Mock sample for your project: Amazon Connect Customer Profiles API

Integrate with "Amazon Connect Customer Profiles API" from amazonaws.com in no time with Mockoon's ready to use mock sample

Amazon Connect Customer Profiles

amazonaws.com

Version: 2020-08-15


Use this API in your project

Integrate third-party APIs faster by using "Amazon Connect Customer Profiles API" ready-to-use mock sample. Mocking this API will help you accelerate your development lifecycles and improves your integration tests' quality and reliability by accounting for random failures, slow response time, etc.
It also helps reduce your dependency on third-party APIs: no more accounts to create, API keys to provision, accesses to configure, unplanned downtime, etc.

Description

Amazon Connect Customer Profiles Welcome to the Amazon Connect Customer Profiles API Reference. This guide provides information about the Amazon Connect Customer Profiles API, including supported operations, data types, parameters, and schemas. Amazon Connect Customer Profiles is a unified customer profile for your contact center that has pre-built connectors powered by AppFlow that make it easy to combine customer information from third party applications, such as Salesforce (CRM), ServiceNow (ITSM), and your enterprise resource planning (ERP), with contact history from your Amazon Connect contact center. If you're new to Amazon Connect , you might find it helpful to also review the Amazon Connect Administrator Guide.

Other APIs by amazonaws.com

AWS IoT Greengrass V2

IoT Greengrass brings local compute, messaging, data management, sync, and ML inference capabilities to edge devices. This enables devices to collect and analyze data closer to the source of information, react autonomously to local events, and communicate securely with each other on local networks. Local devices can also communicate securely with Amazon Web Services IoT Core and export IoT data to the Amazon Web Services Cloud. IoT Greengrass developers can use Lambda functions and components to create and deploy applications to fleets of edge devices for local operation. IoT Greengrass Version 2 provides a new major version of the IoT Greengrass Core software, new APIs, and a new console. Use this API reference to learn how to use the IoT Greengrass V2 API operations to manage components, manage deployments, and core devices. For more information, see What is IoT Greengrass? in the IoT Greengrass V2 Developer Guide.

AWS MediaTailor

Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide. Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).

AWS Elemental MediaPackage

AWS Elemental MediaPackage

AWS Cost and Usage Report Service

The AWS Cost and Usage Report API enables you to programmatically create, query, and delete AWS Cost and Usage report definitions. AWS Cost and Usage reports track the monthly AWS costs and usage associated with your AWS account. The report contains line items for each unique combination of AWS product, usage type, and operation that your AWS account uses. You can configure the AWS Cost and Usage report to show only the data that you want, using the AWS Cost and Usage API. Service Endpoint The AWS Cost and Usage Report API provides the following endpoint: cur.us-east-1.amazonaws.com

Amazon CloudWatch Application Insights

Amazon CloudWatch Application Insights 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.

AWS Marketplace Commerce Analytics

Provides AWS Marketplace business intelligence data on-demand.

Access Analyzer

Identity and Access Management Access Analyzer helps identify potential resource-access risks by enabling you to identify any policies that grant access to an external principal. It does this by using logic-based reasoning to analyze resource-based policies in your Amazon Web Services environment. An external principal can be another Amazon Web Services account, a root user, an IAM user or role, a federated user, an Amazon Web Services service, or an anonymous user. You can also use IAM Access Analyzer to preview and validate public and cross-account access to your resources before deploying permissions changes. This guide describes the Identity and Access Management Access Analyzer operations that you can call programmatically. For general information about IAM Access Analyzer, see Identity and Access Management Access Analyzer in the IAM User Guide. To start using IAM Access Analyzer, you first need to create an analyzer.

