Manual Testing in Azure DevOps

For manual testing in Azure DevOps, first, we need to create test plans and test suites for tracking manual testing for any events.
How to create Test Plans for Manual Testing?
In Manual Testing, first, create test plans. Follow the below steps to create Test Plans.
In Azure DevOps Server, open your project and click Azure Test Plans or the Test hub in Azure DevOps Server. If you have a test plan, then select the Test plans to visit the page that has all test plans.
Select New Test Plan in the test plane page, to make a test plan for your present event.
In the New Test Plan, type the test plan name. Check the region path and repetition is set in the correct way. Then select Create.
How to add requirement-based test suite and select backlog items for manual testing:
Now attach test suites for pending items that have to be tested manually to perform manual testing in Azure with DevOps.
For adding a suite to a test plan, choose + new menu and select a type of test suite. We can use requirement-based suites to collect our test cases collectively.
By this, we can track the testing condition of a backlog item. Every test case that we add to a requirement-based test suite is connected to the backlog item, automatically.
Under ‘Create requirement-based suites’, we can add one or more paragraphs to separate our work objects, by using a repetitive path for the event. Run the query to see the related pending items.
Under the work items lists given by the query, choose the backlog items we want to test in this event. Select ‘Create suites’ for making a requirement-based suite, for everyone.
How to Create Manual Test Cases for Manual Testing?
Wehave to create Manual Testing cases to verify whether every result, is according to the users’ requirements. Arrange your test cases by attaching them to test plans and test suites. Then select the testers that we need to run the tests in Azure DevOps online training.
Follow the below steps to create test cases in Azure with DevOps:
After creating a test plan and requirement based test suites. Choose a requirement based test suite.
On the Right side of the window, select New Test case.
Select the Click or type here to attach a step link, and add test steps along with the explanation of the action needed for testing, and the expected outputs so that anyone from the team can run the test.
If we want, we can also add any attachments to any step.
Repeat the process until you finished adding all the steps for the test. Now, your test case is created which you can run.
How to Run Manual Tests?
We can run our manual tests and save the outcomes for every test step, with Microsoft Test Runner. If you identify a problem while manual testing, create a bug using Test Runner.
Follow the below steps to run tests in Azure with DevOps for web apps.
After creating the manual tests, in the test suite, choose a test and run it.
Begin the app which you want to test. It is not necessary to run your app on the same computer, as Test Runner. We have to use Test Runner simply to save failed or passed tests while manually running the test.
Mark every test step as passed or failed depending on the expected outcomes. When a test step fails, we can type a comment explaining the reason for its failure.
Create a bug, so that we can able to explain what has failed. The steps and our comments will be added to the bug automatically, and the test case will be connected to the bug.
We can see any bugs that we have specified while our test session.
Save the outputs and close the test runner, after running all tests. All test outputs will be saved in Azure DevOps.
See the status of testing for your test suite. You can see the new output for every test.
Open a test and select the test case in a related work part. To see the bugs filed by the tester, use the child links in the related work area of that work product.
In this article, I have shared how to do manual testing in Azure with DevOps. Follow my articles, to get more updates on Azure DevOps online training India.

#azure #devops #azuredevops #testing

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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

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

Create, Build, Deploy and Configure an Azure Function with Azure DevOps and Azure CLI

This post shows how to create, build, deploy and configure an Azure Function using Azure DevOps, Azure CLI and Powershell. An Azure Function is created in Azure using Azure DevOps with Azure CLI and Powershell. The Azure Function (V3) project is created and built using Visual Studio and C#. This project is deployed to the Azure infrastructure using a second Azure DevOps Pipeline. The Azure Function configuration settings is configured to use Azure Key Vault for secrets.

#asp.net core #azure #devops #.net core #azure devops #azure functions #cli #powershell

Azure Synapse Analytics Database CI/CD using Azure Function

In this article, I will discuss an Azure Database CI/CD approach using Azure Premium Function and Jenkins pipeline. I will only explain the architecture and the approach I took to implement the Database CI/CD pipeline.

Problem Statement and Challenges

I was working on a project where I had to build a Database deployment pipeline using enterprise GitHub which is only accessible through the company’s internal network. Also, port 1433 was blocked from the internal network to the Azure Synapse public endpoint for security reasons. Hence the only option I had was to run my pipeline in an internal network so that I could access GitHub which I was using for my Database Deployment Source Control and send the SQL code to Azure Synapse using Azure function HTTP post as port 1433 was blocked.

#azure #devops #azure-synapse-analytics #azure-devops #azure-functions

Azure Synapse Analytics Database CI/CD using Azure Function

In this article, I will discuss an Azure Database CI/CD approach using Azure Premium Function and Jenkins pipeline. I will only explain the architecture and the approach I took to implement the Database CI/CD pipeline.

Problem Statement and Challenges

I was working on a project where I had to build a Database deployment pipeline using enterprise GitHub which is only accessible through the company’s internal network. Also, port 1433 was blocked from the internal network to the Azure Synapse public endpoint for security reasons. Hence the only option I had was to run my pipeline in an internal network so that I could access GitHub which I was using for my Database Deployment Source Control and send the SQL code to Azure Synapse using Azure function HTTP post as port 1433 was blocked.

#azure #devops #azure-synapse-analytics #azure-devops #azure-functions