Mock sample for your project: AWS Marketplace Commerce Analytics API

Shield Advanced This is the Shield Advanced API Reference. This guide is for developers who need detailed information about the Shield Advanced API actions, data types, and errors. For detailed information about WAF and Shield Advanced features and an overview of how to use the WAF and Shield Advanced APIs, see the WAF and Shield Developer Guide.

DAX is a managed caching service engineered for Amazon DynamoDB. DAX dramatically speeds up database reads by caching frequently-accessed data from DynamoDB, so applications can access that data with sub-millisecond latency. You can create a DAX cluster easily, using the AWS Management Console. With a few simple modifications to your code, your application can begin taking advantage of the DAX cluster and realize significant improvements in read performance.

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.

Amazon Connect is a cloud-based contact center solution that makes it easy to set up and manage a customer contact center and provide reliable customer engagement at any scale. Amazon Connect enables customer contacts through voice or chat. The APIs described here are used by chat participants, such as agents and customers.

Glue Defines the public endpoint for the Glue service.

Batch Using Batch, you can run batch computing workloads on the Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. Batch uses the advantages of this computing workload to remove the undifferentiated heavy lifting of configuring and managing required infrastructure. At the same time, it also adopts a familiar batch computing software approach. Given these advantages, Batch can help you to efficiently provision resources in response to jobs submitted, thus effectively helping you to eliminate capacity constraints, reduce compute costs, and deliver your results more quickly. As a fully managed service, Batch can run batch computing workloads of any scale. Batch automatically provisions compute resources and optimizes workload distribution based on the quantity and scale of your specific workloads. With Batch, there's no need to install or manage batch computing software. This means that you can focus your time and energy on analyzing results and solving your specific problems.

Amazon Cognito Sync Amazon Cognito Sync provides an AWS service and client library that enable cross-device syncing of application-related user data. High-level client libraries are available for both iOS and Android. You can use these libraries to persist data locally so that it's available even if the device is offline. Developer credentials don't need to be stored on the mobile device to access the service. You can use Amazon Cognito to obtain a normalized user ID and credentials. User data is persisted in a dataset that can store up to 1 MB of key-value pairs, and you can have up to 20 datasets per user identity. With Amazon Cognito Sync, the data stored for each identity is accessible only to credentials assigned to that identity. In order to use the Cognito Sync service, you need to make API calls using credentials retrieved with Amazon Cognito Identity service. If you want to use Cognito Sync in an Android or iOS application, you will probably want to make API calls via the AWS Mobile SDK. To learn more, see the Developer Guide for Android and the Developer Guide for iOS.

CodeBuild CodeBuild is a fully managed build service in the cloud. CodeBuild compiles your source code, runs unit tests, and produces artifacts that are ready to deploy. CodeBuild eliminates the need to provision, manage, and scale your own build servers. It provides prepackaged build environments for the most popular programming languages and build tools, such as Apache Maven, Gradle, and more. You can also fully customize build environments in CodeBuild to use your own build tools. CodeBuild scales automatically to meet peak build requests. You pay only for the build time you consume. For more information about CodeBuild, see the CodeBuild User Guide.

Amazon API Gateway Amazon API Gateway helps developers deliver robust, secure, and scalable mobile and web application back ends. API Gateway allows developers to securely connect mobile and web applications to APIs that run on AWS Lambda, Amazon EC2, or other publicly addressable web services that are hosted outside of AWS.

