic scaling for the following resources:

• Amazon AppStream 2.0 fleets

• Amazon Aurora Replicas

• Amazon Comprehend document classification and entity recognizer endpoints

• Amazon DynamoDB tables and global secondary indexes throughput capacity

• Amazon ECS services

• Amazon ElastiCache for Redis clusters (replication groups)

• Amazon EMR clusters

• Amazon Keyspaces (for Apache Cassandra) tables

• Lambda function provisioned concurrency

• Amazon Managed Streaming for Apache Kafka broker storage

• Amazon Neptune clusters

• Amazon SageMaker endpoint variants

• Amazon SageMaker inference components

• Amazon SageMaker serverless endpoint provisioned concurrency

• Spot Fleets (Amazon EC2)

• Pool of WorkSpaces

• Custom resources provided by your own applications or services

To learn more about Application Auto Scaling, see the Application Auto Scaling User Guide.

API Summary

The Application Auto Scaling service API includes three key sets of actions:

• Register and manage scalable targets - Register Amazon Web Services or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets.

• Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history.

• Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the register_scalable_target API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling.

Usage

applicationautoscaling(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- applicationautoscaling(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- applicationautoscaling()
# This example deletes a scaling policy for the Amazon ECS service called
# web-app, which is running in the default cluster.
svc$delete_scaling_policy(
  PolicyName = "web-app-cpu-lt-25",
  ResourceId = "service/default/web-app",
  ScalableDimension = "ecs:service:DesiredCount",
  ServiceNamespace = "ecs"
)

## End(Not run)

Description

This reference provides descriptions of the AWS Application Cost Profiler API.

The AWS Application Cost Profiler API provides programmatic access to view, create, update, and delete application cost report definitions, as well as to import your usage data into the Application Cost Profiler service.

For more information about using this service, see the AWS Application Cost Profiler User Guide.

Usage

applicationcostprofiler(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- applicationcostprofiler(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- applicationcostprofiler()
svc$delete_report_definition(
  Foo = 123
)

## End(Not run)

Description

Amazon CloudWatch Application Insights is a service that helps you detect common problems with your applications. It enables you to pinpoint the source of issues in your applications (built with technologies such as Microsoft IIS, .NET, and Microsoft SQL Server), by providing key insights into detected problems.

After you onboard your application, CloudWatch Application Insights identifies, recommends, and sets up metrics and logs. It continuously analyzes and correlates your metrics and logs for unusual behavior to surface actionable problems with your application. For example, if your application is slow and unresponsive and leading to HTTP 500 errors in your Application Load Balancer (ALB), Application Insights informs you that a memory pressure problem with your SQL Server database is occurring. It bases this analysis on impactful metrics and log errors.

Usage

applicationinsights(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- applicationinsights(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- applicationinsights()
svc$add_workload(
  Foo = 123
)

## End(Not run)

Description

Amazon Web Services Service Catalog AppRegistry enables organizations to understand the application context of their Amazon Web Services resources. AppRegistry provides a repository of your applications, their resources, and the application metadata that you use within your enterprise.

Usage

appregistry(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- appregistry(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- appregistry()
svc$associate_attribute_group(
  Foo = 123
)

## End(Not run)

Description

Welcome to the Audit Manager API reference. This guide is for developers who need detailed information about the Audit Manager API operations, data types, and errors.

Audit Manager is a service that provides automated evidence collection so that you can continually audit your Amazon Web Services usage. You can use it to assess the effectiveness of your controls, manage risk, and simplify compliance.

Audit Manager provides prebuilt frameworks that structure and automate assessments for a given compliance standard. Frameworks include a prebuilt collection of controls with descriptions and testing procedures. These controls are grouped according to the requirements of the specified compliance standard or regulation. You can also customize frameworks and controls to support internal audits with specific requirements.

Use the following links to get started with the Audit Manager API:

• Actions: An alphabetical list of all Audit Manager API operations.

• Data types: An alphabetical list of all Audit Manager data types.

• Common parameters: Parameters that all operations can use.

• Common errors: Client and server errors that all operations can return.

If you're new to Audit Manager, we recommend that you review the Audit Manager User Guide.

