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My main use case for Microsoft Azure DevOps is for a dedicated team that is building Copilot Studio agentic AI use cases. I assign tasks to my team members, such as creating Azure Boards, Azure Repositories, and Azure Pipelines, and assigning individual tasks to each team member while monitoring their progress through Microsoft Azure DevOps. My primary objective is to manage Copilot agent applications for our team members. I am also involved in website designing and development, so I coordinate with the design and development teams to maintain their tasks in Azure Boards.

Based on my experience with Microsoft Azure DevOps, I believe everything is good, but I occasionally experience some slowness. This does not occur on a daily basis, but there are times when it takes longer to load in a browser.

I maintain our daily basis tasks on Microsoft Azure DevOps using the main key features of the platform, including the end-to-end DevOps platform, monitoring of each individual's tasks on Azure Boards. It is a faster delivery method that improves collaboration and code quality while automating consistency. It supports main Agile development practices. Microsoft Azure DevOps offers multi-platform and multi-cloud support, though we primarily use Microsoft Azure due to our Microsoft partnership.

The best features Microsoft Azure DevOps offers include the ability to create Azure Boards where I can enter project planning and requirements. Microsoft Azure Repos allows me to manage source code, and Microsoft Azure Pipelines enable me to easily build and create CI/CD pipelines. I can define and write Microsoft Azure Test Plans and create Microsoft Azure Pipelines, also known as CI/CD deployment. Additionally, I can use Microsoft Azure Monitor and Application Insights to easily track resource utilization, time, and resource consumption, showing which resources have been utilized and for how many hours on a daily basis. In simple terms, Microsoft Azure DevOps helps any organization move ideas from development to production faster with greater automation, improved collaboration, quality governance, and a secure environment.

I find myself relying on Microsoft Azure Boards the most. Creating Azure Boards and user stories while managing and dividing tasks into different slots is something I use on a daily basis more than all other capabilities.

Regarding the features of Microsoft Azure DevOps, the team's performance and spending on particular tasks are mentioned in a storyboard, which is a great feature for reporting purposes. If I have 10 team members, Microsoft Azure DevOps shows a bar chart or pie chart, or I can view the report with Excel where I can trigger SQL queries and add conditions, such as how many tasks we have completed on a daily, weekly, or monthly basis, and whether each task is completed, done, to-do listed, or in progress. These features are ones I appreciate and use on a daily basis. Another feature I use is based on licensing plans, which can sometimes be costlier for small and medium organizations from my perspective. However, major enterprise-level organizations use Microsoft Azure DevOps.

Microsoft Azure DevOps saves a lot of time while monitoring tasks and assigning them to team members. I can easily monitor how many tasks take what amount of time. This would be helpful for internal organization teams and for working with customers or clients, as it easily helps manage how many resources and money we have spent on a dedicated project. It is really helpful for any organization adopting DevOps culture.

Since using Microsoft Azure DevOps, I can say that initially, we were managing tasks on Excel and sharing weekly plans with team members, maintaining hours manually. When we started using Microsoft Azure DevOps, it saved considerable time and showed every team member's productivity very transparently. Tasks have been divided on an hourly or two-hour basis, showing how long each task takes. It totally saved a lot more time. I cannot define an exact timeframe, but it definitely helped with assigning tasks compared to doing it manually on Excel. The storyboard provides a graphical representation that is very helpful when summarizing information for executive leadership teams or stakeholders.

I reduced my rating from a perfect score because of one concern. Microsoft Azure DevOps is very easy to use. If any person is new to the platform while creating user stories or repositories, it is a very efficient way for people to work. The platform does not require in-depth training. If someone provides a one to two hour description, people with some technical knowledge would understand it greatly. The platform is interesting for both fully technical and non-technical persons. People can use it easily and it is understandable. Anyone can create a user story or Microsoft Azure Board, generate reports using SQL queries while adding conditions, or monitor tasks. Any person with admin rights can see graphs showing which resources have spent how many hours on a daily, weekly, or monthly basis. Based on that information, we can measure resource performance, which would be really helpful for management or HR departments when increasing employee salaries, offering appreciation, or providing bonus activities in an organization.

Regarding governance and security within Microsoft Azure DevOps, there is strong security because Microsoft provides a secure and productive environment that follows all compliances. Everyone can trust Microsoft because it is a reputable brand in the market. People can rely on and trust any Microsoft product. I am not talking about Microsoft Azure DevOps only, but also CRM, Windows, security, and Entra ID. With any Microsoft product, there is no need to worry about security or compliance concerns. From a security and governance point of view, Microsoft Azure DevOps provides very strong capabilities.

