Azure DevOps Stages, Jobs & Steps
#azure #devops #jobs
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.
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
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.
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.
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
#azure-devops #microsoft #azure #github #azure devops #azure devops and github
In last week’s post, we covered taking our existing build pipeline and making it a multi-stage Pipeline with a build stage and a deploy stage. This week we are going to add another stage to our pipeline for production. Since we don’t want the production stage deployed before it has been through QA we will need to hold the stage until it is verified ready, which is what this post is going to be about. If you haven’t read last week’s post, Azure DevOps Pipelines: Multi-Stage Pipelines, you might want to start there before reading the rest of this post if you are new to multi-stage pipelines.
In order to require approval on a stage is to associate it with and environment and add the approval requirement to the environment. In Azure DevOps under Pipelines select Environments and then click the Create environment button.
On the New environment dialog fill in a Name. If you had actual resources associated with the environment they can be added to provide traceability, but in this example, we are going to stick with the None option.
Now that the resource has been created on its details page we can use the three dots to open the menu and click Approvals and checks.
On the next screen click the **+**button in the upper right corner and then from the lists of check select Approvals and then click Next. As you can see from the partial list in the screenshot the range of check available for approvals is massive.
#azure-devops #azure #azure-pipelines #devops
As part of my personal development, I’ve created a personal health platform that uses various different microservices (Built using Azure Functions) that extract data from my Fitbit account and store them in an Azure Cosmos DB database. I have other microservices that pass messages between different services via Azure Service Bus.
For this project, I use Azure DevOps to build my artifacts, run my unit tests and deploy my microservices to Azure. The great thing about DevOps is that we can do all of this within the YAML pipeline.
Yes I said YAML. Honestly, I don’t know what the fuss is all about 😂
In a previous post, I talked about how we can deploy NuGet packages to a private feed in Azure Artifacts using YAML pipelines. If you haven’t read that post yet, you can check it out below!
In this article, we will turn our attention to building and deploying C## Azure Functions using a single build file.
We’ve got quite a bit to cover, so I’ll break down my YAML file and talk about each stage in the following order:
#azure #azure-devops #azure-functions #dotnet #devops #c#
Azure DevOps Stages, Jobs & Steps
#azure #devops #jobs