Usage

auditmanager(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- auditmanager(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- auditmanager()
svc$associate_assessment_report_evidence_folder(
  Foo = 123
)

## End(Not run)

Description

Amazon EC2 Auto Scaling

Amazon EC2 Auto Scaling is designed to automatically launch and terminate EC2 instances based on user-defined scaling policies, scheduled actions, and health checks.

For more information, see the Amazon EC2 Auto Scaling User Guide and the Amazon EC2 Auto Scaling API Reference.

Usage

autoscaling(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- autoscaling(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- autoscaling()
# This example attaches the specified instance to the specified Auto
# Scaling group.
svc$attach_instances(
  AutoScalingGroupName = "my-auto-scaling-group",
  InstanceIds = list(
    "i-93633f9b"
  )
)

## End(Not run)

Description

AWS Auto Scaling

Use AWS Auto Scaling to create scaling plans for your applications to automatically scale your scalable AWS resources.

API Summary

You can use the AWS Auto Scaling service API to accomplish the following tasks:

• Create and manage scaling plans

• Define target tracking scaling policies to dynamically scale your resources based on utilization

• Scale Amazon EC2 Auto Scaling groups using predictive scaling and dynamic scaling to scale your Amazon EC2 capacity faster

• Set minimum and maximum capacity limits

• Retrieve information on existing scaling plans

• Access current forecast data and historical forecast data for up to 56 days previous

To learn more about AWS Auto Scaling, including information about granting IAM users required permissions for AWS Auto Scaling actions, see the AWS Auto Scaling User Guide.

Usage

autoscalingplans(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- autoscalingplans(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- autoscalingplans()
svc$create_scaling_plan(
  Foo = 123
)

## End(Not run)

Description

CloudFormation

CloudFormation allows you to create and manage Amazon Web Services infrastructure deployments predictably and repeatedly. You can use CloudFormation to leverage Amazon Web Services products, such as Amazon Elastic Compute Cloud, Amazon Elastic Block Store, Amazon Simple Notification Service, Elastic Load Balancing, and Auto Scaling to build highly reliable, highly scalable, cost-effective applications without creating or configuring the underlying Amazon Web Services infrastructure.

With CloudFormation, you declare all your resources and dependencies in a template file. The template defines a collection of resources as a single unit called a stack. CloudFormation creates and deletes all member resources of the stack together and manages all dependencies between the resources for you.

For more information about CloudFormation, see the CloudFormation product page.

CloudFormation makes use of other Amazon Web Services products. If you need additional technical information about a specific Amazon Web Services product, you can find the product's technical documentation at docs.aws.amazon.com.

Usage

cloudformation(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudformation(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudformation()
# This example creates a generated template with a resources file.
svc$create_generated_template(
  GeneratedTemplateName = "JazzyTemplate",
  Resources = list(
    list(
      ResourceIdentifier = list(
        BucketName = "jazz-bucket"
      ),
      ResourceType = "AWS::S3::Bucket"
    ),
    list(
      ResourceIdentifier = list(
        DhcpOptionsId = "random-id123"
      ),
      ResourceType = "AWS::EC2::DHCPOptions"
    )
  )
)

## End(Not run)

Description

CloudTrail

This is the CloudTrail API Reference. It provides descriptions of actions, data types, common parameters, and common errors for CloudTrail.

CloudTrail is a web service that records Amazon Web Services API calls for your Amazon Web Services account and delivers log files to an Amazon S3 bucket. The recorded information includes the identity of the user, the start time of the Amazon Web Services API call, the source IP address, the request parameters, and the response elements returned by the service.

As an alternative to the API, you can use one of the Amazon Web Services SDKs, which consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .NET, iOS, Android, etc.). The SDKs provide programmatic access to CloudTrail. For example, the SDKs handle cryptographically signing requests, managing errors, and retrying requests automatically. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools to Build on Amazon Web Services.

See the CloudTrail User Guide for information about the data that is included with each Amazon Web Services API call listed in the log files.