AWS Performance Insights

Amazon RDS Performance Insights Amazon RDS Performance Insights enables you to monitor and explore different dimensions of database load based on data captured from a running DB instance. The guide provides detailed information about Performance Insights data types, parameters and errors. When Performance Insights is enabled, the Amazon RDS Performance Insights API provides visibility into the performance of your DB instance. Amazon CloudWatch provides the authoritative source for AWS service-vended monitoring metrics. Performance Insights offers a domain-specific view of DB load. DB load is measured as Average Active Sessions. Performance Insights provides the data to API consumers as a two-dimensional time-series dataset. The time dimension provides DB load data for each time point in the queried time range. Each time point decomposes overall load in relation to the requested dimensions, measured at that time point. Examples include SQL, Wait event, User, and Host. To learn more about Performance Insights and Amazon Aurora DB instances, go to the Amazon Aurora User Guide. To learn more about Performance Insights and Amazon RDS DB instances, go to the Amazon RDS User Guide.

Amazon CodeGuru Reviewer

This section provides documentation for the Amazon CodeGuru Reviewer API operations. CodeGuru Reviewer is a service that uses program analysis and machine learning to detect potential defects that are difficult for developers to find and recommends fixes in your Java and Python code. By proactively detecting and providing recommendations for addressing code defects and implementing best practices, CodeGuru Reviewer improves the overall quality and maintainability of your code base during the code review stage. For more information about CodeGuru Reviewer, see the Amazon CodeGuru Reviewer User Guide. To improve the security of your CodeGuru Reviewer API calls, you can establish a private connection between your VPC and CodeGuru Reviewer by creating an interface VPC endpoint. For more information, see CodeGuru Reviewer and interface VPC endpoints (Amazon Web Services PrivateLink) in the Amazon CodeGuru Reviewer User Guide.

Auto Scaling

Amazon EC2 Auto Scaling Amazon EC2 Auto Scaling is designed to automatically launch or terminate EC2 instances based on user-defined scaling policies, scheduled actions, and health checks. For more information about Amazon EC2 Auto Scaling, see the Amazon EC2 Auto Scaling User Guide. For information about granting IAM users required permissions for calls to Amazon EC2 Auto Scaling, see Granting IAM users required permissions for Amazon EC2 Auto Scaling resources in the Amazon EC2 Auto Scaling API Reference.

Amazon Kinesis Video Streams

AWS Price List Service

Amazon Web Services Price List Service API (Amazon Web Services Price List Service) is a centralized and convenient way to programmatically query Amazon Web Services for services, products, and pricing information. The Amazon Web Services Price List Service uses standardized product attributes such as Location, Storage Class, and Operating System, and provides prices at the SKU level. You can use the Amazon Web Services Price List Service to build cost control and scenario planning tools, reconcile billing data, forecast future spend for budgeting purposes, and provide cost benefit analysis that compare your internal workloads with Amazon Web Services. Use GetServices without a service code to retrieve the service codes for all AWS services, then GetServices with a service code to retreive the attribute names for that service. After you have the service code and attribute names, you can use GetAttributeValues to see what values are available for an attribute. With the service code and an attribute name and value, you can use GetProducts to find specific products that you're interested in, such as an AmazonEC2 instance, with a Provisioned IOPS volumeType. Service Endpoint Amazon Web Services Price List Service API provides the following two endpoints: https://api.pricing.us-east-1.amazonaws.com https://api.pricing.ap-south-1.amazonaws.com

Other APIs in the same category

PostgreSQLManagementClient

azure.com
The Microsoft Azure management API provides create, read, update, and delete functionality for Azure PostgreSQL resources including servers, databases, firewall rules, VNET rules, security alert policies, log files and configurations with new business model.

