Mock sample for your project: Amazon Elasticsearch Service API

This reference provides descriptions of the AWS Application Cost Profiler API. The AWS Application Cost Profiler API provides programmatic access to view, create, update, and delete application cost report definitions, as well as to import your usage data into the Application Cost Profiler service. For more information about using this service, see the AWS Application Cost Profiler User Guide.

Amazon EventBridge helps you to respond to state changes in your Amazon Web Services resources. When your resources change state, they automatically send events to an event stream. You can create rules that match selected events in the stream and route them to targets to take action. You can also use rules to take action on a predetermined schedule. For example, you can configure rules to: Automatically invoke an Lambda function to update DNS entries when an event notifies you that Amazon EC2 instance enters the running state. Direct specific API records from CloudTrail to an Amazon Kinesis data stream for detailed analysis of potential security or availability risks. Periodically invoke a built-in target to create a snapshot of an Amazon EBS volume. For more information about the features of Amazon EventBridge, see the Amazon EventBridge User Guide.

Amazon Route 53 is a highly available and scalable Domain Name System (DNS) web service.

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.

Amazon Elastic Container Registry Amazon Elastic Container Registry (Amazon ECR) is a managed container image registry service. Customers can use the familiar Docker CLI, or their preferred client, to push, pull, and manage images. Amazon ECR provides a secure, scalable, and reliable registry for your Docker or Open Container Initiative (OCI) images. Amazon ECR supports private repositories with resource-based permissions using IAM so that specific users or Amazon EC2 instances can access repositories and images. Amazon ECR has service endpoints in each supported Region. For more information, see Amazon ECR endpoints in the Amazon Web Services General Reference.

Amazon MQ is a managed message broker service for Apache ActiveMQ and RabbitMQ that makes it easy to set up and operate message brokers in the cloud. A message broker allows software applications and components to communicate using various programming languages, operating systems, and formal messaging protocols.

You can use Amazon CloudWatch Logs to monitor, store, and access your log files from EC2 instances, CloudTrail, and other sources. You can then retrieve the associated log data from CloudWatch Logs using the CloudWatch console, CloudWatch Logs commands in the Amazon Web Services CLI, CloudWatch Logs API, or CloudWatch Logs SDK. You can use CloudWatch Logs to: Monitor logs from EC2 instances in real-time : You can use CloudWatch Logs to monitor applications and systems using log data. For example, CloudWatch Logs can track the number of errors that occur in your application logs and send you a notification whenever the rate of errors exceeds a threshold that you specify. CloudWatch Logs uses your log data for monitoring so no code changes are required. For example, you can monitor application logs for specific literal terms (such as "NullReferenceException") or count the number of occurrences of a literal term at a particular position in log data (such as "404" status codes in an Apache access log). When the term you are searching for is found, CloudWatch Logs reports the data to a CloudWatch metric that you specify. Monitor CloudTrail logged events : You can create alarms in CloudWatch and receive notifications of particular API activity as captured by CloudTrail. You can use the notification to perform troubleshooting. Archive log data : You can use CloudWatch Logs to store your log data in highly durable storage. You can change the log retention setting so that any log events older than this setting are automatically deleted. The CloudWatch Logs agent makes it easy to quickly send both rotated and non-rotated log data off of a host and into the log service. You can then access the raw log data when you need it.

Contact Lens for Amazon Connect enables you to analyze conversations between customer and agents, by using speech transcription, natural language processing, and intelligent search capabilities. It performs sentiment analysis, detects issues, and enables you to automatically categorize contacts. Contact Lens for Amazon Connect provides both real-time and post-call analytics of customer-agent conversations. For more information, see Analyze conversations using Contact Lens in the Amazon Connect Administrator Guide.

Amazon Managed Workflows for Apache Airflow This section contains the Amazon Managed Workflows for Apache Airflow (MWAA) API reference documentation. For more information, see What Is Amazon MWAA?.

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.

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 Lake Formation Defines the public endpoint for the AWS Lake Formation service.

AWS Server Migration Service AWS Server Migration Service (AWS SMS) makes it easier and faster for you to migrate your on-premises workloads to AWS. To learn more about AWS SMS, see the following resources: AWS Server Migration Service product page AWS Server Migration Service User Guide

Use these REST APIs for performing operations on the ApiVersionSet entity associated with your Azure API Management deployment. Using this entity you create and manage API Version Sets that are used to group APIs for consistent versioning.

Elastic Load Balancing A load balancer distributes incoming traffic across targets, such as your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered targets and ensures that it routes traffic only to healthy targets. 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. You configure a target group with a protocol and port number for connections from the load balancer to the targets, and with health check settings to be used when checking the health status of the targets. Elastic Load Balancing supports the following types of load balancers: Application Load Balancers, Network Load Balancers, Gateway Load Balancers, and Classic Load Balancers. This reference covers the following load balancer types: Application Load Balancer - Operates at the application layer (layer 7) and supports HTTP and HTTPS. Network Load Balancer - Operates at the transport layer (layer 4) and supports TCP, TLS, and UDP. Gateway Load Balancer - Operates at the network layer (layer 3). For more information, see the Elastic Load Balancing User Guide. All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds.

PowerBI Dedicated Web API provides a RESTful set of web services that enables users to create, retrieve, update, and delete Power BI dedicated capacities

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.

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.

Personalizer Service is an Azure Cognitive Service that makes it easy to target content and experiences without complex pre-analysis or cleanup of past data. Given a context and featurized content, the Personalizer Service returns which content item to show to users in rewardActionId. As rewards are sent in response to the use of rewardActionId, the reinforcement learning algorithm will improve the model and improve performance of future rank calls.

Use these REST APIs for performing operations on Property entity associated with your Azure API Management deployment. API Management policies are a powerful capability of the system that allow the publisher to change the behavior of the API through configuration. Policies are a collection of statements that are executed sequentially on the request or response of an API. Policy statements can be constructed using literal text values, policy expressions, and properties. Each API Management service instance has a properties collection of key/value pairs that are global to the service instance. These properties can be used to manage constant string values across all API configuration and policies.

You use the API to scan your content as it is generated. Content Moderator then processes your content and sends the results along with relevant information either back to your systems or to the built-in review tool. You can use this information to take decisions e.g. take it down, send to human judge, etc.
When using the API, images need to have a minimum of 128 pixels and a maximum file size of 4MB.
Text can be at most 1024 characters long.
If the content passed to the text API or the image API exceeds the size limits, the API will return an error code that informs about the issue.

Welcome to the Amazon SQS API Reference. Amazon SQS is a reliable, highly-scalable hosted queue for storing messages as they travel between applications or microservices. Amazon SQS moves data between distributed application components and helps you decouple these components. For information on the permissions you need to use this API, see Identity and access management in the Amazon SQS Developer Guide. You can use Amazon Web Services SDKs to access Amazon SQS using your favorite programming language. The SDKs perform tasks such as the following automatically: Cryptographically sign your service requests Retry requests Handle error responses Additional information Amazon SQS Product Page Amazon SQS Developer Guide Making API Requests Amazon SQS Message Attributes Amazon SQS Dead-Letter Queues Amazon SQS in the Command Line Interface Amazon Web Services General Reference Regions and Endpoints