Mock sample for your project: AWS Device Farm API

Integrate with "AWS Device Farm API" from amazonaws.com in no time with Mockoon's ready to use mock sample

AWS Device Farm

amazonaws.com

Version: 2015-06-23


Use this API in your project

Integrate third-party APIs faster by using "AWS Device Farm 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

Welcome to the AWS Device Farm API documentation, which contains APIs for: Testing on desktop browsers Device Farm makes it possible for you to test your web applications on desktop browsers using Selenium. The APIs for desktop browser testing contain TestGrid in their names. For more information, see Testing Web Applications on Selenium with Device Farm. Testing on real mobile devices Device Farm makes it possible for you to test apps on physical phones, tablets, and other devices in the cloud. For more information, see the Device Farm Developer Guide.

Other APIs by amazonaws.com

Amazon Textract

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

AWS Cost Explorer Service

You can use the Cost Explorer API to programmatically query your cost and usage data. You can query for aggregated data such as total monthly costs or total daily usage. You can also query for granular data. This might include the number of daily write operations for Amazon DynamoDB database tables in your production environment. Service Endpoint The Cost Explorer API provides the following endpoint: https://ce.us-east-1.amazonaws.com For information about the costs that are associated with the Cost Explorer API, see Amazon Web Services Cost Management Pricing.

Amazon EMR

Amazon EMR is a web service that makes it easier to process large amounts of data efficiently. Amazon EMR uses Hadoop processing combined with several Amazon Web Services services to do tasks such as web indexing, data mining, log file analysis, machine learning, scientific simulation, and data warehouse management.

AmazonApiGatewayManagementApi

The Amazon API Gateway Management API allows you to directly manage runtime aspects of your deployed APIs. To use it, you must explicitly set the SDK's endpoint to point to the endpoint of your deployed API. The endpoint will be of the form https://{api-id}.execute-api.{region}.amazonaws.com/{stage}, or will be the endpoint corresponding to your API's custom domain and base path, if applicable.

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 CodeGuru Profiler

This section provides documentation for the Amazon CodeGuru Profiler API operations. Amazon CodeGuru Profiler collects runtime performance data from your live applications, and provides recommendations that can help you fine-tune your application performance. Using machine learning algorithms, CodeGuru Profiler can help you find your most expensive lines of code and suggest ways you can improve efficiency and remove CPU bottlenecks. Amazon CodeGuru Profiler provides different visualizations of profiling data to help you identify what code is running on the CPU, see how much time is consumed, and suggest ways to reduce CPU utilization. Amazon CodeGuru Profiler currently supports applications written in all Java virtual machine (JVM) languages and Python. While CodeGuru Profiler supports both visualizations and recommendations for applications written in Java, it can also generate visualizations and a subset of recommendations for applications written in other JVM languages and Python. For more information, see What is Amazon CodeGuru Profiler in the Amazon CodeGuru Profiler User Guide.

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.

Application Auto Scaling

With Application Auto Scaling, you can configure automatic scaling for the following resources: Amazon AppStream 2.0 fleets Amazon Aurora Replicas Amazon Comprehend document classification and entity recognizer endpoints Amazon DynamoDB tables and global secondary indexes throughput capacity Amazon ECS services Amazon ElastiCache for Redis clusters (replication groups) Amazon EMR clusters Amazon Keyspaces (for Apache Cassandra) tables Lambda function provisioned concurrency Amazon Managed Streaming for Apache Kafka broker storage Amazon SageMaker endpoint variants Spot Fleet (Amazon EC2) requests Custom resources provided by your own applications or services API Summary The Application Auto Scaling service API includes three key sets of actions: Register and manage scalable targets - Register Amazon Web Services or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets. Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history. Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the RegisterScalableTarget API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling. To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.

AmplifyBackend

AWS Amplify Admin API

Amazon API Gateway

Amazon API Gateway Amazon API Gateway helps developers deliver robust, secure, and scalable mobile and web application back ends. API Gateway allows developers to securely connect mobile and web applications to APIs that run on AWS Lambda, Amazon EC2, or other publicly addressable web services that are hosted outside of AWS.
The Amazon Braket API Reference provides information about the operations and structures supported in Amazon Braket.

AWS Application Cost Profiler

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.

