Microsoft Docs - 최신 문서
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Selected Feed: Azure
Deploy template - Azure portal - Azure Resource Manager
https://docs.microsoft.com/en-us/azure/azure-resource-manager/templates/quickstart-create-templates-use-the-portal Learn how to create your first Azure Resource Manager template using the Azure portal, and how to deploy it.Published Date : 2020년 1월 22일 수요일
azureml.train.automl.automlconfig.AutoMLConfig class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.automlconfig Configuration for submitting an Automated Machine Learning experiment in Azure Machine Learning. This configuration object contains and persists the parameters for configuring the experiment run parameters, as well as the training data to be used at run time. For guidance on selecting your settings, you may refer to https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-configure-auto-train. The following code shows a basic example of creating an AutoMLConfig object, and submitting an experiment with the defined configuration: from azureml.core.experiment import Experiment from azureml.core.workspace import Workspace from azureml.train.automl import AutoMLConfig automated_ml_config = AutoMLConfig(task = 'regression', training_data = your_training_data, label_column_name = your_training_label_name, iterations=30, iteration_timeout_minutes=5, primary_metric="spearman_correlation") ws = Workspace.from_config() experiment = Experiment(ws, "your-experiment-name") run = experiment.submit(automated_ml_config, show_output=True)Published Date : 2020년 1월 22일 수요일
azureml.pipeline.steps.python_script_step.PythonScriptStep class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-pipeline-steps/azureml.pipeline.steps.python_script_step.pythonscriptstep Creates an Azure ML Pipeline step that runs Python script. For an example of using PythonScriptStep, see the notebook https://aka.ms/pl-get-started.Published Date : 2020년 1월 22일 수요일
azureml.opendatasets.SanFranciscoSafety class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-opendatasets/azureml.opendatasets.sanfranciscosafety San Francisco city safety class.Published Date : 2020년 1월 22일 수요일
azureml.interpret.common.constants.ExplainParams class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-interpret/azureml.interpret.common.constants.explainparams Provide constants for interpret community (init, explain_local and explain_global) parameters.Published Date : 2020년 1월 22일 수요일
azureml.opendatasets.ChicagoSafety class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-opendatasets/azureml.opendatasets.chicagosafety Chicago city safety class.Published Date : 2020년 1월 22일 수요일
azureml.interpret.common.constants.History class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-interpret/azureml.interpret.common.constants.history Provide constants related to uploading assets to run history.Published Date : 2020년 1월 22일 수요일
azureml.explain.model.common.constants.MimicSerializationConstants class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-explain-model/azureml.explain.model.common.constants.mimicserializationconstants Provide internal class that defines fields used for MimicExplainer serialization.Published Date : 2020년 1월 22일 수요일
azureml.data.file_dataset.FileDataset class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.data.file_dataset.filedataset Represents a collection of file references in datastores or public URLs to use in Azure Machine Learning. A FileDataset defines a series of lazily-evaluated, immutable operations to load data from the data source into file streams. Data is not loaded from the source until FileDataset is asked to deliver data. A FileDataset is created using the method of the FileDatasetFactory class. For more information, see the article Add & register datasets. To get started working with a file dataset, see https://aka.ms/filedataset-samplenotebook.Published Date : 2020년 1월 22일 수요일
azureml.exceptions.AzureMLException class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.exceptions.azuremlexception The base class for all Azure ML exceptions. This class extends the Python Exception class. If you are trying to catch only Azure ML exceptions, then catch them with this class.Published Date : 2020년 1월 22일 수요일
azureml.core.webservice.aks.AksWebservice class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.webservice.aks.akswebservice Represents a machine learning model deployed as a web service endpoint on Azure Kubernetes Service. A deployed service is created from a model, script, and associated files. The resulting web service is a load-balanced, HTTP endpoint with a REST API. You can send data to this API and receive the prediction returned by the model. AksWebservice deploys a single service to one endpoint. To deploy multiple services to one endpoint, use the class. For more information, see Deploy a model to an Azure Kubernetes Service cluster.Published Date : 2020년 1월 22일 수요일
