AWS CodePipeline vs. BMC AMI DevX

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

It's pretty good at creating an extract of a whole table, but not the best at grabbing all related tables in my experience. Pretty intuitive on setting up your test data categories. I also really like that it can either run via ISPF or via Topaz which was included with our purchase.

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

• Extract/load data from one DB or table to another masking the data for testing.
• Compare extracts against each other to ensure good baselines.

Incentivized

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

Incentivized

• I find it more obtuse to use than IBM Optim.
• Related tables are difficult to incorporate.

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

Support has been amazing compared to Optim. Further, new features are very regular with File-AID - I can't remember the last time Optim had a significant update. File-AID support is very receptive to feature requests and reported bugs, including sending out hotfixes quickly.

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

Optim is more user friendly in how it operates, in my opinion. It's less obtuse to figure out how to extract and mask the data required compared to File-AID. Further, Optim is easier to gather related tables, by far. I do prefer using File-AID via the Topaz GUI much more than using Optim via its GUI. Finally, I personally believe that File-AID is significantly faster to run than Optim - this could be a configuration issue.

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

• Saves time creating production like data for testing.
• Keeps that data safe from developers and need-to-know only.

Incentivized