Other APIs in the same category

AWS Network Firewall

This is the API Reference for AWS Network Firewall. This guide is for developers who need detailed information about the Network Firewall API actions, data types, and errors. The REST API requires you to handle connection details, such as calculating signatures, handling request retries, and error handling. For general information about using the AWS REST APIs, see AWS APIs. To access Network Firewall using the REST API endpoint: https://network-firewall..amazonaws.com Alternatively, you can use one of the AWS SDKs to access an API that's tailored to the programming language or platform that you're using. For more information, see AWS SDKs. For descriptions of Network Firewall features, including and step-by-step instructions on how to use them through the Network Firewall console, see the Network Firewall Developer Guide. Network Firewall is a stateful, managed, network firewall and intrusion detection and prevention service for Amazon Virtual Private Cloud (Amazon VPC). With Network Firewall, you can filter traffic at the perimeter of your VPC. This includes filtering traffic going to and coming from an internet gateway, NAT gateway, or over VPN or AWS Direct Connect. Network Firewall uses rules that are compatible with Suricata, a free, open source intrusion detection system (IDS) engine. For information about Suricata, see the Suricata website. You can use Network Firewall to monitor and protect your VPC traffic in a number of ways. The following are just a few examples: Allow domains or IP addresses for known AWS service endpoints, such as Amazon S3, and block all other forms of traffic. Use custom lists of known bad domains to limit the types of domain names that your applications can access. Perform deep packet inspection on traffic entering or leaving your VPC. Use stateful protocol detection to filter protocols like HTTPS, regardless of the port used. To enable Network Firewall for your VPCs, you perform steps in both Amazon VPC and in Network Firewall. For information about using Amazon VPC, see Amazon VPC User Guide. To start using Network Firewall, do the following: (Optional) If you don't already have a VPC that you want to protect, create it in Amazon VPC. In Amazon VPC, in each Availability Zone where you want to have a firewall endpoint, create a subnet for the sole use of Network Firewall. In Network Firewall, create stateless and stateful rule groups, to define the components of the network traffic filtering behavior that you want your firewall to have. In Network Firewall, create a firewall policy that uses your rule groups and specifies additional default traffic filtering behavior. In Network Firewall, create a firewall and specify your new firewall policy and VPC subnets. Network Firewall creates a firewall endpoint in each subnet that you specify, with the behavior that's defined in the firewall policy. In Amazon VPC, use ingress routing enhancements to route traffic through the new firewall endpoints.

ServiceFabricManagementClient

azure.com
Azure Service Fabric Resource Provider API Client

Update Management

azure.com
APIs for managing software update configurations.

Amazon SimpleDB

Amazon SimpleDB is a web service providing the core database functions of data indexing and querying in the cloud. By offloading the time and effort associated with building and operating a web-scale database, SimpleDB provides developers the freedom to focus on application development. A traditional, clustered relational database requires a sizable upfront capital outlay, is complex to design, and often requires extensive and repetitive database administration. Amazon SimpleDB is dramatically simpler, requiring no schema, automatically indexing your data and providing a simple API for storage and access. This approach eliminates the administrative burden of data modeling, index maintenance, and performance tuning. Developers gain access to this functionality within Amazon's proven computing environment, are able to scale instantly, and pay only for what they use. Visit http://aws.amazon.com/simpledb/ for more information.

AWS Network Manager

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 MemoryDB

MemoryDB for Redis is a fully managed, Redis-compatible, in-memory database that delivers ultra-fast performance and Multi-AZ durability for modern applications built using microservices architectures. MemoryDB stores the entire database in-memory, enabling low latency and high throughput data access. It is compatible with Redis, a popular open source data store, enabling you to leverage Redis’ flexible and friendly data structures, APIs, and commands.

Amazon Lex Runtime Service

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, .

AWS Price List Service

Amazon Web Services Price List Service API (Amazon Web Services Price List Service) is a centralized and convenient way to programmatically query Amazon Web Services for services, products, and pricing information. The Amazon Web Services Price List Service uses standardized product attributes such as Location, Storage Class, and Operating System, and provides prices at the SKU level. You can use the Amazon Web Services Price List Service to build cost control and scenario planning tools, reconcile billing data, forecast future spend for budgeting purposes, and provide cost benefit analysis that compare your internal workloads with Amazon Web Services. Use GetServices without a service code to retrieve the service codes for all AWS services, then GetServices with a service code to retreive the attribute names for that service. After you have the service code and attribute names, you can use GetAttributeValues to see what values are available for an attribute. With the service code and an attribute name and value, you can use GetProducts to find specific products that you're interested in, such as an AmazonEC2 instance, with a Provisioned IOPS volumeType. Service Endpoint Amazon Web Services Price List Service API provides the following two endpoints: https://api.pricing.us-east-1.amazonaws.com https://api.pricing.ap-south-1.amazonaws.com

Platform API

The REST API specification for Ably.

SubscriptionsManagementClient

azure.com
The Admin Subscriptions Management Client.

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

AWS Server Migration 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