azureml.core.webservice.webservice.Webservice class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.webservice.webservice.webservice Defines base functionality for deploying models as web service endpoints in Azure Machine Learning. Webservice constructor is used to retrieve a cloud representation of a Webservice object associated with the provided Workspace. Returns an instance of a child class corresponding to the specific type of the retrieved Webservice object. The Webservice class allows for deploying machine learning models from either a or object. For more information about working with Webservice, see Deploy models with Azure Machine Learning.Published Date : 2020년 1월 22일 수요일
azureml.data.FileDataset class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.data.filedataset Represents a collection of file references in datastores or public URLs to use in Azure Machine Learning. A FileDataset defines a series of lazily-evaluated, immutable operations to load data from the data source into file streams. Data is not loaded from the source until FileDataset is asked to deliver data. A FileDataset is created using the method of the FileDatasetFactory class. For more information, see the article Add & register datasets. To get started working with a file dataset, see https://aka.ms/filedataset-samplenotebook.Published Date : 2020년 1월 22일 수요일
azureml.core.webservice.aci.AciWebservice class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.webservice.aci.aciwebservice Represents a machine learning model deployed as a web service endpoint on Azure Container Instances. A deployed service is created from a model, script, and associated files. The resulting web service is a load-balanced, HTTP endpoint with a REST API. You can send data to this API and receive the prediction returned by the model. For more information, see Deploy a model to Azure Container Instances.Published Date : 2020년 1월 22일 수요일
azureml.core.model.InferenceConfig class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.model.inferenceconfig Represents configuration settings for a custom environment used for deployment. Inference configuration is an input parameter for deployment-related actions:Published Date : 2020년 1월 22일 수요일
azureml.core.webservice.Webservice class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.webservice.webservice(class) Defines base functionality for deploying models as web service endpoints in Azure Machine Learning. Webservice constructor is used to retrieve a cloud representation of a Webservice object associated with the provided Workspace. Returns an instance of a child class corresponding to the specific type of the retrieved Webservice object. The Webservice class allows for deploying machine learning models from either a or object. For more information about working with Webservice, see Deploy models with Azure Machine Learning.Published Date : 2020년 1월 22일 수요일
azureml.core.image.container.ContainerImage class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.image.container.containerimage Represents a container image, currently only for Docker images. The image contains the dependencies needed to run the model including: The runtime Python environment definitions specified in a Conda file Ability to enable GPU support Custom Docker file for specific run commandsPublished Date : 2020년 1월 22일 수요일
azureml.core.webservice.AciWebservice class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.webservice.aciwebservice Represents a machine learning model deployed as a web service endpoint on Azure Container Instances. A deployed service is created from a model, script, and associated files. The resulting web service is a load-balanced, HTTP endpoint with a REST API. You can send data to this API and receive the prediction returned by the model. For more information, see Deploy a model to Azure Container Instances.Published Date : 2020년 1월 22일 수요일
azureml.core.image.Image class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.image.image(class) Defines the abstract parent class for Azure Machine Learning Images.Published Date : 2020년 1월 22일 수요일