Usage

cloudtrail(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudtrail(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudtrail()
svc$add_tags(
  Foo = 123
)

## End(Not run)

Description

The CloudTrail Data Service lets you ingest events into CloudTrail from any source in your hybrid environments, such as in-house or SaaS applications hosted on-premises or in the cloud, virtual machines, or containers. You can store, access, analyze, troubleshoot and take action on this data without maintaining multiple log aggregators and reporting tools. After you run put_audit_events to ingest your application activity into CloudTrail, you can use CloudTrail Lake to search, query, and analyze the data that is logged from your applications.

Usage

cloudtraildataservice(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudtraildataservice(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudtraildataservice()
svc$put_audit_events(
  Foo = 123
)

## End(Not run)

Description

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.

Usage

cloudwatch(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudwatch(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudwatch()
svc$delete_alarms(
  Foo = 123
)

## End(Not run)

Description

Amazon EventBridge helps you to respond to state changes in your Amazon Web Services resources. When your resources change state, they automatically send events to an event stream. You can create rules that match selected events in the stream and route them to targets to take action. You can also use rules to take action on a predetermined schedule. For example, you can configure rules to:

• Automatically invoke an Lambda function to update DNS entries when an event notifies you that Amazon EC2 instance enters the running state.

• Direct specific API records from CloudTrail to an Amazon Kinesis data stream for detailed analysis of potential security or availability risks.

• Periodically invoke a built-in target to create a snapshot of an Amazon EBS volume.

For more information about the features of Amazon EventBridge, see the Amazon EventBridge User Guide.

Usage

cloudwatchevents(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudwatchevents(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudwatchevents()
svc$activate_event_source(
  Foo = 123
)

## End(Not run)

Description

You can use Amazon CloudWatch Evidently to safely validate new features by serving them to a specified percentage of your users while you roll out the feature. You can monitor the performance of the new feature to help you decide when to ramp up traffic to your users. This helps you reduce risk and identify unintended consequences before you fully launch the feature.

You can also conduct A/B experiments to make feature design decisions based on evidence and data. An experiment can test as many as five variations at once. Evidently collects experiment data and analyzes it using statistical methods. It also provides clear recommendations about which variations perform better. You can test both user-facing features and backend features.

Usage

cloudwatchevidently(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudwatchevidently(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudwatchevidently()
svc$batch_evaluate_feature(
  Foo = 123
)

## End(Not run)

Description

Amazon CloudWatch Internet Monitor provides visibility into how internet issues impact the performance and availability between your applications hosted on Amazon Web Services and your end users. It can reduce the time it takes for you to diagnose internet issues from days to minutes. Internet Monitor uses the connectivity data that Amazon Web Services captures from its global networking footprint to calculate a baseline of performance and availability for internet traffic. This is the same data that Amazon Web Services uses to monitor internet uptime and availability. With those measurements as a baseline, Internet Monitor raises awareness for you when there are significant problems for your end users in the different geographic locations where your application runs.

Internet Monitor publishes internet measurements to CloudWatch Logs and CloudWatch Metrics, to easily support using CloudWatch tools with health information for geographies and networks specific to your application. Internet Monitor sends health events to Amazon EventBridge so that you can set up notifications. If an issue is caused by the Amazon Web Services network, you also automatically receive an Amazon Web Services Health Dashboard notification with the steps that Amazon Web Services is taking to mitigate the problem.

To use Internet Monitor, you create a monitor and associate your application's resources with it - VPCs, NLBs, CloudFront distributions, or WorkSpaces directories - so Internet Monitor can determine where your application's internet traffic is. Internet Monitor then provides internet measurements from Amazon Web Services that are specific to the locations and ASNs (typically, internet service providers or ISPs) that communicate with your application.

For more information, see Using Amazon CloudWatch Internet Monitor in the Amazon CloudWatch User Guide.

Usage

cloudwatchinternetmonitor(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudwatchinternetmonitor(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudwatchinternetmonitor()
svc$create_monitor(
  Foo = 123
)

## End(Not run)

Description

You can use Amazon CloudWatch Logs to monitor, store, and access your log files from EC2 instances, CloudTrail, and other sources. You can then retrieve the associated log data from CloudWatch Logs using the CloudWatch console. Alternatively, you can use CloudWatch Logs commands in the Amazon Web Services CLI, CloudWatch Logs API, or CloudWatch Logs SDK.

