Mock sample for your project: AWS Compute Optimizer API

The AWS Migration Hub API methods help to obtain server and application migration status and integrate your resource-specific migration tool by providing a programmatic interface to Migration Hub. Remember that you must set your AWS Migration Hub home region before you call any of these APIs, or a HomeRegionNotSetException error will be returned. Also, you must make the API calls while in your home region.

Amazon OpenSearch Configuration Service Use the Amazon OpenSearch configuration API to create, configure, and manage Amazon OpenSearch Service domains. For sample code that uses the configuration API, see the Amazon OpenSearch Service Developer Guide. The guide also contains sample code for sending signed HTTP requests to the OpenSearch APIs. The endpoint for configuration service requests is region-specific: es. region.amazonaws.com. For example, es.us-east-1.amazonaws.com. For a current list of supported regions and endpoints, see Regions and Endpoints.

Provides AWS Marketplace business intelligence data on-demand.

Amazon Lookout for Equipment is a machine learning service that uses advanced analytics to identify anomalies in machines from sensor data for use in predictive maintenance.

Amazon Managed Blockchain is a fully managed service for creating and managing blockchain networks using open-source frameworks. Blockchain allows you to build applications where multiple parties can securely and transparently run transactions and share data without the need for a trusted, central authority. Managed Blockchain supports the Hyperledger Fabric and Ethereum open-source frameworks. Because of fundamental differences between the frameworks, some API actions or data types may only apply in the context of one framework and not the other. For example, actions related to Hyperledger Fabric network members such as CreateMember and DeleteMember do not apply to Ethereum. The description for each action indicates the framework or frameworks to which it applies. Data types and properties that apply only in the context of a particular framework are similarly indicated.

You can use the Amazon Redshift Data API to run queries on Amazon Redshift tables. You can run SQL statements, which are committed if the statement succeeds. For more information about the Amazon Redshift Data API, see Using the Amazon Redshift Data API in the Amazon Redshift Cluster Management Guide.

With Fleet Hub for AWS IoT Device Management you can build stand-alone web applications for monitoring the health of your device fleets. Fleet Hub for AWS IoT Device Management is in public preview and is subject to change.

The operations for managing an Amazon MSK cluster.

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.

API for AWS Elemental MediaConnect

Amazon Lex provides both build and runtime endpoints. Each endpoint provides a set of operations (API). Your conversational bot uses the runtime API to understand user utterances (user input text or voice). For example, suppose a user says "I want pizza", your bot sends this input to Amazon Lex using the runtime API. Amazon Lex recognizes that the user request is for the OrderPizza intent (one of the intents defined in the bot). Then Amazon Lex engages in user conversation on behalf of the bot to elicit required information (slot values, such as pizza size and crust type), and then performs fulfillment activity (that you configured when you created the bot). You use the build-time API to create and manage your Amazon Lex bot. For a list of build-time operations, see the build-time API, .

A client for issuing REST requests to the Azure metrics service.

Amazon Cognito Federated Identities Amazon Cognito Federated Identities is a web service that delivers scoped temporary credentials to mobile devices and other untrusted environments. It uniquely identifies a device and supplies the user with a consistent identity over the lifetime of an application. Using Amazon Cognito Federated Identities, you can enable authentication with one or more third-party identity providers (Facebook, Google, or Login with Amazon) or an Amazon Cognito user pool, and you can also choose to support unauthenticated access from your app. Cognito delivers a unique identifier for each user and acts as an OpenID token provider trusted by AWS Security Token Service (STS) to access temporary, limited-privilege AWS credentials. For a description of the authentication flow from the Amazon Cognito Developer Guide see Authentication Flow. For more information see Amazon Cognito Federated Identities.

Amazon Managed Service for Prometheus

Azure Log Analytics API reference for Query Packs management.

For more information about AWS CloudHSM, see AWS CloudHSM and the AWS CloudHSM User Guide.

Elastic Load Balancing A load balancer can distribute incoming traffic across your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered instances and ensures that it routes traffic only to healthy instances. You configure your load balancer to accept incoming traffic by specifying one or more listeners, which are configured with a protocol and port number for connections from clients to the load balancer and a protocol and port number for connections from the load balancer to the instances. Elastic Load Balancing supports three types of load balancers: Application Load Balancers, Network Load Balancers, and Classic Load Balancers. You can select a load balancer based on your application needs. For more information, see the Elastic Load Balancing User Guide. This reference covers the 2012-06-01 API, which supports Classic Load Balancers. The 2015-12-01 API supports Application Load Balancers and Network Load Balancers. To get started, create a load balancer with one or more listeners using CreateLoadBalancer. Register your instances with the load balancer using RegisterInstancesWithLoadBalancer. All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds with a 200 OK response code.

Amazon DynamoDB Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB lets you offload the administrative burdens of operating and scaling a distributed database, so that you don't have to worry about hardware provisioning, setup and configuration, replication, software patching, or cluster scaling. With DynamoDB, you can create database tables that can store and retrieve any amount of data, and serve any level of request traffic. You can scale up or scale down your tables' throughput capacity without downtime or performance degradation, and use the AWS Management Console to monitor resource utilization and performance metrics. DynamoDB automatically spreads the data and traffic for your tables over a sufficient number of servers to handle your throughput and storage requirements, while maintaining consistent and fast performance. All of your data is stored on solid state disks (SSDs) and automatically replicated across multiple Availability Zones in an AWS region, providing built-in high availability and data durability.

AWS Fault Injection Simulator is a managed service that enables you to perform fault injection experiments on your AWS workloads. For more information, see the AWS Fault Injection Simulator User Guide.

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.

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.

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.