azureml.core.model.Model class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.model.model Represents the result of machine learning training. A model is the result of a Azure Machine learning training or some other model training process outside of Azure. Regardless of how the model is produced, it can be registered in a workspace, where it is represented by a name and a version. With the Model class, you can package models for use with Docker and deploy them as a real-time endpoint that can be used for inference requests. For an end-to-end tutorial showing how models are created, managed, and consumed, see Train image classification model with MNIST data and scikit-learn using Azure Machine Learning.Published Date : 2020년 1월 22일 수요일
azureml.core.Webservice class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.webservice(class) Defines base functionality for deploying models as web service endpoints in Azure Machine Learning. Webservice constructor is used to retrieve a cloud representation of a Webservice object associated with the provided Workspace. Returns an instance of a child class corresponding to the specific type of the retrieved Webservice object. The Webservice class allows for deploying machine learning models from either a or object. For more information about working with Webservice, see Deploy models with Azure Machine Learning.Published Date : 2020년 1월 22일 수요일
azureml.core.compute.AmlCompute class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.compute.amlcompute(class) Manages an Azure Machine Learning compute in Azure Machine Learning. An Azure Machine Learning Compute (AmlCompute) is a managed-compute infrastructure that allows you to easily create a single or multi-node compute. The compute is created within your workspace region as a resource that can be shared with other users. For more information, see What are compute targets in Azure Machine Learning?Published Date : 2020년 1월 22일 수요일
azureml.core.Model class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.model(class) Represents the result of machine learning training. A model is the result of a Azure Machine learning training or some other model training process outside of Azure. Regardless of how the model is produced, it can be registered in a workspace, where it is represented by a name and a version. With the Model class, you can package models for use with Docker and deploy them as a real-time endpoint that can be used for inference requests. For an end-to-end tutorial showing how models are created, managed, and consumed, see Train image classification model with MNIST data and scikit-learn using Azure Machine Learning.Published Date : 2020년 1월 22일 수요일
azureml.core.Image class - Azure Machine Learning Python
https://docs.microsoft.com/ko-kr/python/api/azureml-core/azureml.core.image(class) Defines the abstract parent class for Azure Machine Learning Images.Published Date : 2020년 1월 22일 수요일
SplashScreen - Windows UWP applications
https://docs.microsoft.com/en-us/uwp/schemas/appxpackage/appxmanifestschema2013/element-splashscreen Size requirements of a splash screen image are shown here: Image attributes Scale Image size in pixels Applications\Application\VisualElements\SplashScreen\@Image 100 620x300 140 868x420 180 1116x540 The following are supported background color names: aliceBlue antiqueWhite aqua aquamarine azure beigePublished Date : 2020년 1월 22일 수요일
SplashScreen - Windows UWP applications
https://docs.microsoft.com/en-us/uwp/schemas/appxpackage/appxmanifestschema2010-v2/element-splashscreen Size requirements of a splash screen image are shown here: Image attributes Scale Image size in pixels Applications\Application\VisualElements\SplashScreen\@Image 100 620x300 140 868x420 180 1116x540 The following are supported background color names: aliceBlue antiqueWhite aqua aquamarine azure beigePublished Date : 2020년 1월 22일 수요일
SplashScreen - Windows UWP applications
https://docs.microsoft.com/en-us/uwp/schemas/appxpackage/appxmanifestschema/element-splashscreen Size requirements of a splash screen image are shown here: Image attributes Scale Image size in pixels Applications\Application\VisualElements\SplashScreen\@Image 100 620x300 140 868x420 180 1116x540 The following are supported background color names: aliceBlue antiqueWhite aqua aquamarine azure beigePublished Date : 2020년 1월 22일 수요일
VisualElements - Windows UWP applications
https://docs.microsoft.com/en-us/uwp/schemas/appxpackage/appxmanifestschema/element-visualelements here: Image attribute Scale Image size in pixels Applications\Application\VisualElements\@Logo 100 150x150 140 210x210 180 270x270 Applications\Application\VisualElements\@SmallLogo 100 30x30 140 42x42 180 54x54 These are the supported background color names: aliceBlue antiqueWhite aqua aquamarine azurePublished Date : 2020년 1월 22일 수요일
uap3:VisualElements (Windows 10) - Windows UWP applications