You can use CloudWatch Logs to:

• Monitor logs from EC2 instances in real time: You can use CloudWatch Logs to monitor applications and systems using log data. For example, CloudWatch Logs can track the number of errors that occur in your application logs. Then, it can send you a notification whenever the rate of errors exceeds a threshold that you specify. CloudWatch Logs uses your log data for monitoring so no code changes are required. For example, you can monitor application logs for specific literal terms (such as "NullReferenceException"). You can also count the number of occurrences of a literal term at a particular position in log data (such as "404" status codes in an Apache access log). When the term you are searching for is found, CloudWatch Logs reports the data to a CloudWatch metric that you specify.

• Monitor CloudTrail logged events: You can create alarms in CloudWatch and receive notifications of particular API activity as captured by CloudTrail. You can use the notification to perform troubleshooting.

• Archive log data: You can use CloudWatch Logs to store your log data in highly durable storage. You can change the log retention setting so that any log events earlier than this setting are automatically deleted. The CloudWatch Logs agent helps to quickly send both rotated and non-rotated log data off of a host and into the log service. You can then access the raw log data when you need it.

Usage

cloudwatchlogs(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudwatchlogs(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudwatchlogs()
svc$associate_kms_key(
  Foo = 123
)

## End(Not run)

Description

Use Amazon CloudWatch Observability Access Manager to create and manage links between source accounts and monitoring accounts by using CloudWatch cross-account observability. With CloudWatch cross-account observability, you can monitor and troubleshoot applications that span multiple accounts within a Region. Seamlessly search, visualize, and analyze your metrics, logs, traces, and Application Insights applications in any of the linked accounts without account boundaries.

Set up one or more Amazon Web Services accounts as monitoring accounts and link them with multiple source accounts. A monitoring account is a central Amazon Web Services account that can view and interact with observability data generated from source accounts. A source account is an individual Amazon Web Services account that generates observability data for the resources that reside in it. Source accounts share their observability data with the monitoring account. The shared observability data can include metrics in Amazon CloudWatch, logs in Amazon CloudWatch Logs, traces in X-Ray, and applications in Amazon CloudWatch Application Insights.

Usage

cloudwatchobservabilityaccessmanager(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudwatchobservabilityaccessmanager(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudwatchobservabilityaccessmanager()
svc$create_link(
  Foo = 123
)

## End(Not run)

Description

With Amazon CloudWatch RUM, you can perform real-user monitoring to collect client-side data about your web application performance from actual user sessions in real time. The data collected includes page load times, client-side errors, and user behavior. When you view this data, you can see it all aggregated together and also see breakdowns by the browsers and devices that your customers use.

You can use the collected data to quickly identify and debug client-side performance issues. CloudWatch RUM helps you visualize anomalies in your application performance and find relevant debugging data such as error messages, stack traces, and user sessions. You can also use RUM to understand the range of end-user impact including the number of users, geolocations, and browsers used.

Usage

cloudwatchrum(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- cloudwatchrum(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- cloudwatchrum()
svc$batch_create_rum_metric_definitions(
  Foo = 123
)

## End(Not run)

Description

Config

Config provides a way to keep track of the configurations of all the Amazon Web Services resources associated with your Amazon Web Services account. You can use Config to get the current and historical configurations of each Amazon Web Services resource and also to get information about the relationship between the resources. An Amazon Web Services resource can be an Amazon Compute Cloud (Amazon EC2) instance, an Elastic Block Store (EBS) volume, an elastic network Interface (ENI), or a security group. For a complete list of resources currently supported by Config, see Supported Amazon Web Services resources.

You can access and manage Config through the Amazon Web Services Management Console, the Amazon Web Services Command Line Interface (Amazon Web Services CLI), the Config API, or the Amazon Web Services SDKs for Config. This reference guide contains documentation for the Config API and the Amazon Web Services CLI commands that you can use to manage Config. The Config API uses the Signature Version 4 protocol for signing requests. For more information about how to sign a request with this protocol, see Signature Version 4 Signing Process. For detailed information about Config features and their associated actions or commands, as well as how to work with Amazon Web Services Management Console, see What Is Config in the Config Developer Guide.

