Mock sample for your project: DataLakeStoreFileSystemManagementClient API

Integrate with "DataLakeStoreFileSystemManagementClient API" from azure.com in no time with Mockoon's ready to use mock sample

DataLakeStoreFileSystemManagementClient

azure.com

Version: 2016-11-01


Use this API in your project

Start working with "DataLakeStoreFileSystemManagementClient 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

Creates an Azure Data Lake Store filesystem client.

Other APIs by azure.com

Azure Media Services

azure.com
This Swagger was generated by the API Framework.

UsageManagementClient

azure.com

SubscriptionClient

azure.com
The User Subscription Management Client.

MonitorManagementClient

azure.com

ContainerServiceClient

azure.com
The Container Service Client.

Content Moderator Client

azure.com
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.

Azure Stack Azure Bridge Client

azure.com

ConsumptionManagementClient

azure.com
Consumption management client provides access to consumption resources for Azure Enterprise Subscriptions.

BlockchainManagementClient

azure.com
REST API for Azure Blockchain Service

BlueprintClient

azure.com
Azure Blueprints Client provides access to blueprint definitions, assignments, and artifacts, and related blueprint operations.

GuestConfiguration

azure.com

FabricAdminClient

azure.com
Storage subsystem operation endpoints and objects.

Other APIs in the same category

Local Search Client

microsoft.com
The Local Search client lets you send a search query to Bing and get back search results that include local businesses such as restaurants, hotels, retail stores, or other local businesses. The query can specify the name of the local business or it can ask for a list (for example, restaurants near me).

SubscriptionsManagementClient

azure.com
The Admin Subscriptions Management Client.

AWS IoT Fleet Hub

With Fleet Hub for AWS IoT Device Management you can build stand-alone web applications for monitoring the health of your device fleets. Fleet Hub for AWS IoT Device Management is in public preview and is subject to change.

Amazon Augmented AI Runtime

Amazon Augmented AI (Amazon A2I) adds the benefit of human judgment to any machine learning application. When an AI application can't evaluate data with a high degree of confidence, human reviewers can take over. This human review is called a human review workflow. To create and start a human review workflow, you need three resources: a worker task template, a flow definition, and a human loop. For information about these resources and prerequisites for using Amazon A2I, see Get Started with Amazon Augmented AI in the Amazon SageMaker Developer Guide. This API reference includes information about API actions and data types that you can use to interact with Amazon A2I programmatically. Use this guide to: Start a human loop with the StartHumanLoop operation when using Amazon A2I with a custom task type. To learn more about the difference between custom and built-in task types, see Use Task Types. To learn how to start a human loop using this API, see Create and Start a Human Loop for a Custom Task Type in the Amazon SageMaker Developer Guide. Manage your human loops. You can list all human loops that you have created, describe individual human loops, and stop and delete human loops. To learn more, see Monitor and Manage Your Human Loop in the Amazon SageMaker Developer Guide. Amazon A2I integrates APIs from various AWS services to create and start human review workflows for those services. To learn how Amazon A2I uses these APIs, see Use APIs in Amazon A2I in the Amazon SageMaker Developer Guide.

Amazon CloudFront

Amazon CloudFront This is the Amazon CloudFront API Reference. This guide is for developers who need detailed information about CloudFront API actions, data types, and errors. For detailed information about CloudFront features, see the Amazon CloudFront Developer Guide.

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 QLDB

The control plane for Amazon QLDB

AWS Marketplace Catalog Service

Catalog API actions allow you to manage your entities through list, describe, and update capabilities. An entity can be a product or an offer on AWS Marketplace. You can automate your entity update process by integrating the AWS Marketplace Catalog API with your AWS Marketplace product build or deployment pipelines. You can also create your own applications on top of the Catalog API to manage your products on AWS Marketplace.

AWS CodeDeploy

AWS CodeDeploy AWS CodeDeploy is a deployment service that automates application deployments to Amazon EC2 instances, on-premises instances running in your own facility, serverless AWS Lambda functions, or applications in an Amazon ECS service. You can deploy a nearly unlimited variety of application content, such as an updated Lambda function, updated applications in an Amazon ECS service, code, web and configuration files, executables, packages, scripts, multimedia files, and so on. AWS CodeDeploy can deploy application content stored in Amazon S3 buckets, GitHub repositories, or Bitbucket repositories. You do not need to make changes to your existing code before you can use AWS CodeDeploy. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during application deployment, and handles the complexity of updating your applications, without many of the risks associated with error-prone manual deployments. AWS CodeDeploy Components Use the information in this guide to help you work with the following AWS CodeDeploy components: Application : A name that uniquely identifies the application you want to deploy. AWS CodeDeploy uses this name, which functions as a container, to ensure the correct combination of revision, deployment configuration, and deployment group are referenced during a deployment. Deployment group : A set of individual instances, CodeDeploy Lambda deployment configuration settings, or an Amazon ECS service and network details. A Lambda deployment group specifies how to route traffic to a new version of a Lambda function. An Amazon ECS deployment group specifies the service created in Amazon ECS to deploy, a load balancer, and a listener to reroute production traffic to an updated containerized application. An EC2/On-premises deployment group contains individually tagged instances, Amazon EC2 instances in Amazon EC2 Auto Scaling groups, or both. All deployment groups can specify optional trigger, alarm, and rollback settings. Deployment configuration : A set of deployment rules and deployment success and failure conditions used by AWS CodeDeploy during a deployment. Deployment : The process and the components used when updating a Lambda function, a containerized application in an Amazon ECS service, or of installing content on one or more instances. Application revisions : For an AWS Lambda deployment, this is an AppSpec file that specifies the Lambda function to be updated and one or more functions to validate deployment lifecycle events. For an Amazon ECS deployment, this is an AppSpec file that specifies the Amazon ECS task definition, container, and port where production traffic is rerouted. For an EC2/On-premises deployment, this is an archive file that contains source content—source code, webpages, executable files, and deployment scripts—along with an AppSpec file. Revisions are stored in Amazon S3 buckets or GitHub repositories. For Amazon S3, a revision is uniquely identified by its Amazon S3 object key and its ETag, version, or both. For GitHub, a revision is uniquely identified by its commit ID. This guide also contains information to help you get details about the instances in your deployments, to make on-premises instances available for AWS CodeDeploy deployments, to get details about a Lambda function deployment, and to get details about Amazon ECS service deployments. AWS CodeDeploy Information Resources AWS CodeDeploy User Guide AWS CodeDeploy API Reference Guide AWS CLI Reference for AWS CodeDeploy AWS CodeDeploy Developer Forum

AWS Migration Hub

The AWS Migration Hub API methods help to obtain server and application migration status and integrate your resource-specific migration tool by providing a programmatic interface to Migration Hub. Remember that you must set your AWS Migration Hub home region before you call any of these APIs, or a HomeRegionNotSetException error will be returned. Also, you must make the API calls while in your home region.

Amazon Mobile Analytics

Amazon Mobile Analytics is a service for collecting, visualizing, and understanding app usage data at scale.

Elastic Load Balancing

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.