When we began scaling our infrastructure at Bacancy, one question kept coming up. Should we continue investing in AWS or shift some of our DevOps workflows to Azure? Both platforms are strong, but they handle DevOps in very different ways. That difference becomes clear once you start building pipelines, managing infrastructure at scale, and trying to keep everything stable while still moving fast.

Here’s how we break it down, based on real projects and practical outcomes.

Top 8 Considerations for DevOps on AWS vs Azure

Here's a quick comparison of how AWS and Azure stack up for our DevOps teams.

1. DevOps Tooling: Flexibility or Structure?

AWS offers freedom. You get CodePipeline, CodeBuild, CodeDeploy, and more. But in most cases, you’ll still end up plugging in third-party tools like Jenkins, GitLab CI, or ArgoCD. Nothing wrong with that. It works. But it means more setup, more glue code, and more responsibility on your end to keep everything running.

Azure takes a different approach. Azure DevOps brings Repos, Boards, Pipelines, Test Plans, and Artifacts together in one stack. It’s tighter, more structured, and for teams already using Microsoft tools, it’s a smooth fit.

At Bacancy, developers onboard faster with Azure DevOps. It feels unified. Less context switching, fewer things to configure. If your team prefers a clear path over maximum customization, Azure saves time.

2. CI/CD Experience: Do You Want Full Control or Quick Delivery?

AWS gives you full control over your CI/CD pipelines. You can design fine-tuned workflows using Lambda triggers, Step Functions, or CloudFormation. The trade-off is time. These setups take longer to build and maintain. Most of the time, we also bring in GitHub Actions or Jenkins to fill the gaps.

Azure Pipelines is more streamlined. You can use YAML or the classic visual editor. It supports Linux, Windows, and macOS builds natively. It also integrates cleanly with GitHub, which makes life easier if you're already using it for source control.

We’ve used both. If your team needs flexibility and doesn’t mind complexity, AWS delivers. But if you're trying to ship features quickly without babysitting your pipeline, Azure wins.

3. Infrastructure as Code: AWS Leads, But Azure Is Catching Up

AWS has had a strong lead here for a while. CloudFormation is solid, and the AWS CDK gives developers a familiar programming interface. That’s helpful if your engineers prefer writing infrastructure in TypeScript or Python instead of JSON or YAML.

Azure offers ARM templates, which are powerful but heavy to work with. That’s where Bicep comes in. It’s a cleaner way to manage infrastructure on Azure, and we’ve seen growing adoption.

At Bacancy, we rely on Terraform across both clouds. It keeps our infrastructure code portable and consistent. We prefer tools that don’t tie us to one cloud unless absolutely necessary. Hire Terraform Developers if you also need help with cloud infrastructure management.

4. Monitoring and Observability: Who Makes It Easier?

CloudWatch on AWS is deep, but not friendly. You can do a lot with it, but you need to know what you're doing. We’ve often paired it with Grafana just to get better visibility.

Azure Monitor is more accessible out of the box. It works well with Application Insights and Log Analytics. You can see meaningful data faster, especially if you’re running .NET or Windows-based apps.

In our experience, Azure gets you to useful dashboards quicker. AWS has more capability, but you have to build more of it yourself.

5. Containers and Kubernetes: Both Are Good, But Usability Differs

Both clouds support containers and Kubernetes. AWS gives you ECS for simple setups and EKS for full Kubernetes clusters. ECS is easier, but EKS offers more control. That control comes with more setup effort.

Azure has AKS, which is simpler to manage. It ties in well with Azure CLI, the portal, and Azure DevOps. You can get a cluster running and deploying in less time.

We run both AKS and EKS at Bacancy. Teams looking for speed and simplicity tend to go with AKS. Teams that need more control stick with EKS. Both get the job done, it just depends on your priorities.

6. Security and Identity: Ease or Precision?

AWS IAM is powerful. You can build precise, least-privilege policies for just about anything. But the learning curve is steep, and mistakes can be costly.

Azure simplifies identity with Active Directory. If your organization already uses it, everything just connects. DevOps pipelines, resource permissions, and role management all fall into place faster.

From an enterprise standpoint, Azure often takes the edge here. It’s just easier to integrate identity across your environment if you're already in the Microsoft ecosystem.

7. Developer Experience: What Does It Feel Like to Build on Each?

AWS offers flexibility but can be overwhelming. You end up jumping between services, wiring things together, and relying heavily on documentation to troubleshoot.

Azure gives a smoother experience. Services talk to each other better, and there’s a clear path from writing code to deploying it. Azure DevOps plus AKS plus AAD all work together without too much friction.

Junior developers at Bacancy tend to get up to speed faster on Azure. With AWS, there’s a learning curve, but the trade-off is deeper control once you're comfortable.

8. Cost Considerations: Transparency vs Simplicity

AWS pricing is granular. That helps when you're trying to optimize spend at scale. You can tune almost every resource to match your workload.

Azure bundles more services together, which can be easier to manage but sometimes harder to break down when costs spike.

We use both. For highly optimized workloads or where we want control over every component, AWS works better. For managed services or projects where simplicity matters more than deep tuning, Azure ends up being more cost-effective.

Final Take: Which Cloud Platform Wins?

There’s no single answer when we compare DevOps on AWS vs Azure. Here’s how we think about it at Bacancy:

• Go with Azure if your team works in the Microsoft ecosystem, if you want integrated tools, and if your priority is speed and clarity.
• Choose AWS if your workloads need customization, if you already use their services heavily, or if you want full control over your DevOps process.

We use both. Azure runs our internal tools, quick prototypes, and projects where we want to move fast. AWS powers most of our production workloads and anything that needs fine-tuned infrastructure or deeper platform control.

If you’re deciding between the two, consider what your team already knows and what you actually need today. The best DevOps workflow is the one your team can understand, maintain, and build on without wasting time in setup and configuration. Reach out to our DevOps Consultants to help you make the right choice.