Mock sample for your project: Marketplace RP Service API

Azure Log Analytics API reference

The Azure Data Catalog Resource Provider Services API.

Azure Application Insights client for API keys of a component.

Azure Application Insights client for web test based alerting.

The Admin Gallery Management Client.

The service for managing third party addons.

The Admin Backup Management Client.

The Admin Subscriptions Management Client.

Azure Application Insights workbook template type.

Storage pool operation endpoints and objects.

The Admin Subscriptions Management Client.

REST API for Azure Logic Apps.

Use these REST APIs for performing operations on Identity Provider entity associated with your Azure API Management deployment. Setting up an external Identity Provider for authentication can help you manage the developer portal logins using the OAuth2 flow.

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.

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.

Glue DataBrew is a visual, cloud-scale data-preparation service. DataBrew simplifies data preparation tasks, targeting data issues that are hard to spot and time-consuming to fix. DataBrew empowers users of all technical levels to visualize the data and perform one-click data transformations, with no coding required.

AWS IoT Jobs is a service that allows you to define a set of jobs — remote operations that are sent to and executed on one or more devices connected to AWS IoT. For example, you can define a job that instructs a set of devices to download and install application or firmware updates, reboot, rotate certificates, or perform remote troubleshooting operations. To create a job, you make a job document which is a description of the remote operations to be performed, and you specify a list of targets that should perform the operations. The targets can be individual things, thing groups or both. AWS IoT Jobs sends a message to inform the targets that a job is available. The target starts the execution of the job by downloading the job document, performing the operations it specifies, and reporting its progress to AWS IoT. The Jobs service provides commands to track the progress of a job on a specific target and for all the targets of the job

The FinSpace APIs let you take actions inside the FinSpace environment.

AWS AppConfig Use AWS AppConfig, a capability of AWS Systems Manager, to create, manage, and quickly deploy application configurations. AppConfig supports controlled deployments to applications of any size and includes built-in validation checks and monitoring. You can use AppConfig with applications hosted on Amazon EC2 instances, AWS Lambda, containers, mobile applications, or IoT devices. To prevent errors when deploying application configurations, especially for production systems where a simple typo could cause an unexpected outage, AppConfig includes validators. A validator provides a syntactic or semantic check to ensure that the configuration you want to deploy works as intended. To validate your application configuration data, you provide a schema or a Lambda function that runs against the configuration. The configuration deployment or update can only proceed when the configuration data is valid. During a configuration deployment, AppConfig monitors the application to ensure that the deployment is successful. If the system encounters an error, AppConfig rolls back the change to minimize impact for your application users. You can configure a deployment strategy for each application or environment that includes deployment criteria, including velocity, bake time, and alarms to monitor. Similar to error monitoring, if a deployment triggers an alarm, AppConfig automatically rolls back to the previous version. AppConfig supports multiple use cases. Here are some examples. Application tuning : Use AppConfig to carefully introduce changes to your application that can only be tested with production traffic. Feature toggle : Use AppConfig to turn on new features that require a timely deployment, such as a product launch or announcement. Allow list : Use AppConfig to allow premium subscribers to access paid content. Operational issues : Use AppConfig to reduce stress on your application when a dependency or other external factor impacts the system. This reference is intended to be used with the AWS AppConfig User Guide.

AppSync provides API actions for creating and interacting with data sources using GraphQL from your application.

AWS CodeStar This is the API reference for AWS CodeStar. This reference provides descriptions of the operations and data types for the AWS CodeStar API along with usage examples. You can use the AWS CodeStar API to work with: Projects and their resources, by calling the following: DeleteProject, which deletes a project. DescribeProject, which lists the attributes of a project. ListProjects, which lists all projects associated with your AWS account. ListResources, which lists the resources associated with a project. ListTagsForProject, which lists the tags associated with a project. TagProject, which adds tags to a project. UntagProject, which removes tags from a project. UpdateProject, which updates the attributes of a project. Teams and team members, by calling the following: AssociateTeamMember, which adds an IAM user to the team for a project. DisassociateTeamMember, which removes an IAM user from the team for a project. ListTeamMembers, which lists all the IAM users in the team for a project, including their roles and attributes. UpdateTeamMember, which updates a team member's attributes in a project. Users, by calling the following: CreateUserProfile, which creates a user profile that contains data associated with the user across all projects. DeleteUserProfile, which deletes all user profile information across all projects. DescribeUserProfile, which describes the profile of a user. ListUserProfiles, which lists all user profiles. UpdateUserProfile, which updates the profile for a user.

AWS Data Exchange is a service that makes it easy for AWS customers to exchange data in the cloud. You can use the AWS Data Exchange APIs to create, update, manage, and access file-based data set in the AWS Cloud. As a subscriber, you can view and access the data sets that you have an entitlement to through a subscription. You can use the APIS to download or copy your entitled data sets to Amazon S3 for use across a variety of AWS analytics and machine learning services. As a provider, you can create and manage your data sets that you would like to publish to a product. Being able to package and provide your data sets into products requires a few steps to determine eligibility. For more information, visit the AWS Data Exchange User Guide. A data set is a collection of data that can be changed or updated over time. Data sets can be updated using revisions, which represent a new version or incremental change to a data set. A revision contains one or more assets. An asset in AWS Data Exchange is a piece of data that can be stored as an Amazon S3 object. The asset can be a structured data file, an image file, or some other data file. Jobs are asynchronous import or export operations used to create or copy assets.

You can use the Cost Explorer API to programmatically query your cost and usage data. You can query for aggregated data such as total monthly costs or total daily usage. You can also query for granular data. This might include the number of daily write operations for Amazon DynamoDB database tables in your production environment. Service Endpoint The Cost Explorer API provides the following endpoint: https://ce.us-east-1.amazonaws.com For information about the costs that are associated with the Cost Explorer API, see Amazon Web Services Cost Management Pricing.

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.