https://docs.microsoft.com/en-us/uwp/schemas/appxpackage/uapmanifestschema/element-uap3-visualelements-manual Applications/Application/VisualElements/@Square150x150Logo 100 150x150 250 375x375 Applications/Application/VisualElements/@Square44x44Logo 100 44x44 250 110x110 Applications/Application/VisualElements/@Tall150x310Logo 100 150x310 250 375x775 These are the supported background color names: aliceBlue antiqueWhite aqua aquamarine azurePublished Date : 2020년 1월 22일 수요일
uap:SplashScreen (Windows 10) - Windows UWP applications
https://docs.microsoft.com/en-us/uwp/schemas/appxpackage/uapmanifestschema/element-uap-splashscreen Size requirements of a splash screen image are shown here: Image attributes Scale Image size in pixels Applications/Application/VisualElements/SplashScreen/@Image 100 620x300 140 868x420 180 1116x540 The following are supported background color names: aliceBlue antiqueWhite aqua aquamarine azure beigePublished Date : 2020년 1월 22일 수요일
uap:VisualElements (Windows 10) - Windows UWP applications
https://docs.microsoft.com/en-us/uwp/schemas/appxpackage/uapmanifestschema/element-uap-visualelements Applications/Application/VisualElements/@Square150x150Logo 100 150x150 250 375x375 Applications/Application/VisualElements/@Square44x44Logo 100 44x44 250 110x110 Applications/Application/VisualElements/@Tall150x310Logo 100 150x310 250 375x775 These are the supported background color names: aliceBlue antiqueWhite aqua aquamarine azurePublished Date : 2020년 1월 22일 수요일
VisualElements - Windows UWP applications
https://docs.microsoft.com/en-us/uwp/schemas/appxpackage/appxmanifestschema2010-v2/element-visualelements here: Image attribute Scale Image size in pixels Applications\Application\VisualElements\@Logo 100 150x150 140 210x210 180 270x270 Applications\Application\VisualElements\@SmallLogo 100 30x30 140 42x42 180 54x54 These are the supported background color names: aliceBlue antiqueWhite aqua aquamarine azurePublished Date : 2020년 1월 22일 수요일
Use Spark Structured Streaming with Apache Spark and Kafka on HDInsight - Code Samples
https://docs.microsoft.com/en-us/samples/azure-samples/hdinsight-spark-kafka-structured-streaming/hdinsight-spark-kafka-structured-streaming/ This example contains a Jupyter notebook that demonstrates how to use Apache Spark structured streaming with Apache Kafka on Azure HDInsight.Published Date : 2020년 1월 22일 수요일
Code examples for Cognitive Services Quickstarts - Code Samples
https://docs.microsoft.com/en-us/samples/azure-samples/cognitive-services-quickstart-code/cognitive-services-quickstart-code/ This repository contains the code examples used by the QuickStarts on the Cognitive Services DocumentationPublished Date : 2020년 1월 22일 수요일
Upgrade TFS - TFS
https://docs.microsoft.com/en-us/azure/devops/server/upgrade/walkthrough Walkthrough of a standard upgrade of a two server deployment from TFS 2012 to TFS 2015.Published Date : 2020년 1월 22일 수요일
Upgrade your deployment - Azure DevOps Server & TFS
https://docs.microsoft.com/en-us/azure/devops/server/upgrade/get-started Upgrade your instance of Azure DevOps Server to the latest versionPublished Date : 2020년 1월 22일 수요일
Release Notes, 2019 Update 1 - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/server/release-notes/azuredevops2019u1 Azure DevOps Server 2019 Update 1 release notes. You can direct upgrade to this release from Azure DevOps Server 2019 or TFS 2012 and newer.Published Date : 2020년 1월 22일 수요일
What's new on-premises - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/server/whats-new Your guide to new features that support DevOps made available with Azure DevOps Server and Team Foundation ServerPublished Date : 2020년 1월 22일 수요일
Run the TFS Upgrade Wizard - Azure DevOps Server & TFS
https://docs.microsoft.com/en-us/azure/devops/server/upgrade/run-upgrade-wizard Run the TFS Upgrade WizardPublished Date : 2020년 1월 22일 수요일
Configure with TFSConfig - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/server/command-line/tfsconfig-cmd Use TFSConfig to manage the configuration of your Azure DevOps Server from the command-line.Published Date : 2020년 1월 22일 수요일
Install & configure single server - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/server/install/single-server Install and set up Azure DevOps Server or TFS Express on a single server by using the Server Configuration WizardPublished Date : 2020년 1월 22일 수요일
Install and configure - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/server/install/get-started Use the new install guide for Team Foundation Server to set up TFS on your server or serversPublished Date : 2020년 1월 22일 수요일
Set up a dual server configuration - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/server/install/dual-server How to set up Team Foundation Server in a dual server configuration using the full configuration wizardPublished Date : 2020년 1월 22일 수요일
Do a pre-production upgrade - Azure DevOps Server & TFS
