Mock sample for your project: Elastic Load Balancing API
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Elastic Load Balancing
Version: 2015-12-01
Start working with "Elastic Load Balancing API" right away by using this ready-to-use mock sample. API mocking can greatly speed up your application development by removing all the tedious tasks or issues: API key provisioning, account creation, unplanned downtime, etc.
It also helps reduce your dependency on third-party APIs and improves your integration tests' quality and reliability by accounting for random failures, slow response time, etc.
Description
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.
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AWS Batch
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.
AWS IoT Greengrass V2
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.
Amazon CodeGuru Reviewer
This section provides documentation for the Amazon CodeGuru Reviewer API operations. CodeGuru Reviewer is a service that uses program analysis and machine learning to detect potential defects that are difficult for developers to find and recommends fixes in your Java and Python code. By proactively detecting and providing recommendations for addressing code defects and implementing best practices, CodeGuru Reviewer improves the overall quality and maintainability of your code base during the code review stage. For more information about CodeGuru Reviewer, see the Amazon CodeGuru Reviewer User Guide. To improve the security of your CodeGuru Reviewer API calls, you can establish a private connection between your VPC and CodeGuru Reviewer by creating an interface VPC endpoint. For more information, see CodeGuru Reviewer and interface VPC endpoints (Amazon Web Services PrivateLink) in the Amazon CodeGuru Reviewer User Guide.
AWS Import/Export
AWS Import/Export Service AWS Import/Export accelerates transferring large amounts of data between the AWS cloud and portable storage devices that you mail to us. AWS Import/Export transfers data directly onto and off of your storage devices using Amazon's high-speed internal network and bypassing the Internet. For large data sets, AWS Import/Export is often faster than Internet transfer and more cost effective than upgrading your connectivity.
AWS Cloud9
Cloud9 Cloud9 is a collection of tools that you can use to code, build, run, test, debug, and release software in the cloud. For more information about Cloud9, see the Cloud9 User Guide. Cloud9 supports these operations: CreateEnvironmentEC2 : Creates an Cloud9 development environment, launches an Amazon EC2 instance, and then connects from the instance to the environment. CreateEnvironmentMembership : Adds an environment member to an environment. DeleteEnvironment : Deletes an environment. If an Amazon EC2 instance is connected to the environment, also terminates the instance. DeleteEnvironmentMembership : Deletes an environment member from an environment. DescribeEnvironmentMemberships : Gets information about environment members for an environment. DescribeEnvironments : Gets information about environments. DescribeEnvironmentStatus : Gets status information for an environment. ListEnvironments : Gets a list of environment identifiers. ListTagsForResource : Gets the tags for an environment. TagResource : Adds tags to an environment. UntagResource : Removes tags from an environment. UpdateEnvironment : Changes the settings of an existing environment. UpdateEnvironmentMembership : Changes the settings of an existing environment member for an environment.
AWS Audit Manager
Welcome to the Audit Manager API reference. This guide is for developers who need detailed information about the Audit Manager API operations, data types, and errors. Audit Manager is a service that provides automated evidence collection so that you can continuously audit your Amazon Web Services usage, and assess the effectiveness of your controls to better manage risk and simplify compliance. Audit Manager provides pre-built frameworks that structure and automate assessments for a given compliance standard. Frameworks include a pre-built collection of controls with descriptions and testing procedures, which are grouped according to the requirements of the specified compliance standard or regulation. You can also customize frameworks and controls to support internal audits with unique requirements. Use the following links to get started with the Audit Manager API: Actions : An alphabetical list of all Audit Manager API operations. Data types : An alphabetical list of all Audit Manager 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 Audit Manager, we recommend that you review the Audit Manager User Guide.