Amazon Interactive Video Service

Introduction The Amazon Interactive Video Service (IVS) API is REST compatible, using a standard HTTP API and an AWS EventBridge event stream for responses. JSON is used for both requests and responses, including errors. The API is an AWS regional service, currently in these regions: us-west-2, us-east-1, and eu-west-1. All API request parameters and URLs are case sensitive. For a summary of notable documentation changes in each release, see Document History. Service Endpoints The following are the Amazon IVS service endpoints (all HTTPS): Region name: US West (Oregon) Region: us-west-2 Endpoint: ivs.us-west-2.amazonaws.com Region name: US East (Virginia) Region: us-east-1 Endpoint: ivs.us-east-1.amazonaws.com Region name: EU West (Dublin) Region: eu-west-1 Endpoint: ivs.eu-west-1.amazonaws.com Allowed Header Values Accept: application/json Accept-Encoding: gzip, deflate Content-Type: application/json Resources The following resources contain information about your IVS live stream (see Getting Started with Amazon IVS): Channel β€” Stores configuration data related to your live stream. You first create a channel and then use the channel’s stream key to start your live stream. See the Channel endpoints for more information. Stream key β€” An identifier assigned by Amazon IVS when you create a channel, which is then used to authorize streaming. See the StreamKey endpoints for more information. Treat the stream key like a secret, since it allows anyone to stream to the channel. Playback key pair β€” Video playback may be restricted using playback-authorization tokens, which use public-key encryption. A playback key pair is the public-private pair of keys used to sign and validate the playback-authorization token. See the PlaybackKeyPair endpoints for more information. Recording configuration β€” Stores configuration related to recording a live stream and where to store the recorded content. Multiple channels can reference the same recording configuration. See the Recording Configuration endpoints for more information. Tagging A tag is a metadata label that you assign to an AWS resource. A tag comprises a key and a value, both set by you. For example, you might set a tag as topic:nature to label a particular video category. See Tagging AWS Resources for more information, including restrictions that apply to tags. Tags can help you identify and organize your AWS resources. For example, you can use the same tag for different resources to indicate that they are related. You can also use tags to manage access (see Access Tags). The Amazon IVS API has these tag-related endpoints: TagResource, UntagResource, and ListTagsForResource. The following resources support tagging: Channels, Stream Keys, Playback Key Pairs, and Recording Configurations. Authentication versus Authorization Note the differences between these concepts: Authentication is about verifying identity. You need to be authenticated to sign Amazon IVS API requests. Authorization is about granting permissions. You need to be authorized to view Amazon IVS private channels. (Private channels are channels that are enabled for "playback authorization.") Authentication All Amazon IVS API requests must be authenticated with a signature. The AWS Command-Line Interface (CLI) and Amazon IVS Player SDKs take care of signing the underlying API calls for you. However, if your application calls the Amazon IVS API directly, it’s your responsibility to sign the requests. You generate a signature using valid AWS credentials that have permission to perform the requested action. For example, you must sign PutMetadata requests with a signature generated from an IAM user account that has the ivs:PutMetadata permission. For more information: Authentication and generating signatures β€” See Authenticating Requests (AWS Signature Version 4) in the AWS General Reference. Managing Amazon IVS permissions β€” See Identity and Access Management on the Security page of the Amazon IVS User Guide. Channel Endpoints CreateChannel β€” Creates a new channel and an associated stream key to start streaming. GetChannel β€” Gets the channel configuration for the specified channel ARN (Amazon Resource Name). BatchGetChannel β€” Performs GetChannel on multiple ARNs simultaneously. ListChannels β€” Gets summary information about all channels in your account, in the AWS region where the API request is processed. This list can be filtered to match a specified name or recording-configuration ARN. Filters are mutually exclusive and cannot be used together. If you try to use both filters, you will get an error (409 Conflict Exception). UpdateChannel β€” Updates a channel's configuration. This does not affect an ongoing stream of this channel. You must stop and restart the stream for the changes to take effect. DeleteChannel β€” Deletes the specified channel. StreamKey Endpoints CreateStreamKey β€” Creates a stream key, used to initiate a stream, for the specified channel ARN. GetStreamKey β€” Gets stream key information for the specified ARN. BatchGetStreamKey β€” Performs GetStreamKey on multiple ARNs simultaneously. ListStreamKeys β€” Gets summary information about stream keys for the specified channel. DeleteStreamKey β€” Deletes the stream key for the specified ARN, so it can no longer be used to stream. Stream Endpoints GetStream β€” Gets information about the active (live) stream on a specified channel. ListStreams β€” Gets summary information about live streams in your account, in the AWS region where the API request is processed. StopStream β€” Disconnects the incoming RTMPS stream for the specified channel. Can be used in conjunction with DeleteStreamKey to prevent further streaming to a channel. PutMetadata β€” Inserts metadata into the active stream of the specified channel. A maximum of 5 requests per second per channel is allowed, each with a maximum 1 KB payload. (If 5 TPS is not sufficient for your needs, we recommend batching your data into a single PutMetadata call.) PlaybackKeyPair Endpoints For more information, see Setting Up Private Channels in the Amazon IVS User Guide. ImportPlaybackKeyPair β€” Imports the public portion of a new key pair and returns its arn and fingerprint. The privateKey can then be used to generate viewer authorization tokens, to grant viewers access to private channels (channels enabled for playback authorization). GetPlaybackKeyPair β€” Gets a specified playback authorization key pair and returns the arn and fingerprint. The privateKey held by the caller can be used to generate viewer authorization tokens, to grant viewers access to private channels. ListPlaybackKeyPairs β€” Gets summary information about playback key pairs. DeletePlaybackKeyPair β€” Deletes a specified authorization key pair. This invalidates future viewer tokens generated using the key pair’s privateKey. RecordingConfiguration Endpoints CreateRecordingConfiguration β€” Creates a new recording configuration, used to enable recording to Amazon S3. GetRecordingConfiguration β€” Gets the recording-configuration metadata for the specified ARN. ListRecordingConfigurations β€” Gets summary information about all recording configurations in your account, in the AWS region where the API request is processed. DeleteRecordingConfiguration β€” Deletes the recording configuration for the specified ARN. AWS Tags Endpoints TagResource β€” Adds or updates tags for the AWS resource with the specified ARN. UntagResource β€” Removes tags from the resource with the specified ARN. ListTagsForResource β€” Gets information about AWS tags for the specified ARN.

