Ruthe  Sawayn

Ruthe Sawayn

1627983240

Perform Git Operation in Visual Studio - Azure DevOps 20

In this vide I’ll show how to perform Git operations using Visual Studio.

#AzureDevops
#Azure

#azuredevops #azure #git

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Buddha Community

Perform Git Operation in Visual Studio - Azure DevOps 20
Rylan  Becker

Rylan Becker

1621121100

Writing U-SQL scripts using Visual Studio for Azure Data Lake Analytics

In the 2nd article of the series for Azure Data Lake Analytics, we will use Visual Studio for writing U-SQL scripts.

Introduction

Azure Data Lake stores the unstructured, structured, and semi-structured data in the Azure cloud infrastructure. You can use Azure portal, Azure Data Factory(ADF), Azure CLI, or various other tools. In the previous article, An overview of Azure Data Lake Analytics and U-SQL, we explored the Azure Data lake Analytics using the U-SQL script.

In this article, we will understand U-SQL scripts and executing them using Visual Studio.

U-SQL scripts execution in the Visual Studio

U-SQL is known as a big data query language, and it combines the syntax similar to t-SQL and the power of C## language. You can extract, transform data in the required format using the scripts. It has few predefined extractors for CSV, Text, TSV for extracting data from these formats. Similarly, it allows you to convert the output to your desired format. It offers big data processing from gigabyte to petabyte scale. You can combine data from Azure Data Lake Storage, Azure SQL DB Azure Blob Storage, Azure SQL Data Warehouse.

You can develop and execute the scripts locally using Visual Studio. Later, you can move your resources to the Azure cloud. This approach allows you to save the cost for Azure resources ( compute and storage) because in the Visual Studio, it does not cost you for the executions.

To use these scripts in the Visual Studio, you should have _the _Azure Data Lake and Stream Analytics Tools installed. You can navigate to Visual Studio installer -> Workloads-> Data Storage and processing -> Azure Data lake and Stream Analytics.

Launch the Visual Studio 2019 and create a new U-SQL project. You get a few other templates such as Class Library, Unit Test project and sample application as well. We will work with a project template that creates a project with your USQL scripts.

#azure #sql azure #visual studio #azure data lake analytics #visual studio #u-sql

How to Extend your DevOps Strategy For Success in the Cloud?

DevOps and Cloud computing are joined at the hip, now that fact is well appreciated by the organizations that engaged in SaaS cloud and developed applications in the Cloud. During the COVID crisis period, most of the organizations have started using cloud computing services and implementing a cloud-first strategy to establish their remote operations. Similarly, the extended DevOps strategy will make the development process more agile with automated test cases.

According to the survey in EMEA, IT decision-makers have observed a 129%* improvement in the overall software development process when performing DevOps on the Cloud. This success result was just 81% when practicing only DevOps and 67%* when leveraging Cloud without DevOps. Not only that, but the practice has also made the software predictability better, improve the customer experience as well as speed up software delivery 2.6* times faster.

3 Core Principle to fit DevOps Strategy

If you consider implementing DevOps in concert with the Cloud, then the

below core principle will guide you to utilize the strategy.

  • It is indispensable to follow a continuous process, including all stages from Dev to deploy with the help of auto-provisioning resources of the target platform.
  • The team always keeps an eye on major and minor application changes that can typically appear within a few hours of development to operation. However, the support of unlimited resource provisioning is needed at the stage of deployment.
  • Cloud or hybrid configuration can associate this process, but you must confirm that configuration should support multiple cloud brands like Microsoft, AWS, Google, any public and private cloud models.

Guide to Remold Business with DevOps and Cloud

Companies are now re-inventing themselves to become better at sensing the next big thing their customers need and finding ways with the Cloud based DevOps to get ahead of the competition.

#devops #devops-principles #azure-devops #devops-transformation #good-company #devops-tools #devops-top-story #devops-infrastructure

Ruthe  Sawayn

Ruthe Sawayn

1627983240

Perform Git Operation in Visual Studio - Azure DevOps 20

In this vide I’ll show how to perform Git operations using Visual Studio.

#AzureDevops
#Azure

#azuredevops #azure #git

Nabunya  Jane

Nabunya Jane

1624939448

A side-by-side comparison of Azure DevOps and GitHub

Collaboration is a crucial element in software development; having the right collaboration tools can make a difference and boost the entire team’s productivity. Microsoft introduced its Application Lifecycle Management product with Team Foundation Server (aka TFS) on March 16th, 2006. This software had to be installed on a server within your network and had a user-based license. To reduce the complexity of setting up and maintaining the server, Microsoft released Visual Studio Online–an Azure-based, server-hosted version of TFS. Microsoft manages and administers the servers as well as taking care of backups. To clarify its commitment to agile and DevOps, Microsoft rebranded Visual Studio Online in 2015 as Visual Studio Team Services and later as Azure DevOps in 2018.

Since its beginning, this platform has changed significantly. For example, it introduced a customizable, task-based build service, release gates, and much more. Many organizations across the world made a significant investment to run their businesses on Azure DevOps. For this reason, after Microsoft announced the acquisition of GitHub in mid-2018, GitHub announced its automated workflow system, which is much like Azure Pipelines. It’s called GitHub Actions. Due to the switch, some companies became afraid of having to migrate their practices again. In the past few months, I have gotten several questions about whether it is still worth starting new projects on Azure DevOps, especially after the release of features like GitHub Advanced Security and GitHub Codespaces (similar to Visual Studio Codespaces). In this article, I’ll clarify the differences between these two platforms, and I’ll give you some advice on how you should be using them to your advantage.

Data Residency

To meet the needs of companies that want to keep their data within their network, both GitHub and Azure DevOps provide a server version of their platform. GitHub version is called GitHub Enterprise Server, and the Azure DevOps version is called Azure DevOps Server. Both versions require the client to install and maintain both software and machine.

On the other hand, there is a critical difference between their cloud-hosted version. While Azure DevOps Service allows you to choose the Azure region, which is closes to your organization’s location, to decrease the eventuality of networking latency during the creation of your organization (collection of projects). GitHub doesn’t provide this feature.

Project management and bug tracking

GitHub

At the core of GitHub project management, we can find the issues. This task can be used to track any work item, from feature to bugs, and can be sorted into a Kanban-style board for easy consultation. The issue’s description also supports markdown syntax. Adding a specific keyword #issue-number (ex: #3) can associate the issue with another one. Each issue can be assigned to multiple developers, be linked to pull requests, and have various labels assigned to it. One can link a pull request to an issue to show that a fix is in progress and automatically close the issue when someone merges the pull request.

GitHub Kanban board

  • Lastly, multiple issues can be grouped into milestones that will give immediate feedback about the completion percentage. Milestones can also include a due date.

#azure-devops #microsoft #azure #github #azure devops #azure devops and github

Wasswa  Meagan

Wasswa Meagan

1621106400

Visualizing The Code Coverage Results From Azure Pipelines in Visual Studio

In a previous posts, I explained how to computing code coverage for a .NET Core project with Azure DevOps and Coverlet. In this post, the code coverage visualization could be done directly in Azure DevOps. As a developer, you want to see these results directly into the IDE.

  1. Download the code coverage file from the build artifacts
  2. Open the file in Visual Studio
  3. In the “Code Coverage Results” tool window, find the method you want and double click on it to open the file in the editor with the coverage highlight

#azure devops #azure #tools #visual studio