I have been using Microsoft Azure DevOps for the last eight years to manage tasks, create user stories, and manage teams through graphical representations inside the DevOps platform. These features are what I use on Microsoft Azure DevOps.

I occasionally experience slowness with Microsoft Azure DevOps, though not very slow. The speed could be faster, which has been my main concern throughout my eight years of using the platform.

Regarding Microsoft Azure DevOps's scalability, it depends on your usage and the number of team members you have. You can scale according to your needs. From a scalability point of view, it is really helpful, and I can say it is a scalable platform.

We have communicated with the Microsoft Azure DevOps team, but we rarely need to contact the support team. When I have raised tickets, they have been resolved within 24 hours SLA, mainly. Sometimes I reside in India and the ticket assignee is in the United States, so they schedule collaboration or contact requirements according to the appropriate time zone. The support process is smooth with no issues.

I would rate customer support for Microsoft Azure DevOps at 8 or 8.5 out of 10 because we cannot connect directly with Microsoft Azure DevOps or the support team on the spot. There is a process that anyone needs to follow: drop an email to the support team and they will reply. Suppose I am in a hurry and stuck somewhere, then a phone call would be helpful. However, I do not have a direct number to call and connect to the support team immediately, which is not possible. Microsoft does not provide that kind of immediate support.

I have not used any DevOps platform before using Microsoft Azure DevOps. I have some knowledge of Jira, which also follows Agile terminologies, but I am not much more familiar with it.

I did not evaluate other options for Microsoft Azure DevOps. There are many tools in the market used for project management such as Trello and Jira, but Microsoft Azure DevOps has a standard, and we are in the Microsoft ecosystem. That is why I prefer to use Microsoft Azure DevOps because on a single platform, there is a complete cycle starting from Microsoft Azure DevOps to Microsoft Azure Artifacts, Microsoft Azure testing, creating CI/CD pipelines, and Microsoft Azure Test Plans. Everything is on a single platform. That is why Microsoft Azure DevOps is a complete solution for any organization dealing in software development or IT solutions. From my experience, it would be really helpful for anyone as a complete platform, and there is no need to go to any other solution.

Microsoft Azure DevOps is very easy to use. If any person is new to the platform while creating user stories or repositories, it is a very efficient way for people to use it without needing in-depth training. If someone provides a one to two hour overview, people with some technical knowledge would understand it greatly. The platform is interesting and suitable for both fully technical and non-technical persons. People can use it easily and it is understandable. Anyone can create a user story or Microsoft Azure Board, generate reports using SQL queries while adding conditions, or monitor tasks. Any person with admin rights can see graphs showing which resources have spent how many hours on a daily, weekly, or monthly basis, allowing us to measure resource performance. This information would be really helpful for management or HR departments when increasing employee salaries, offering appreciation, or providing bonus activities in an organization.

It is a difficult question for me because I cannot state the exact amount of time and money saved for us. However, Microsoft Azure DevOps definitely saves a lot of time and resources as well as money for any company, including mine. It is helpful while using Microsoft Azure DevOps for my company. Additionally, it is reputable if we are maintaining projects on Microsoft Azure DevOps. If a reputed company approaches us for their services or product requirements and they learn that we are maintaining Microsoft Azure DevOps, it would be very helpful to convert our customers into real revenue generation and business growth.

I am not much involved in the pricing, licensing, or costing aspects. However, one of my colleagues is involved in the licensing and pricing part, and it is very efficient. We are Microsoft Gold Partners, so we directly reach out to Microsoft resellers or partners to enhance our licenses if required.

I would definitely suggest using Microsoft Azure DevOps. Microsoft Azure DevOps is a scalable platform and a complete solution for any IT or software development company. People can rely on Microsoft Azure DevOps as a platform or tool that every company should follow. I cannot commit that every company follows Microsoft Azure DevOps, but definitely if a company has any reputation, they can use Microsoft Azure DevOps and maintain their code as well as maintain their storyboard, create sprints, easily monitor tasks, resource utilization, and reporting and analytics features. My overall rating for Microsoft Azure DevOps is 9 out of 10.

