Mock sample for your project: Amazon Forecast Service API

Integrate with "Amazon Forecast Service API" from amazonaws.com in no time with Mockoon's ready to use mock sample

Amazon Forecast Service

amazonaws.com

Version: 2018-06-26


Use this API in your project

Integrate third-party APIs faster by using "Amazon Forecast Service API" ready-to-use mock sample. Mocking this API will allow you to start working in no time. No more accounts to create, API keys to provision, accesses to configure, unplanned downtime, just work.
Improve your integration tests by mocking third-party APIs and cover more edge cases: slow response time, random failures, etc.

Description

Provides APIs for creating and managing Amazon Forecast resources.

Other APIs by amazonaws.com

Amazon CloudHSM

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.

Amazon Route 53 Resolver

When you create a VPC using Amazon VPC, you automatically get DNS resolution within the VPC from Route 53 Resolver. By default, Resolver answers DNS queries for VPC domain names such as domain names for EC2 instances or Elastic Load Balancing load balancers. Resolver performs recursive lookups against public name servers for all other domain names. You can also configure DNS resolution between your VPC and your network over a Direct Connect or VPN connection: Forward DNS queries from resolvers on your network to Route 53 Resolver DNS resolvers on your network can forward DNS queries to Resolver in a specified VPC. This allows your DNS resolvers to easily resolve domain names for Amazon Web Services resources such as EC2 instances or records in a Route 53 private hosted zone. For more information, see How DNS Resolvers on Your Network Forward DNS Queries to Route 53 Resolver in the Amazon Route 53 Developer Guide. Conditionally forward queries from a VPC to resolvers on your network You can configure Resolver to forward queries that it receives from EC2 instances in your VPCs to DNS resolvers on your network. To forward selected queries, you create Resolver rules that specify the domain names for the DNS queries that you want to forward (such as example.com), and the IP addresses of the DNS resolvers on your network that you want to forward the queries to. If a query matches multiple rules (example.com, acme.example.com), Resolver chooses the rule with the most specific match (acme.example.com) and forwards the query to the IP addresses that you specified in that rule. For more information, see How Route 53 Resolver Forwards DNS Queries from Your VPCs to Your Network in the Amazon Route 53 Developer Guide. Like Amazon VPC, Resolver is Regional. In each Region where you have VPCs, you can choose whether to forward queries from your VPCs to your network (outbound queries), from your network to your VPCs (inbound queries), or both.

Amazon CloudWatch

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.

Amazon Elastic Inference

Elastic Inference public APIs.

Amazon Appflow

Welcome to the Amazon AppFlow API reference. This guide is for developers who need detailed information about the Amazon AppFlow API operations, data types, and errors. Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between software as a service (SaaS) applications like Salesforce, Marketo, Slack, and ServiceNow, and Amazon Web Services like Amazon S3 and Amazon Redshift. Use the following links to get started on the Amazon AppFlow API: Actions : An alphabetical list of all Amazon AppFlow API operations. Data types : An alphabetical list of all Amazon AppFlow data types. Common parameters : Parameters that all Query operations can use. Common errors : Client and server errors that all operations can return. If you're new to Amazon AppFlow, we recommend that you review the Amazon AppFlow User Guide. Amazon AppFlow API users can use vendor-specific mechanisms for OAuth, and include applicable OAuth attributes (such as auth-code and redirecturi) with the connector-specific ConnectorProfileProperties when creating a new connector profile using Amazon AppFlow API operations. For example, Salesforce users can refer to the Authorize Apps with OAuth documentation.

Amazon Prometheus Service

Amazon Managed Service for Prometheus

AWS Mobile

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.

AWS Amplify

Amplify enables developers to develop and deploy cloud-powered mobile and web apps. The Amplify Console provides a continuous delivery and hosting service for web applications. For more information, see the Amplify Console User Guide. The Amplify Framework is a comprehensive set of SDKs, libraries, tools, and documentation for client app development. For more information, see the Amplify Framework.

Managed Streaming for Kafka

The operations for managing an Amazon MSK cluster.

Amazon Kinesis Analytics

Amazon Kinesis Data Analytics is a fully managed service that you can use to process and analyze streaming data using Java, SQL, or Scala. The service enables you to quickly author and run Java, SQL, or Scala code against streaming sources to perform time series analytics, feed real-time dashboards, and create real-time metrics.

AWS Resource Groups

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

Amazon Neptune

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.

Other APIs in the same category

AzureBridgeAdminClient

azure.com
AzureBridge Admin Client.

SqlManagementClient

azure.com
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.

RedisManagementClient

azure.com
REST API for Azure Redis Cache Service.

Azure SQL Database disaster recovery configurations

azure.com
Provides create, read, update, delete, and failover functionality for Azure SQL Database disaster recovery configurations.

Security Center

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

FeatureClient

azure.com
Azure Feature Exposure Control (AFEC) provides a mechanism for the resource providers to control feature exposure to users. Resource providers typically use this mechanism to provide public/private preview for new features prior to making them generally available. Users need to explicitly register for AFEC features to get access to such functionality.

SqlManagementClient

azure.com
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.

SqlManagementClient

azure.com
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.

Security Center

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

SiteRecoveryManagementClient

azure.com

Security Center

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

Relay

azure.com
Use these API to manage Azure Relay resources through Azure Resource Manager.