GitLab vs. Optimizely Feature Experimentation

We started to use GitLab for hosting git source code repositories of our projects only but slowly we started to use it to store container images, packages, dependency proxy as well infrastucture registry and it is now well suited for Continuous Integration in our projects, It wasn't that good in Continuous Deployment before 12.0 version but after 12.0 it is amazingly good for Continuous Deployment as well since it keeps deployment information in a well organized manner which can be configure in ci yaml configuration.

Incentivized

I would use Optimizely Feature Experimentation when we would like to run basic experiments where metrics to be tracked are impressions, revenue or clicks. However, most of our experiments are tracking more complex metrics and this functionality is not enough. We still need to do work to analyse the data in our end.

Incentivized

• GitLab excels in managing code versions, allowing easy tracking of changes, branch management, and merging contributions.
• It helps maintain code stability and reliability, saving time and effort in the development or research workflow.
• Powerful code review features, enabling collaboration and feedback among team members.
• Robust project management features, including issue tracking, kanban boards, and milestones.

Incentivized

• Its ability to run A/B tests and multivariate experiments simultaneously allows us to identify the best-performing options quickly.
• Optimizely blends into our analytics tools, giving us immediate feedback on how our experiments are performing. This tool helps us avoid interruptions. With this pairing, we can arrive at informed decisions quickly.
• Additionally, feature toggles enable us to introduce new features or modifications to specific user groups, guaranteeing a smooth and controlled user experience. This tool helps us avoid interruptions.

Incentivized

• CI variables management is sometimes hard to use, for example, with File type variables. The scope of each variable is also hard to guess.
• Access Token: there are too many types (Personal, Project, global..), and it is hard to identify the scope and where it comes from once created.
• Runners: auto-scaled runners are for the moment hard to put in place, and monitoring is not easy.

Incentivized

• Splitting feature flags from actual experiments is slightly clunky and can be done either as part of the same page or better still you can create a flag on the spot while starting an experiment and not always needing to start with a flag.
• Recommending metrics to track based on description using AI

Incentivized

Gitlab is the best in its segment. They have a free version, they have open-source software, they provide a good service with their SaaS product, they are a fully-remote company since the beginning (which means they are fully distributed and have forward-thinking IMO). I would certainly recommend them to everyone.

Incentivized

I find it easy to use, I haven't had to do the integration work, so that's why it is a 9/10, cause I can't speak to how easy that part was or the initial set up, but day to day use is great!

Incentivized

All features that we used were pretty clear. They have a good documentation

Incentivized

At this point, I do not have much experience with Gitlab support as I have never had to engage them. They have documentation that is helpful, not quite as extensive as other documentation, but helpful nonetheless. They also seem to be relatively responsive on social media platforms (twitter) and really thrived when GitHub was acquired by Microsoft

Incentivized

It’s straightforward. Docs are well written and I believe there must be a support. But we haven’t used it

Incentivized

GitLab is easily the preferred tool when it comes to versioning and source control. With other tools the UI often feels outdated and clunky leading to inefficiency and confusion. With some of the sleeker tools such as GitKraken, while the aesthetic is pleasing, the experience is plagued by a lack of support, lack of optional plugins, and a plethora of bugs that cause unnecessary legwork to resolve. GitLab is the best of both aesthetic and functionality

Incentivized

Optimizely Feature Experimentation is better for building more complex experiments than Optimizely Web. However, Optimizely Web is much easier to kickstart your experimentation program with as the learning curve is much lower, and dedicated developer resources are not always necessary (marketers can build experiments quickly with Optimizely Web without developers' help).

Incentivized

had troubles with performance for SSR and the React SDK

Incentivized

• We were able to streamline our project's codebase which made us very organised and laid out a proper plan for development.
• Our deployment and infra pipelines are well structured now making our process 10x faster.
• We are more focused into project building rather infra, as infra is totally on autopilot mode. Which has enabled us to grow our ROI by records.

Incentivized

• Experimentation is key to figuring out the impact of changes made on-site.
• Experimentation is very helpful with pricing tests and other backend tests.
• Before running an experiment, many factors need to be evaluated, such as conflicting experiments, audience, user profile service, etc. This requires a considerable amount of time.

Incentivized