AWS App Runner

AWS App Runner AWS App Runner is an application service that provides a fast, simple, and cost-effective way to go directly from an existing container image or source code to a running service in the AWS cloud in seconds. You don't need to learn new technologies, decide which compute service to use, or understand how to provision and configure AWS resources. App Runner connects directly to your container registry or source code repository. It provides an automatic delivery pipeline with fully managed operations, high performance, scalability, and security. For more information about App Runner, see the AWS App Runner Developer Guide. For release information, see the AWS App Runner Release Notes. To install the Software Development Kits (SDKs), Integrated Development Environment (IDE) Toolkits, and command line tools that you can use to access the API, see Tools for Amazon Web Services. Endpoints For a list of Region-specific endpoints that App Runner supports, see AWS App Runner endpoints and quotas in the AWS General Reference.

FabricAdminClient

azure.com
MAC address pool operation endpoints and objects.

Amazon Textract

Amazon Textract detects and analyzes text in documents and converts it into machine-readable text. This is the API reference documentation for Amazon Textract.

ApiManagementClient

azure.com
Use these REST APIs for performing operations on Tag entity in your Azure API Management deployment. Tags can be assigned to APIs, Operations and Products.

ApplicationInsightsManagementClient

azure.com
Azure Application Insights client for API keys of a component.

HDInsightManagementClient

azure.com
The HDInsight Management Client.

Management Groups

azure.com
The Azure Management Groups API enables consolidation of multiple subscriptions/resources into an organizational hierarchy and centrally manage access control, policies, alerting and reporting for those resources.

ComputeManagementClient

azure.com
The Compute Management Client.

ContainerRegistryManagementClient

azure.com

Anomaly Detector Client

azure.com
The Anomaly Detector API detects anomalies automatically in time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a time range without preparing time series in client side. Besides the above three functionalities, stateful model also provide group based detection and labeling service. By leveraging labeling service user can provide labels for each detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using anomaly detector service, business customers can discover incidents and establish a logic flow for root cause analysis.