FinSpace User Environment Management service
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Application Auto Scaling
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AWS IoT Data Plane
IoT data IoT data enables secure, bi-directional communication between Internet-connected things (such as sensors, actuators, embedded devices, or smart appliances) and the Amazon Web Services cloud. It implements a broker for applications and things to publish messages over HTTP (Publish) and retrieve, update, and delete shadows. A shadow is a persistent representation of your things and their state in the Amazon Web Services cloud. Find the endpoint address for actions in IoT data by running this CLI command: aws iot describe-endpoint --endpoint-type iot:Data-ATS The service name used by Amazon Web ServicesSignature Version 4 to sign requests is: iotdevicegateway.
Amazon EC2 Container Registry
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.
AWS Service Catalog App Registry
Amazon Web Services Service Catalog AppRegistry enables organizations to understand the application context of their Amazon Web Services resources. AppRegistry provides a repository of your applications, their resources, and the application metadata that you use within your enterprise.
AWS Direct Connect
Direct Connect links your internal network to an Direct Connect location over a standard Ethernet fiber-optic cable. One end of the cable is connected to your router, the other to an Direct Connect router. With this connection in place, you can create virtual interfaces directly to the Cloud (for example, to Amazon EC2 and Amazon S3) and to Amazon VPC, bypassing Internet service providers in your network path. A connection provides access to all Regions except the China (Beijing) and (China) Ningxia Regions. Amazon Web Services resources in the China Regions can only be accessed through locations associated with those Regions.
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Transit Gateway Network Manager (Network Manager) enables you to create a global network, in which you can monitor your AWS and on-premises networks that are built around transit gateways. The Network Manager APIs are supported in the US West (Oregon) Region only. You must specify the us-west-2 Region in all requests made to Network Manager.
Amazon Honeycode
Amazon Honeycode is a fully managed service that allows you to quickly build mobile and web apps for teams—without programming. Build Honeycode apps for managing almost anything, like projects, customers, operations, approvals, resources, and even your team.
Amazon CloudWatch Application Insights
Amazon CloudWatch Application Insights Amazon CloudWatch Application Insights is a service that helps you detect common problems with your applications. It enables you to pinpoint the source of issues in your applications (built with technologies such as Microsoft IIS, .NET, and Microsoft SQL Server), by providing key insights into detected problems. After you onboard your application, CloudWatch Application Insights identifies, recommends, and sets up metrics and logs. It continuously analyzes and correlates your metrics and logs for unusual behavior to surface actionable problems with your application. For example, if your application is slow and unresponsive and leading to HTTP 500 errors in your Application Load Balancer (ALB), Application Insights informs you that a memory pressure problem with your SQL Server database is occurring. It bases this analysis on impactful metrics and log errors.
Amazon Kinesis Analytics
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 Mobile Analytics
Amazon Mobile Analytics is a service for collecting, visualizing, and understanding app usage data at scale.
Amazon Data Lifecycle Manager
Amazon Data Lifecycle Manager With Amazon Data Lifecycle Manager, you can manage the lifecycle of your Amazon Web Services resources. You create lifecycle policies, which are used to automate operations on the specified resources. Amazon DLM supports Amazon EBS volumes and snapshots. For information about using Amazon DLM with Amazon EBS, see Automating the Amazon EBS Snapshot Lifecycle in the Amazon EC2 User Guide.
Amazon ElastiCache
Amazon ElastiCache Amazon ElastiCache is a web service that makes it easier to set up, operate, and scale a distributed cache in the cloud. With ElastiCache, customers get all of the benefits of a high-performance, in-memory cache with less of the administrative burden involved in launching and managing a distributed cache. The service makes setup, scaling, and cluster failure handling much simpler than in a self-managed cache deployment. In addition, through integration with Amazon CloudWatch, customers get enhanced visibility into the key performance statistics associated with their cache and can receive alarms if a part of their cache runs hot.
AWS IoT Secure Tunneling
AWS IoT Secure Tunneling AWS IoT Secure Tunnling enables you to create remote connections to devices deployed in the field. For more information about how AWS IoT Secure Tunneling works, see AWS IoT Secure Tunneling.
Amazon DynamoDB
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.