https://docs.microsoft.com/en-us/azure/devops/server/upgrade/pre-production Do a dry run of your upgrade in pre-production to avoid surprises in production.Published Date : 2020년 1월 22일 수요일
Configure Visual Studio Lab Management - TFS
https://docs.microsoft.com/en-us/azure/devops/server/command-line/tfslabconfig-cmd Use TFSLabConfig to manage and configure the lab service provide by Visual Studio Lab ManagementPublished Date : 2020년 1월 22일 수요일
Administration - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/server/server/ Install, upgrade, or manage your on-premises deployment of Azure DevOps Server, previously named Visual Studio Team Foundation Server (TFS), with the guidance provided here.Published Date : 2020년 1월 22일 수요일
Install & configure multiple servers - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/server/install/multiple-server How to set up Azure DevOps Server in a multiple server configuration using the full configuration wizardPublished Date : 2020년 1월 22일 수요일
Sign up, sign in, invite teammates - Azure DevOps Services
https://docs.microsoft.com/en-us/azure/devops/user-guide/sign-up-invite-teammates Quickstart guide to signing up and inviting others to join a project in Azure DevOpsPublished Date : 2020년 1월 22일 수요일
Features and services included - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/services Understand the services provided by in Azure DevOps Services and Team Foundation ServerPublished Date : 2020년 1월 22일 수요일
Get started as a project admin or organization Owner - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/project-admin-tutorial Learn how to structure a project, manage users, and more to support your software development teams in Azure DevOpsPublished Date : 2020년 1월 22일 수요일
Supported roles for software development - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/roles Understand how Azure DevOps tools support various software development rolesPublished Date : 2020년 1월 22일 수요일
Tools and clients that connect - Azure DevOps - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/tools Understand the tools that support connecting to Azure DevOpsPublished Date : 2020년 1월 22일 수요일
DevOps tools overview for Azure DevOps - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/devops-alm-overview Guide to getting started using DevOps and Agile tools provided by Azure DevOps Services and Team Foundation Server (TFS)Published Date : 2020년 1월 22일 수요일
Plan, code, collaborate, ship applications - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/what-is-azure-devops Get an integrated set of features to help you plan, code, collaborate, and ship your applications faster.Published Date : 2020년 1월 22일 수요일
Get support and provide feedback - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/provide-feedback Guide to providing product and content feedback, and accessing support resources in Azure DevOpsPublished Date : 2020년 1월 22일 수요일
Understand source control - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/source-control What is source control or version control in Azure DevOps & Team Foundation Server?Published Date : 2020년 1월 22일 수요일
Feature overview for Azure DevOps - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/alm-devops-features Comprehensive index to all features for Azure DevOpsPublished Date : 2020년 1월 22일 수요일
Add, run, update inline tests - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/add-run-manual-tests Learn how to add, run, and quickly update manual test casesPublished Date : 2020년 1월 22일 수요일
Code with Git - Azure DevOps - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/code-with-git Learn how to share code within a Git repo and new projectPublished Date : 2020년 1월 22일 수요일
Understand differences between Azure DevOps Services and Azure DevOps Server - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/about-azure-devops-services-tfs Understand the fundamental differences between Azure DevOps Services and Azure DevOps Server, formerly named Visual Studio Team Services (VSTS), and Team Foundation Server (TFS)Published Date : 2020년 1월 22일 수요일
Navigate in Visual Studio Team Explorer - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/work-team-explorer Download TFS clients, navigate in Team Explorer for Azure DevOps Services & Team Foundation ServerPublished Date : 2020년 1월 22일 수요일
Questions and answers to support getting started - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/faqs FAQs to support getting started using the hosted cloud offering and on-premises offering of Azure DevOpsPublished Date : 2020년 1월 22일 수요일
Troubleshoot connecting project - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/troubleshoot-connection Follow these steps to resolve connection issues with Azure DevOps Services & Team Foundation ServerPublished Date : 2020년 1월 22일 수요일
