Azure DevOps vs AWS DevOps: What Each Does, and How to Do It in the Other

Two of the most common ways to run CI/CD in production are Microsoft's Azure DevOps and Amazon's family of DevOps services, loosely called "AWS DevOps." They are routinely compared as if they were the same kind of thing. They are not — and understanding why is the first and most useful thing to establish before you standardise a team on either.

Azure DevOps is a single, integrated product. One service, one login, one permissions model, covering the whole software lifecycle: planning, source control, build, release, packages and test.

"AWS DevOps" is not a product at all. It is a set of separate, composable services — CodePipeline, CodeBuild, CodeDeploy, CodeArtifact — that you assemble yourself, alongside the rest of AWS (IAM, CloudFormation/CDK, CloudWatch). AWS's attempt at a single integrated equivalent, CodeCatalyst, is now closing to new customers, and its hosted Git service, CodeCommit, has been frozen since 2024. On AWS today, the realistic assumption is that your source control lives in GitHub or GitLab and you wire the rest together.

The fundamental difference: a suite vs a toolbox

Azure DevOps is opinionated. You get Boards, Repos, Pipelines, Artifacts and Test Plans out of the box, sharing one identity model, one set of permissions and one project structure. A work item links to a commit links to a build links to a release with no integration work on your part. For a team that wants an end-to-end lifecycle without assembling it, that is the whole value.

AWS is the opposite by design. Each Code* service does one job and expects you to compose it with the others and with IAM. That composability is powerful — you can build exactly the pipeline you want, deeply integrated with the rest of AWS — but nothing is joined up until you join it, and the identity and permissions wiring (an IAM role per service, per stage) is real work. AWS also increasingly assumes that the parts it no longer invests in — source control and issue tracking — live in GitHub.

Capability by capability

The quickest way to see the difference is to line up what each gives you for the same job.

Capability	Azure DevOps	AWS
Work tracking / planning	Azure Boards (native, mature)	No native service — bolt on Jira or GitHub Projects
Source control (Git)	Azure Repos	CodeCommit — frozen to new customers → use GitHub / GitLab
Build (CI)	Azure Pipelines (YAML)	CodeBuild
Release / deploy (CD)	Azure Pipelines — environments, approvals, gates	CodePipeline (orchestration) + CodeDeploy (to ECS, EC2, Lambda)
Package / artifact feeds	Azure Artifacts	CodeArtifact
Test management	Azure Test Plans (native)	No native service — third-party
Infrastructure as Code	ARM / Bicep (+ Terraform)	CloudFormation / CDK (+ Terraform)
Secrets	Azure Key Vault	Secrets Manager / SSM Parameter Store
Monitoring	Azure Monitor + Application Insights	CloudWatch + X-Ray
One integrated product?	Yes	Only via CodeCatalyst — now closed to new customers

The source-control catch on AWS

This is the single most important current fact, and it catches teams starting fresh on AWS. CodeCommit stopped onboarding new customers on 25 July 2024: if your account has never created a CodeCommit repository, you cannot start one now. AWS's own guidance points to GitHub, GitLab or Bitbucket. And CodeCatalyst — Amazon's integrated, Azure-DevOps-like offering — closes to new customers on 7 November 2025 and is in maintenance mode, receiving only security and availability fixes.

The practical consequence: a new "AWS DevOps" stack today is really GitHub (repositories, and often GitHub Actions) plus AWS CodeBuild / CodePipeline / CodeDeploy for deployment — or Terraform driving everything. Azure DevOps, by contrast, still ships its own first-class Git in Azure Repos.

CI/CD: one pipeline vs three services

In Azure DevOps, build and release are one thing. A single azure-pipelines.yml defines the stages, and environments carry approvals, gates and deployment history. Want a manual approval before production, with an audit trail? A few lines of YAML and a check on the environment.

In AWS, the same outcome is assembled: CodeBuild runs the build, CodePipeline orchestrates the stages and manual-approval actions, and CodeDeploy performs the rollout — including AWS-native blue/green and canary deployments to ECS, Lambda and EC2 that are genuinely first-class here. More moving parts, but tighter integration with AWS deploy targets.

How to do the same job in each

A few concrete tasks, both ways:

• Build on every push. Azure DevOps: a trigger in azure-pipelines.yml. AWS: a webhook or EventBridge rule starts CodePipeline (or CodeBuild directly), with the source stage pointed at GitHub.
• Gated production deploy with approval. Azure DevOps: an environment with an approval check. AWS: a manual-approval action in CodePipeline ahead of the CodeDeploy stage.
• Store and share build artifacts. Azure DevOps: an Azure Artifacts feed (NuGet, npm, Maven, Python). AWS: a CodeArtifact repository.
• Track the work against the code. Azure DevOps: Azure Boards, linked to commits and builds automatically. AWS: no native answer — Jira or GitHub Projects, integrated by hand.

Which to choose

• Choose Azure DevOps when you want one integrated lifecycle — planning, source, CI/CD, packages and test — with the least assembly, strong approvals and audit, and first-class multi-cloud and hybrid deployment (its hosted and self-hosted agents deploy anywhere, not only to Azure). It is also the pragmatic choice for Microsoft-stack and enterprise teams that value Boards and Test Plans.
• Choose the AWS Code* services when your deployment target is AWS and you want CI/CD sitting inside the same account, IAM and network as everything else — blue/green to ECS or Lambda, tight CloudFormation/CDK integration — and you are comfortable bringing your own source control (GitHub) and issue tracking.
• Increasingly, the honest third option is GitHub Actions with either cloud as the deploy target. Both Microsoft and AWS are steering there, and it avoids betting on a first-party service that might be frozen next.

The deeper point for anyone standardising a team: Azure DevOps is a decision you make once and get a whole lifecycle from; an AWS DevOps stack is a set of decisions you keep making, service by service — and two of the services you might have reached for first are no longer open to you.

Sources: AWS — CodeCommit closed to new customers on 25 July 2024, and Amazon CodeCatalyst closing to new customers on 7 November 2025 (AWS service announcements and documentation); AWS CodePipeline, CodeBuild, CodeDeploy and CodeArtifact product documentation; Microsoft Learn — Azure DevOps services (Boards, Repos, Pipelines, Artifacts, Test Plans) and 2025 release notes. Service availability and terms change; verify against the vendors' current documentation before standardising a team.