Mock sample for your project: Application Auto Scaling API

Amazon Textract detects and analyzes text in documents and converts it into machine-readable text. This is the API reference documentation for Amazon Textract.

Amazon Neptune Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. This interface reference for Amazon Neptune contains documentation for a programming or command line interface you can use to manage Amazon Neptune. Note that Amazon Neptune is asynchronous, which means that some interfaces might require techniques such as polling or callback functions to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a command is applied immediately, on the next instance reboot, or during the maintenance window. The reference structure is as follows, and we list following some related topics from the user guide.

This is the Amazon Lookout for Metrics API Reference. For an introduction to the service with tutorials for getting started, visit Amazon Lookout for Metrics Developer Guide.

Amazon Kinesis Analytics Overview This documentation is for version 1 of the Amazon Kinesis Data Analytics API, which only supports SQL applications. Version 2 of the API supports SQL and Java applications. For more information about version 2, see Amazon Kinesis Data Analytics API V2 Documentation. This is the Amazon Kinesis Analytics v1 API Reference. The Amazon Kinesis Analytics Developer Guide provides additional information.

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.

AWS Mobile Service provides mobile app and website developers with capabilities required to configure AWS resources and bootstrap their developer desktop projects with the necessary SDKs, constants, tools and samples to make use of those resources.

Resource Groups Tagging API

WAF This is the latest version of the WAF API, released in November, 2019. The names of the entities that you use to access this API, like endpoints and namespaces, all have the versioning information added, like "V2" or "v2", to distinguish from the prior version. We recommend migrating your resources to this version, because it has a number of significant improvements. If you used WAF prior to this release, you can't use this WAFV2 API to access any WAF resources that you created before. You can access your old rules, web ACLs, and other WAF resources only through the WAF Classic APIs. The WAF Classic APIs have retained the prior names, endpoints, and namespaces. For information, including how to migrate your WAF resources to this version, see the WAF Developer Guide. WAF is a web application firewall that lets you monitor the HTTP and HTTPS requests that are forwarded to Amazon CloudFront, an Amazon API Gateway REST API, an Application Load Balancer, or an AppSync GraphQL API. WAF also lets you control access to your content. Based on conditions that you specify, such as the IP addresses that requests originate from or the values of query strings, the Amazon API Gateway REST API, CloudFront distribution, the Application Load Balancer, or the AppSync GraphQL API responds to requests either with the requested content or with an HTTP 403 status code (Forbidden). You also can configure CloudFront to return a custom error page when a request is blocked. This API guide is for developers who need detailed information about WAF API actions, data types, and errors. For detailed information about WAF features and an overview of how to use WAF, see the WAF Developer Guide. You can make calls using the endpoints listed in WAF endpoints and quotas. For regional applications, you can use any of the endpoints in the list. A regional application can be an Application Load Balancer (ALB), an Amazon API Gateway REST API, or an AppSync GraphQL API. For Amazon CloudFront applications, you must use the API endpoint listed for US East (N. Virginia): us-east-1. Alternatively, you can use one of the Amazon Web Services SDKs to access an API that's tailored to the programming language or platform that you're using. For more information, see Amazon Web Services SDKs. We currently provide two versions of the WAF API: this API and the prior versions, the classic WAF APIs. This new API provides the same functionality as the older versions, with the following major improvements: You use one API for both global and regional applications. Where you need to distinguish the scope, you specify a Scope parameter and set it to CLOUDFRONT or REGIONAL. You can define a web ACL or rule group with a single call, and update it with a single call. You define all rule specifications in JSON format, and pass them to your rule group or web ACL calls. The limits WAF places on the use of rules more closely reflects the cost of running each type of rule. Rule groups include capacity settings, so you know the maximum cost of a rule group when you use it.

The transactional data APIs for Amazon QLDB Instead of interacting directly with this API, we recommend using the QLDB driver or the QLDB shell to execute data transactions on a ledger. If you are working with an AWS SDK, use the QLDB driver. The driver provides a high-level abstraction layer above this QLDB Session data plane and manages SendCommand API calls for you. For information and a list of supported programming languages, see Getting started with the driver in the Amazon QLDB Developer Guide. If you are working with the AWS Command Line Interface (AWS CLI), use the QLDB shell. The shell is a command line interface that uses the QLDB driver to interact with a ledger. For information, see Accessing Amazon QLDB using the QLDB shell.

Amazon Timestream is a fast, scalable, fully managed time series database service that makes it easy to store and analyze trillions of time series data points per day. With Timestream, you can easily store and analyze IoT sensor data to derive insights from your IoT applications. You can analyze industrial telemetry to streamline equipment management and maintenance. You can also store and analyze log data and metrics to improve the performance and availability of your applications. Timestream is built from the ground up to effectively ingest, process, and store time series data. It organizes data to optimize query processing. It automatically scales based on the volume of data ingested and on the query volume to ensure you receive optimal performance while inserting and querying data. As your data grows over time, Timestream’s adaptive query processing engine spans across storage tiers to provide fast analysis while reducing costs.

Amazon CloudWatch Synthetics You can use Amazon CloudWatch Synthetics to continually monitor your services. You can create and manage canaries, which are modular, lightweight scripts that monitor your endpoints and APIs from the outside-in. You can set up your canaries to run 24 hours a day, once per minute. The canaries help you check the availability and latency of your web services and troubleshoot anomalies by investigating load time data, screenshots of the UI, logs, and metrics. The canaries seamlessly integrate with CloudWatch ServiceLens to help you trace the causes of impacted nodes in your applications. For more information, see Using ServiceLens to Monitor the Health of Your Applications in the Amazon CloudWatch User Guide. Before you create and manage canaries, be aware of the security considerations. For more information, see Security Considerations for Synthetics Canaries.

Use these REST APIs for performing operations on Cache entity in your Azure API Management deployment. Azure API Management also allows for caching responses in an external Azure Cache for Redis. For more information refer to External Redis Cache in ApiManagement.

Azure Resource Graph Query API Reference

Specification for ManagedServices.

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MariaDB resources including servers, databases, firewall rules, VNET rules, security alert policies, log files and configurations with new business model.

The Container Service Client.

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MariaDB resources including servers, databases, firewall rules, VNET rules, log files and configurations with new business model.

This Swagger was generated by the API Framework.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

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

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