Azure DevOps Service status - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/user-guide/service-status-info Understand how Azure DevOps Services status is monitored and available to usersPublished Date : 2020년 1월 22일 수요일
Voluntarily provide stakeholder feedback - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/voluntary-stakeholder-feedback Voluntarily provide stakeholder feedback in Azure DevOps or TFS using the Exploratory Testing browser extension when you want to test your applicationsPublished Date : 2020년 1월 22일 수요일
Copy and clone test suites and cases - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/mtm/copying-and-cloning-test-suites-and-test-cases Manual and exploratory testing - Copying and cloning test suites and test cases when you want to test web applicationsPublished Date : 2020년 1월 22일 수요일
FAQs and problem solutions - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/reference-qa FAQs for manual testing topics for Azure DevOps and Microsoft Team Foundation Server (TFS)Published Date : 2020년 1월 22일 수요일
Exploratory test in standalone mode - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/standalone-mode-exploratory-testing Manual and exploratory testing - exploratory testing by using the Microsoft Test & Feedback extension in Standalone modePublished Date : 2020년 1월 22일 수요일
Test Microsoft Store apps - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/mtm/testing-microsoft-store-apps Manual and exploratory testing - Testing Microsoft Store appsPublished Date : 2020년 1월 22일 수요일
Track stakeholder feedback - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/track-stakeholder-feedback Track stakeholder feedback in Azure DevOps or TFS using the Exploratory Testing browser extension when you want to test your applicationsPublished Date : 2020년 1월 22일 수요일
Test Case Management Reporting FAQs - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/reference-tcm FAQs for Test Case Management Reporting for Azure DevOps and Microsoft Team Foundation Server (TFS)Published Date : 2020년 1월 22일 수요일
Run automated tests from test plans - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/run-automated-tests-from-test-hub Run automated tests on-demand against Team Foundation builds from test plans in the Test Manager with a build or release pipelinePublished Date : 2020년 1월 22일 수요일
Request stakeholder feedback - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/request-stakeholder-feedback Request stakeholder feedback in Azure DevOps or TFS using the Exploratory Testing browser extensionPublished Date : 2020년 1월 22일 수요일
Use configurations and specify test platforms - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/mtm/test-configurations-specifying-test-platforms Manual and exploratory testing - Test configurations, specifying test platforms when you want to test web applicationsPublished Date : 2020년 1월 22일 수요일
Collect more diagnostic data - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/mtm/collect-more-diagnostic-data-in-manual-tests Manual and exploratory testing - Collect more diagnostic data in manual tests when you want to test web applicationsPublished Date : 2020년 1월 22일 수요일
Share steps between test cases - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/mtm/share-steps-between-test-cases Manual and exploratory testing - Share steps between all your test cases when you want to test web applicationsPublished Date : 2020년 1월 22일 수요일
Exploratory test your web app - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/perform-exploratory-tests Test tools - Exploratory test your web app in Azure DevOps from your web browser with the Microsoft Test & Feedback extensionPublished Date : 2020년 1월 22일 수요일
Load test in the cloud with Visual Studio - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/load-test/getting-started-with-performance-testing Performance test your app with cloud-based load tests using the features of Visual Studio, Azure DevOps, and TFSPublished Date : 2020년 1월 22일 수요일
Repeat a test with different data - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/repeat-test-with-different-data Manual and exploratory testing - repeat a test with different data in Azure DevOps and Team Foundation Server (TFS)Published Date : 2020년 1월 22일 수요일
Run manual tests - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/run-manual-tests Test tools - Run manual tests in Azure DevOps and TFS to make sure each of the deliverables meets your users needsPublished Date : 2020년 1월 22일 수요일
Create a service hook for Azure DevOps Services and TFS with Datadog - Azure DevOps