Usage

configservice(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- configservice(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- configservice()
svc$batch_get_aggregate_resource_config(
  Foo = 123
)

## End(Not run)

Description

Amazon Web Services Control Tower offers application programming interface (API) operations that support programmatic interaction with these types of resources:

• Controls

  • disable_control

  • enable_control

  • get_enabled_control

  • list_control_operations

  • list_enabled_controls

  • update_enabled_control

• Landing zones

  • create_landing_zone

  • delete_landing_zone

  • get_landing_zone

  • get_landing_zone_operation

  • list_landing_zones

  • list_landing_zone_operations

  • reset_landing_zone

  • update_landing_zone

• Baselines

  • disable_baseline

  • enable_baseline

  • get_baseline

  • get_baseline_operation

  • get_enabled_baseline

  • list_baselines

  • list_enabled_baselines

  • reset_enabled_baseline

  • update_enabled_baseline

• Tagging

  • list_tags_for_resource

  • tag_resource

  • untag_resource

For more information about these types of resources, see the Amazon Web Services Control Tower User Guide .

About control APIs

These interfaces allow you to apply the Amazon Web Services library of pre-defined controls to your organizational units, programmatically. In Amazon Web Services Control Tower, the terms "control" and "guardrail" are synonyms.

To call these APIs, you'll need to know:

• the controlIdentifier for the control–or guardrail–you are targeting.

• the ARN associated with the target organizational unit (OU), which we call the targetIdentifier.

• the ARN associated with a resource that you wish to tag or untag.

To get the controlIdentifier for your Amazon Web Services Control Tower control:

The controlIdentifier is an ARN that is specified for each control. You can view the controlIdentifier in the console on the Control details page, as well as in the documentation.

About identifiers for Amazon Web Services Control Tower

The Amazon Web Services Control Tower controlIdentifier is unique in each Amazon Web Services Region for each control. You can find the controlIdentifier for each Region and control in the Tables of control metadata or the Control availability by Region tables in the Amazon Web Services Control Tower Controls Reference Guide.

A quick-reference list of control identifers for the Amazon Web Services Control Tower legacy Strongly recommended and Elective controls is given in Resource identifiers for APIs and controls in the Amazon Web Services Control Tower Controls Reference Guide . Remember that Mandatory controls cannot be added or removed.

Some controls have two identifiers

• ARN format for Amazon Web Services Control Tower: ⁠arn:aws:controltower:{REGION}::control/{CONTROL_TOWER_OPAQUE_ID}⁠

  Example:

  ⁠arn:aws:controltower:us-west-2::control/AWS-GR_AUTOSCALING_LAUNCH_CONFIG_PUBLIC_IP_DISABLED⁠

• ARN format for Amazon Web Services Control Catalog: arn:{PARTITION}:controlcatalog:::control/{CONTROL_CATALOG_OPAQUE_ID}

You can find the {CONTROL_CATALOG_OPAQUE_ID} in the Amazon Web Services Control Tower Controls Reference Guide , or in the Amazon Web Services Control Tower console, on the Control details page.

The Amazon Web Services Control Tower APIs for enabled controls, such as get_enabled_control and list_enabled_controls always return an ARN of the same type given when the control was enabled.

To get the targetIdentifier:

The targetIdentifier is the ARN for an OU.

In the Amazon Web Services Organizations console, you can find the ARN for the OU on the Organizational unit details page associated with that OU.

OU ARN format:

⁠arn:${Partition}:organizations::${MasterAccountId}:ou/o-${OrganizationId}/ou-${OrganizationalUnitId}⁠

About landing zone APIs

You can configure and launch an Amazon Web Services Control Tower landing zone with APIs. For an introduction and steps, see Getting started with Amazon Web Services Control Tower using APIs.

For an overview of landing zone API operations, see Amazon Web Services Control Tower supports landing zone APIs. The individual API operations for landing zones are detailed in this document, the API reference manual, in the "Actions" section.

About baseline APIs

You can apply the AWSControlTowerBaseline baseline to an organizational unit (OU) as a way to register the OU with Amazon Web Services Control Tower, programmatically. For a general overview of this capability, see Amazon Web Services Control Tower supports APIs for OU registration and configuration with baselines.

You can call the baseline API operations to view the baselines that Amazon Web Services Control Tower enables for your landing zone, on your behalf, when setting up the landing zone. These baselines are read-only baselines.

