AWS CodePipeline vs. Azure Pipelines

I think AWS CodePipeline is a great tool for anyone wanted automated deployments in a multi-server/container AWS environment. AWS also offers services like Elastic Beanstalk that provide a more managed hosting & deployment experience. CodePipeline is a good middle ground with solid, built-in automation with enough customizability to not lock people into one deployment or architecture philosophy.

Incentivized

With a fully Microsoft Azure based workflow - Azure Pipelines makes absolute sense. Azure Pipelines are robust and work very well with SonarQube for test coverage and are shared with our developers. This prevents the developers for pushing code without unit tests across our backend and frontend platforms. We have reduced our instances of manual regression tests especially when there are multiple teams working across the same repositories.

Incentivized

• It is reliable and works without errors
• It integrates well with our repository and all other AWS functions as well as our end database

Incentivized

• all in one place
• good ability to personalize deployment process
• easy to develop

Incentivized

• Ease of use - things like CircleCI or other tools are a bit easier to learn.
• Ability to build from more sources.

Incentivized

• Error messaging when team members don't have permissions

Incentivized

Overall, I give AWS Codepipeline a 9 because it gets the job done and I can't complain much about the web interface as much of the action is taking place behind the scenes on the terminal locally or via Amazon's infrastructure anyway. It would be nicer to have a better flowing and visualizable web interface, however.

Incentivized

Our pipeline takes about 30 minutes to run through. Although this time depends on the applications you are using on either end, I feel that it is a reasonable time to make upgrades and updates to our system as it is not an every day push.

Incentivized

We didn't need a lot of support with AWS CodePipeline as it was pretty straightforward to configure and use, but where we ran into problems, the AWS community was able to help. AWS support agents were also helpful in resolving some of the minor issues we encountered, which we could not find a solution elsewhere.

Incentivized

CodeCommit and CodeDeploy can be used with CodePipeline so it’s not really fair to stack them against each other as they can be quite the compliment. The same goes for Beanstalk, which is often used as a deployment target in relation to CodePipeline.

CodePipeline fulfills the CI/CD duty, where the other services do not focus on that specific function. They are supplements, not replacements. CodePipeline will detect the updated code and handle deploying it to the actual instance via Beanstalk.

Jenkins is open source and not a native AWS service, that is its primary differentiator. Jenkins can also be used as a supplement to CodePipeline.

Incentivized

The tools are very similar - but Azure Pipelines work best for Azure-based products are better suited for the stack. For our engineers, we could switch between all the various continuous integration/deployment tools without much issues, but it makes sense to use the stack recommended by Azure. Our team has the relevant support licences to get support from Microsoft for all our products.

Incentivized

• CodePipeline has reduced ongoing devops costs for my clients, especially around deployment & testing.
• CodePipeline has sped up development workflow by making the deployment process automated off git pushes. Deployment takes very little coordination as the system will just trigger based on what is the latest commit in a branch.
• CodePipeline offered a lot of out-of-the-box functionality that was much simpler to setup than a dedicated CI server. It allowed the deployment process to built and put into production with much less and effort and cost compared to rolling the functionality manually.

Incentivized

• We don't have to deploy changes manually
• But because of this that we automated some tasks, we need to be still aware of some edge cases we can meet and which can cause a pipelines failures
• We can deploy changes pretty fast

Incentivized