https://docs.microsoft.com/en-us/azure/devops/service-hooks/services/datadog Use Datadog with your Azure DevOps Services organizationPublished Date : 2020년 1월 22일 수요일
Manage how long to keep test results - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/how-long-to-keep-test-results Manage how long Azure DevOps keeps your manual test results by clearing test results that you do not need anymore or when you delete your buildsPublished Date : 2020년 1월 22일 수요일
Get insights across exploratory test sessions - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/insights-exploratory-testing Manual and exploratory testing - get insights with exploratory testing across your test sessions by using the Microsoft Test & Feedback extensionPublished Date : 2020년 1월 22일 수요일
Run cloud-based load tests on your machines - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/load-test/clt-with-private-machines Run cloud-based load tests by using your own subscription and machines using Azure DevOps and TFSPublished Date : 2020년 1월 22일 수요일
Perform user acceptance testing - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/user-acceptance-testing Create and run user acceptance tests in Azure DevOps and TFS to make sure each of the deliverables meets your users needsPublished Date : 2020년 1월 22일 수요일
Run manual tests with MTM - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/mtm/run-manual-tests-with-microsoft-test-manager Manual and exploratory testing - Run manual tests with Microsoft Test Manager when you want to test web applicationsPublished Date : 2020년 1월 22일 수요일
Track test status - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/track-test-status Track test status with charts and graphs using Azure DevOpsPublished Date : 2020년 1월 22일 수요일
Run automated tests with MTM - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/mtm/run-automated-tests-with-microsoft-test-manager Manual and exploratory testing - Run automated tests with Microsoft Test ManagerPublished Date : 2020년 1월 22일 수요일
Give feedback with Test & Feedback extension - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/provide-stakeholder-feedback Provide feedback in Azure DevOps or TFS using the Exploratory Testing browser extensionPublished Date : 2020년 1월 22일 수요일
Exploratory and manual testing overview - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/overview Test tools - Drive quality and collaboration throughout the development process with manual and exploratory testing capabilitiesPublished Date : 2020년 1월 22일 수요일
New test plans page - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/new-test-plans-page New Test Plans pagePublished Date : 2020년 1월 22일 수요일
Test performance from the Azure portal - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/load-test/app-service-web-app-performance-test Run Azure web app performance tests to check how your app handles user load. Measure response time and find failures that might indicate problems.Published Date : 2020년 1월 22일 수요일
Guidance on MTM usage - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/mtm/guidance-mtm-usage Manual and exploratory testing - Guidance on Microsoft Test Manager usage when you want to test web applicationsPublished Date : 2020년 1월 22일 수요일
Test different configurations - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/test-different-configurations Manual and exploratory testing - test different configurations with Azure DevOps and Team Foundation Server (TFS)Published Date : 2020년 1월 22일 수요일
FAQs for load testing - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/load-test/reference-qa FAQs for load testing topics using the features of Azure DevOps and Microsoft Team Foundation Server (TFS)Published Date : 2020년 1월 22일 수요일
New test plans view - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/preview/new-test-plan-page A preview of a new user experience for test plans on Azure DevOpsPublished Date : 2020년 1월 22일 수요일
Add findings to existing bugs - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/add-to-bugs-exploratory-testing Manual and exploratory testing - add findings to existing bugs existing bugs when using the Test & Feedback extensionPublished Date : 2020년 1월 22일 수요일
Permissions and access for manual testing - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/manual-test-permissions Default permissions and access levels in Azure DevOps and TFS for manual and exploratory testing topics and problemsPublished Date : 2020년 1월 22일 수요일
Create test plans and suites - Azure Test Plans
https://docs.microsoft.com/en-us/azure/devops/test/create-a-test-plan Test tools - Create test plans in Azure Test Plans and Azure DevOps Server to make sure each of the deliverables meets your users needsPublished Date : 2020년 1월 22일 수요일