AWS CodeArtifact is a fully managed artifact repository compatible with language-native package managers and build tools such as npm, Apache Maven, and pip. You can use CodeArtifact to share packages with development teams and pull packages. Packages can be pulled from both public and CodeArtifact repositories. You can also create an upstream relationship between a CodeArtifact repository and another repository, which effectively merges their contents from the point of view of a package manager client. AWS CodeArtifact Components Use the information in this guide to help you work with the following CodeArtifact components: Repository : A CodeArtifact repository contains a set of package versions, each of which maps to a set of assets, or files. Repositories are polyglot, so a single repository can contain packages of any supported type. Each repository exposes endpoints for fetching and publishing packages using tools like the npm CLI, the Maven CLI ( mvn ), and pip . Domain : Repositories are aggregated into a higher-level entity known as a domain. All package assets and metadata are stored in the domain, but are consumed through repositories. A given package asset, such as a Maven JAR file, is stored once per domain, no matter how many repositories it's present in. All of the assets and metadata in a domain are encrypted with the same customer master key (CMK) stored in AWS Key Management Service (AWS KMS). Each repository is a member of a single domain and can't be moved to a different domain. The domain allows organizational policy to be applied across multiple repositories, such as which accounts can access repositories in the domain, and which public repositories can be used as sources of packages. Although an organization can have multiple domains, we recommend a single production domain that contains all published artifacts so that teams can find and share packages across their organization. Package : A package is a bundle of software and the metadata required to resolve dependencies and install the software. CodeArtifact supports npm, PyPI, and Maven package formats. In CodeArtifact, a package consists of: A name (for example, webpack is the name of a popular npm package) An optional namespace (for example, @types in @types/node) A set of versions (for example, 1.0.0, 1.0.1, 1.0.2, etc.) Package-level metadata (for example, npm tags) Package version : A version of a package, such as @types/node 12.6.9. The version number format and semantics vary for different package formats. For example, npm package versions must conform to the Semantic Versioning specification. In CodeArtifact, a package version consists of the version identifier, metadata at the package version level, and a set of assets. Upstream repository : One repository is upstream of another when the package versions in it can be accessed from the repository endpoint of the downstream repository, effectively merging the contents of the two repositories from the point of view of a client. CodeArtifact allows creating an upstream relationship between two repositories. Asset : An individual file stored in CodeArtifact associated with a package version, such as an npm.tgz file or Maven POM and JAR files. CodeArtifact supports these operations: AssociateExternalConnection : Adds an existing external connection to a repository. CopyPackageVersions : Copies package versions from one repository to another repository in the same domain. CreateDomain : Creates a domain CreateRepository : Creates a CodeArtifact repository in a domain. DeleteDomain : Deletes a domain. You cannot delete a domain that contains repositories. DeleteDomainPermissionsPolicy : Deletes the resource policy that is set on a domain. DeletePackageVersions : Deletes versions of a package. After a package has been deleted, it can be republished, but its assets and metadata cannot be restored because they have been permanently removed from storage. DeleteRepository : Deletes a repository. DeleteRepositoryPermissionsPolicy : Deletes the resource policy that is set on a repository. DescribeDomain : Returns a DomainDescription object that contains information about the requested domain. DescribePackageVersion : Returns a PackageVersionDescription object that contains details about a package version. DescribeRepository : Returns a RepositoryDescription object that contains detailed information about the requested repository. DisposePackageVersions : Disposes versions of a package. A package version with the status Disposed cannot be restored because they have been permanently removed from storage. DisassociateExternalConnection : Removes an existing external connection from a repository. GetAuthorizationToken : Generates a temporary authorization token for accessing repositories in the domain. The token expires the authorization period has passed. The default authorization period is 12 hours and can be customized to any length with a maximum of 12 hours. GetDomainPermissionsPolicy : Returns the policy of a resource that is attached to the specified domain. GetPackageVersionAsset : Returns the contents of an asset that is in a package version. GetPackageVersionReadme : Gets the readme file or descriptive text for a package version. GetRepositoryEndpoint : Returns the endpoint of a repository for a specific package format. A repository has one endpoint for each package format: npm pypi maven GetRepositoryPermissionsPolicy : Returns the resource policy that is set on a repository. ListDomains : Returns a list of DomainSummary objects. Each returned DomainSummary object contains information about a domain. ListPackages : Lists the packages in a repository. ListPackageVersionAssets : Lists the assets for a given package version. ListPackageVersionDependencies : Returns a list of the direct dependencies for a package version. ListPackageVersions : Returns a list of package versions for a specified package in a repository. ListRepositories : Returns a list of repositories owned by the AWS account that called this method. ListRepositoriesInDomain : Returns a list of the repositories in a domain. PutDomainPermissionsPolicy : Attaches a resource policy to a domain. PutRepositoryPermissionsPolicy : Sets the resource policy on a repository that specifies permissions to access it. UpdatePackageVersionsStatus : Updates the status of one or more versions of a package. UpdateRepository : Updates the properties of a repository.

DataSync DataSync is a managed data transfer service that makes it simpler for you to automate moving data between on-premises storage and Amazon Simple Storage Service (Amazon S3) or Amazon Elastic File System (Amazon EFS). This API interface reference for DataSync contains documentation for a programming interface that you can use to manage DataSync.

Compute Optimizer is a service that analyzes the configuration and utilization metrics of your Amazon Web Services compute resources, such as Amazon EC2 instances, Amazon EC2 Auto Scaling groups, Lambda functions, and Amazon EBS volumes. It reports whether your resources are optimal, and generates optimization recommendations to reduce the cost and improve the performance of your workloads. Compute Optimizer also provides recent utilization metric data, in addition to projected utilization metric data for the recommendations, which you can use to evaluate which recommendation provides the best price-performance trade-off. The analysis of your usage patterns can help you decide when to move or resize your running resources, and still meet your performance and capacity requirements. For more information about Compute Optimizer, including the required permissions to use the service, see the Compute Optimizer User Guide.

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.

Azure Application Insights client for web test based alerting.

The Compute Management Client.

REST API for Azure Logic Apps.

These APIs allow end users to operate on Azure Machine Learning Team Account resources. They support CRUD operations for Azure Machine Learning Team Accounts.

Azure Cosmos DB Database Service Resource Provider REST API

The Hybrid Compute Management Client.

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

IoT data IoT data enables secure, bi-directional communication between Internet-connected things (such as sensors, actuators, embedded devices, or smart appliances) and the Amazon Web Services cloud. It implements a broker for applications and things to publish messages over HTTP (Publish) and retrieve, update, and delete shadows. A shadow is a persistent representation of your things and their state in the Amazon Web Services cloud. Find the endpoint address for actions in IoT data by running this CLI command: aws iot describe-endpoint --endpoint-type iot:Data-ATS The service name used by Amazon Web ServicesSignature Version 4 to sign requests is: iotdevicegateway.

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.