The individual API operations for baselines are detailed in this document, the API reference manual, in the "Actions" section. For usage examples, see Baseline API input and output examples with CLI.

About Amazon Web Services Control Catalog identifiers

• The enable_control and disable_control API operations can be called by specifying either the Amazon Web Services Control Tower identifer or the Amazon Web Services Control Catalog identifier. The API response returns the same type of identifier that you specified when calling the API.

• If you use an Amazon Web Services Control Tower identifier to call the enable_control API, and then call enable_control again with an Amazon Web Services Control Catalog identifier, Amazon Web Services Control Tower returns an error message stating that the control is already enabled. Similar behavior applies to the disable_control API operation.

• Mandatory controls and the landing-zone-level Region deny control have Amazon Web Services Control Tower identifiers only.

Details and examples

• Control API input and output examples with CLI

• Baseline API input and output examples with CLI

• Enable controls with CloudFormation

• Launch a landing zone with CloudFormation

• Control metadata tables (large page)

• Control availability by Region tables (large page)

• List of identifiers for legacy controls

• Controls reference guide

• Controls library groupings

• Creating Amazon Web Services Control Tower resources with Amazon Web Services CloudFormation

To view the open source resource repository on GitHub, see aws-cloudformation/aws-cloudformation-resource-providers-controltower

Recording API Requests

Amazon Web Services Control Tower supports Amazon Web Services CloudTrail, a service that records Amazon Web Services API calls for your Amazon Web Services account and delivers log files to an Amazon S3 bucket. By using information collected by CloudTrail, you can determine which requests the Amazon Web Services Control Tower service received, who made the request and when, and so on. For more about Amazon Web Services Control Tower and its support for CloudTrail, see Logging Amazon Web Services Control Tower Actions with Amazon Web Services CloudTrail in the Amazon Web Services Control Tower User Guide. To learn more about CloudTrail, including how to turn it on and find your log files, see the Amazon Web Services CloudTrail User Guide.

Usage

controltower(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- controltower(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- controltower()
svc$create_landing_zone(
  Foo = 123
)

## End(Not run)

Description

The FinSpace management service provides the APIs for managing FinSpace environments.

Usage

finspace(config = list(), credentials = list(), endpoint = NULL, region = NULL)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- finspace(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- finspace()
svc$create_environment(
  Foo = 123
)

## End(Not run)

Description

Health

The Health API provides access to the Health information that appears in the Health Dashboard. You can use the API operations to get information about events that might affect your Amazon Web Services and resources.

You must have a Business, Enterprise On-Ramp, or Enterprise Support plan from Amazon Web Services Support to use the Health API. If you call the Health API from an Amazon Web Services account that doesn't have a Business, Enterprise On-Ramp, or Enterprise Support plan, you receive a SubscriptionRequiredException error.

For API access, you need an access key ID and a secret access key. Use temporary credentials instead of long-term access keys when possible. Temporary credentials include an access key ID, a secret access key, and a security token that indicates when the credentials expire. For more information, see Best practices for managing Amazon Web Services access keys in the Amazon Web Services General Reference.

You can use the Health endpoint health.us-east-1.amazonaws.com (HTTPS) to call the Health API operations. Health supports a multi-Region application architecture and has two regional endpoints in an active-passive configuration. You can use the high availability endpoint example to determine which Amazon Web Services Region is active, so that you can get the latest information from the API. For more information, see Accessing the Health API in the Health User Guide.

For authentication of requests, Health uses the Signature Version 4 Signing Process.

If your Amazon Web Services account is part of Organizations, you can use the Health organizational view feature. This feature provides a centralized view of Health events across all accounts in your organization. You can aggregate Health events in real time to identify accounts in your organization that are affected by an operational event or get notified of security vulnerabilities. Use the organizational view API operations to enable this feature and return event information. For more information, see Aggregating Health events in the Health User Guide.

When you use the Health API operations to return Health events, see the following recommendations:

• Use the eventScopeCode parameter to specify whether to return Health events that are public or account-specific.

• Use pagination to view all events from the response. For example, if you call the describe_events_for_organization operation to get all events in your organization, you might receive several page results. Specify the nextToken in the next request to return more results.

