Mock sample for your project: AWS Cloud Map API

Amazon Macie Classic Amazon Macie Classic is a security service that uses machine learning to automatically discover, classify, and protect sensitive data in AWS. Macie Classic recognizes sensitive data such as personally identifiable information (PII) or intellectual property, and provides you with dashboards and alerts that give visibility into how this data is being accessed or moved. For more information, see the Amazon Macie Classic User Guide.

Amazon DevOps Guru is a fully managed service that helps you identify anomalous behavior in business critical operational applications. You specify the AWS resources that you want DevOps Guru to cover, then the Amazon CloudWatch metrics and AWS CloudTrail events related to those resources are analyzed. When anomalous behavior is detected, DevOps Guru creates an insight that includes recommendations, related events, and related metrics that can help you improve your operational applications. For more information, see What is Amazon DevOps Guru. You can specify 1 or 2 Amazon Simple Notification Service topics so you are notified every time a new insight is created. You can also enable DevOps Guru to generate an OpsItem in AWS Systems Manager for each insight to help you manage and track your work addressing insights. To learn about the DevOps Guru workflow, see How DevOps Guru works. To learn about DevOps Guru concepts, see Concepts in DevOps Guru.

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.

The Amazon Braket API Reference provides information about the operations and structures supported in Amazon Braket.

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.

Amazon Managed Service for Prometheus

The AWS IoT 1-Click Projects API Reference

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 SageMaker endpoint variants Spot Fleet (Amazon EC2) requests Custom resources provided by your own applications or services 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 RegisterScalableTarget 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. To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.

AWS CloudHSM Service This is documentation for AWS CloudHSM Classic. For more information, see AWS CloudHSM Classic FAQs, the AWS CloudHSM Classic User Guide, and the AWS CloudHSM Classic API Reference. For information about the current version of AWS CloudHSM, see AWS CloudHSM, the AWS CloudHSM User Guide, and the AWS CloudHSM API Reference.

Storage Gateway Service Storage Gateway is the service that connects an on-premises software appliance with cloud-based storage to provide seamless and secure integration between an organization's on-premises IT environment and the Amazon Web Services storage infrastructure. The service enables you to securely upload data to the Cloud for cost effective backup and rapid disaster recovery. Use the following links to get started using the Storage Gateway Service API Reference : Storage Gateway required request headers : Describes the required headers that you must send with every POST request to Storage Gateway. Signing requests : Storage Gateway requires that you authenticate every request you send; this topic describes how sign such a request. Error responses : Provides reference information about Storage Gateway errors. Operations in Storage Gateway : Contains detailed descriptions of all Storage Gateway operations, their request parameters, response elements, possible errors, and examples of requests and responses. Storage Gateway endpoints and quotas : Provides a list of each Region and the endpoints available for use with Storage Gateway. Storage Gateway resource IDs are in uppercase. When you use these resource IDs with the Amazon EC2 API, EC2 expects resource IDs in lowercase. You must change your resource ID to lowercase to use it with the EC2 API. For example, in Storage Gateway the ID for a volume might be vol-AA22BB012345DAF670. When you use this ID with the EC2 API, you must change it to vol-aa22bb012345daf670. Otherwise, the EC2 API might not behave as expected. IDs for Storage Gateway volumes and Amazon EBS snapshots created from gateway volumes are changing to a longer format. Starting in December 2016, all new volumes and snapshots will be created with a 17-character string. Starting in April 2016, you will be able to use these longer IDs so you can test your systems with the new format. For more information, see Longer EC2 and EBS resource IDs. For example, a volume Amazon Resource Name (ARN) with the longer volume ID format looks like the following: arn:aws:storagegateway:us-west-2:111122223333:gateway/sgw-12A3456B/volume/vol-1122AABBCCDDEEFFG. A snapshot ID with the longer ID format looks like the following: snap-78e226633445566ee. For more information, see Announcement: Heads-up – Longer Storage Gateway volume and snapshot IDs coming in 2016.

AWS Resource Groups AWS Resource Groups lets you organize AWS resources such as Amazon EC2 instances, Amazon Relational Database Service databases, and Amazon S3 buckets into groups using criteria that you define as tags. A resource group is a collection of resources that match the resource types specified in a query, and share one or more tags or portions of tags. You can create a group of resources based on their roles in your cloud infrastructure, lifecycle stages, regions, application layers, or virtually any criteria. Resource Groups enable you to automate management tasks, such as those in AWS Systems Manager Automation documents, on tag-related resources in AWS Systems Manager. Groups of tagged resources also let you quickly view a custom console in AWS Systems Manager that shows AWS Config compliance and other monitoring data about member resources. To create a resource group, build a resource query, and specify tags that identify the criteria that members of the group have in common. Tags are key-value pairs. For more information about Resource Groups, see the AWS Resource Groups User Guide. AWS Resource Groups uses a REST-compliant API that you can use to perform the following types of operations. Create, Read, Update, and Delete (CRUD) operations on resource groups and resource query entities Applying, editing, and removing tags from resource groups Resolving resource group member ARNs so they can be returned as search results Getting data about resources that are members of a group Searching AWS resources based on a resource query

AWS Elemental MediaPackage

Backup Backup is a unified backup service designed to protect Amazon Web Services services and their associated data. Backup simplifies the creation, migration, restoration, and deletion of backups, while also providing reporting and auditing.

Logical network operation endpoints and objects.

The User Subscription Management Client.

AzureBridge Admin Client.

The HDInsight Management Client.

API spec for Microsoft.Security (Azure Security Center) resource provider

The Anomaly Finder API detects anomalies automatically in time series data. It supports two functionalities, one is for detecting the whole series with model trained by the timeseries, another is detecting last point with model trained by points before. By using this service, business customers can discover incidents and establish a logic flow for root cause analysis.

Microsoft NetApp Azure Resource Provider specification

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.