My main use case for Digital.ai Release is to take the headache out of coordinating software releases. In our environment, a release isn't just a developer pushing code to production. We usually follow several steps, including testing, security checks, approvals, and post-release verification. I use Digital.ai Release to define that process into a workflow. For example, once our development team finishes a build, it can move into testing. If tests pass, we can trigger the next step and get required approval and then proceed with deployment. I use Digital.ai Release to automate all this process.

The benefit for me about Digital.ai Release since we started using it is consistency because once we have a clear release process that works, we can turn it into a reusable template. Instead of rebuilding this process every time, we use a template we have used. This will reduce the amount of manual coordination and makes the releases more predictable.

Using reusable templates has changed my team's workflow and efficiency because once we have a release process that works, we don't have to rebuild it every time. We can create a template and reuse it for future releases, which gives us consistency and reduces the chance of someone forgetting an important step.

The best features Digital.ai Release offers include release orchestration because I can put the whole release process into one workflow instead of coordinating every step manually. These steps include development, testing, approvals, deployment, and all the validations. Reusable release templates are also one of my best features because I do not have to rebuild the process every time. I appreciate the number of tools it can connect with because you can bring together tools such as Jira, ServiceNow, Kubernetes, and cloud platforms into Digital.ai Release. Approval gates are also on my list because this is good for us since we are in a controlled environment. If a production deployment requires security or we have to get a business approval, then the workflow can stop until that approval is given.

Digital.ai Release has positively impacted my organization because it is the biggest change. It makes our release process less dependent on people. Before we started using it, a lot of time would disappear into coordination, checking whether testing is finished, waiting for approvals, and other administrative tasks. Digital.ai Release gives us a structured workflow. Much of that coordination happens automatically. The biggest impact I have also seen is more predictable releases. We can predict what will come out, what will fail, and what will succeed because of these reusable templates.

I cannot give realistic numbers, but I think for manual release work, we have reduced around 40% since we started using it. We have completely reduced failed deployments; since we started using it, so far six months now, we haven't had any failed deployment because we can predict what will happen. We have seen a release frequency of around 18 releases per month.

The first area I would see improved for Digital.ai Release is user experience. The platform is very powerful, but some workflows are complicated to configure, especially if customer support is not responsive. I would also like to see improved troubleshooting. In case a release fails, I want the platform to immediately tell me what went wrong, which step caused it, and what I should do next.

There is also room for improvement in integrations because it does not configure with newer DevOps tools.

I have been using Digital.ai Release for seven months.

Digital.ai Release is stable in my experience because generally it has been good. We run our release workflows consistently without the platform becoming a bottleneck for us.

I would rate the scalability of Digital.ai Release a 9 out of 10 because it is well-designed to handle enterprise release orchestration, and it supports deployments on Kubernetes, Docker, JVM-based environments, and other configurations. From my experience, it is scalable.

Regarding customer support, a few times I have interacted with it, it has been good because it is not limited to simply replying to a ticket. It provides a good support portal, an AI chatbot, documentation, and community resources. I have several ways to get help.

We did not previously use a different solution.

My experience with pricing, setup cost, and licensing for Digital.ai Release is that it is a little bit difficult to estimate. It has plans such as Pro, Premium, and Essentials. However, sometimes it depends on the integrations you are using, the automations you are using, and also if you want to consider the licensing setup cost which we incurred, and ongoing maintenance, which requires a cost. Thus, I cannot give a clear figure, but Digital.ai Release is not cheap.

We have seen less manual coordination effort, down around 50%. The release-related administration work that could take us a lot of hours now we can do in a few hours or a few days. About failed releases, I think we have had none since we started using it. I would approximate rollback has improved around 25%.

Before choosing Digital.ai Release, we evaluated other options, including GitLab and Octopus Deploy. I looked particularly at Digital.ai Release, especially its release orchestration and how it gives you reusable templates. In the end, we decided to go with Digital.ai Release.

I would not add anything else about the features.

I rate Digital.ai Release an 8 out of 10.

I chose 8 out of 10 because there is still a gap in the user experience. The platform is too powerful, and these workflows are complicated to configure. However, it is generally good because since we started using it, we have seen a noticeable change in our releases.

My advice to others looking into using Digital.ai Release is to pay close attention to your integration and permissions, especially before you make a decision whether to integrate. Also, check that the tools you are already using can connect properly with Digital.ai Release. Make sure you put across access controls for better governance and audits, and also determine your return on investment metrics before purchasing. Track the release cycle time and the deployment frequency. You can do that by scheduling a demo with the sales support of Digital.ai Release.

I found this interview good and have no suggestions for change in the future.