Usage

health(config = list(), credentials = list(), endpoint = NULL, region = NULL)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- health(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- health()
svc$describe_affected_accounts_for_organization(
  Foo = 123
)

## End(Not run)

Description

License Manager makes it easier to manage licenses from software vendors across multiple Amazon Web Services accounts and on-premises servers.

Usage

licensemanager(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- licensemanager(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- licensemanager()
svc$accept_grant(
  Foo = 123
)

## End(Not run)

Description

With License Manager, you can discover and track your commercial Linux subscriptions on running Amazon EC2 instances.

Usage

licensemanagerlinuxsubscriptions(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- licensemanagerlinuxsubscriptions(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- licensemanagerlinuxsubscriptions()
svc$deregister_subscription_provider(
  Foo = 123
)

## End(Not run)

Description

With License Manager, you can create user-based subscriptions to utilize licensed software with a per user subscription fee on Amazon EC2 instances.

Usage

licensemanagerusersubscriptions(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- licensemanagerusersubscriptions(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- licensemanagerusersubscriptions()
svc$associate_user(
  Foo = 123
)

## End(Not run)

Description

Amazon Managed Grafana is a fully managed and secure data visualization service that you can use to instantly query, correlate, and visualize operational metrics, logs, and traces from multiple sources. Amazon Managed Grafana makes it easy to deploy, operate, and scale Grafana, a widely deployed data visualization tool that is popular for its extensible data support.

With Amazon Managed Grafana, you create logically isolated Grafana servers called workspaces. In a workspace, you can create Grafana dashboards and visualizations to analyze your metrics, logs, and traces without having to build, package, or deploy any hardware to run Grafana servers.

Usage

managedgrafana(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- managedgrafana(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

Examples

## Not run: 
svc <- managedgrafana()
svc$associate_license(
  Foo = 123
)

## End(Not run)

Description

OpsWorks

Welcome to the OpsWorks Stacks API Reference. This guide provides descriptions, syntax, and usage examples for OpsWorks Stacks actions and data types, including common parameters and error codes.

OpsWorks Stacks is an application management service that provides an integrated experience for managing the complete application lifecycle. For information about OpsWorks, see the OpsWorks information page.

SDKs and CLI

Use the OpsWorks Stacks API by using the Command Line Interface (CLI) or by using one of the Amazon Web Services SDKs to implement applications in your preferred language. For more information, see:

• CLI

• SDK for Java

• SDK for .NET

• SDK for PHP

• SDK for Ruby

• Amazon Web Services SDK for Node.js

• SDK for Python (Boto)

Endpoints

OpsWorks Stacks supports the following endpoints, all HTTPS. You must connect to one of the following endpoints. Stacks can only be accessed or managed within the endpoint in which they are created.

• opsworks.us-east-1.amazonaws.com

• opsworks.us-east-2.amazonaws.com

• opsworks.us-west-1.amazonaws.com

• opsworks.us-west-2.amazonaws.com

• opsworks.ca-central-1.amazonaws.com (API only; not available in the Amazon Web Services Management Console)

• opsworks.eu-west-1.amazonaws.com

• opsworks.eu-west-2.amazonaws.com

• opsworks.eu-west-3.amazonaws.com

• opsworks.eu-central-1.amazonaws.com

• opsworks.ap-northeast-1.amazonaws.com

• opsworks.ap-northeast-2.amazonaws.com

• opsworks.ap-south-1.amazonaws.com

• opsworks.ap-southeast-1.amazonaws.com

• opsworks.ap-southeast-2.amazonaws.com

• opsworks.sa-east-1.amazonaws.com

Chef Versions

When you call create_stack, clone_stack, or update_stack we recommend you use the ConfigurationManager parameter to specify the Chef version. The recommended and default value for Linux stacks is currently 12. Windows stacks use Chef 12.2. For more information, see Chef Versions.

You can specify Chef 12, 11.10, or 11.4 for your Linux stack. We recommend migrating your existing Linux stacks to Chef 12 as soon as possible.

Usage

opsworks(config = list(), credentials = list(), endpoint = NULL, region = NULL)

Arguments

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- opsworks(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations