Automated code deployment pipeline on Amazon
August 06, 2019

Automated code deployment pipeline on Amazon

Anonymous | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Overall Satisfaction with AWS CodePipeline

AWS CodePipeline is being used as a continuous integration/continuous deployment tool at my organization. It is used by specific teams that require builds within a CI/CD developer workflow. The business problems it addresses is the need for automated code deployment and testing pipeline that allows for a continuous flow of code from testing to staging to deployment.

Pros

  • Continuous integration
  • Continuous delivery
  • Automated release pipeline

Cons

  • Amazon exclusivity
  • Cleaner interface
  • Increased deployment speed
  • Reduced server side bugs
  • Increased transparency
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.
AWS Support is bar none and I have access to dedicated account managers on the business level so they can help me with any questions I have regarding their product. No complaints there at all because they have dedicated support engineers who can help me understand the product well.
AWS Codepipeline is proprietary to Amazon Web Services and works well when you're working with other AWS products. If you're using a different technology stack, then Codepipeline may not be the best tool and some open source/closed source tools available on the web may suffice.
AWS CodePipeline is well suited for a specific software engineering workflow. If there is a need to deploy code within a framework, then this is a great tool to automate the code deployments outward. The scenarios where it is less appropriate is in situations of internal tooling or other code that might not change as often or are tools running locally.

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