Azure DevOps Server vs. Datadog

Azure DevOps is good to use if you are all-in on the Microsoft Azure stack. It's fully integrated across Azure so it is a point-and-click for most of what you will need to achieve. If you are new to Azure make sure you get some outside experience to help you otherwise it is very easy to overcomplicate things and go down the wrong track, or for you to manually create things that come out of the box.

Incentivized

If I want to see what customers are doing wrong in their sessions, we can do that easily. On the other hand, if we want to know the payload in the API calls, that is the area where Datadog can improve.

Incentivized

• Reporting Integration- Azure boards provides Kanban and other dashboard, their templates for easy management of project.
• Project Pipeline- easy integration and development of CI/CD pipelines, helped in testing, releasing project artifacts.
• Version Control- Integration with Git and code IDE made it easy to share, review our code, fix bugs and do testing.

Incentivized

• The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
• Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
• Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.

Incentivized

• Can add more build templates for specific technology requirements
• Can have more features in dashboards which can help dev teams stream line their tasks and priorities
• Can have raise alarm feature in case of any sort of failure in devops pipeline execution

Incentivized

• In my experience, .NET Tracing Agent caused severe and untraceable performance issues
• In my opinion, usage and billing structures were opaque and surprising
• In my experience, documentation was incomplete, contradicting or sometimes completely wrong, even for common infrastructure (AWS Fargate)
• I feel support was unhelpful at times, and bounced us back and forth to other teams
• In my opinion, multiple methods of sample rate control were ineffective, adding to excessive usage and cost

Incentivized

Because we are a Microsoft Gold Partner we utilize most of their software and we have so much invested in Team Foundation Server now it would take a catastrophic amount of time and resources to switch to a different product.

Incentivized

Its a one stop solution for most processes and does reduce cost overall. This does in turn help teams communicate in a much more efficient way, also RUM is a game changer for any quality product; we use RUM alot for debugging and reverse engineering issues. Reports and coverage has been a plus, it all has helped us a lot in our processes.

Incentivized

For standard users the interface is friendly. but if you are a manager some tools are a little confusing to use, like the query system that you always need to create from scratch. Templates should be more helpful for queries and for standard procedures that you need to duplicate PBIs over time. The search history of Work Items is a little painful to use.

Incentivized

There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.

Incentivized

I have not had to use the support for Azure DevOps Server. There have never been any issues where I was not able to figure it out or quickly resolve. Our Scrum Master has used support before though, and the service has always been prompt and clear with a customer-focus

Incentivized

The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

Incentivized

Do research beforehand and, if possible, do a trial run before implementing into production environment.

Incentivized

Documentation was difficult to work through, rollout was catastrophic (completely outage)

Incentivized

In my opinion, DevOps covers the development process end to end way better than Jira or GitHub. Both competitors are nice in their specific fields but DevOps provides a more comprehensive package in my opinion. It is still crazy to see that the whole suite can be used for free. The productivity increase we realized with DevOps is worth real money!

Incentivized

In terms of usability, I’ve found Datadog significantly more approachable and powerful compared to Elasticsearch, especially for day-to-day operational monitoring. Datadog offers a much more cohesive, user-friendly interface out of the box, with built-in support for metrics, logs, tracing, alerting, and dashboards—all tightly integrated. In contrast, Elasticsearch often felt barebones and required considerable setup and additional tooling (like Kibana or Logstash) to reach the same level of functionality.
While Elasticsearch is excellent for high-volume log ingestion and full-text search, it lacks the depth of features and real-time visualization capabilities that Datadog provides natively. The query language in Datadog is also quite usable and comparable for my needs—mainly filtering and aggregating logs and metrics—without needing to learn Elasticsearch's more complex DSL. Overall, Datadog saves our team time and effort, whereas Elasticsearch often felt like building a monitoring system from scratch. The all-in-one nature of Datadog, despite its complexity, is ultimately more efficient and scalable for our use case.

Incentivized

• It has streamlined the pipeline and project management for our agile effort.
• It has helped our agile team get organized since that is a new methodology being leveraged within the Enterprise.
• The calendar has improved visibility into different OOOs across the project team since we all come from different departments across the larger organization.

Incentivized

• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

Incentivized