Share your experience using Plutora

Regarding my use cases, I am cautious about breaking customers in production, so I generally put LaunchDarkly flags on pretty much any feature that is going to be rolled out to production to slowly roll things out and ensure nothing is broken. Additionally, it is valuable for developing a new feature and then launching it all at once when it is ready to go, so I do both of those.

I am not using LaunchDarkly to manage any AI in production, as other teams may be doing that. At the moment, my use of AI is limited to coding assistance, while other teams are integrating AI into the product.

What I appreciate most about LaunchDarkly is that it is very easy to use. I estimate I have around 30 flags, though I have not counted them recently. Finding the flags is straightforward; I search for the flag I need and then proceed with the setup for whatever I need to do. One useful aspect for my workflow is that whenever I set a flag or change something, I ask my coding LLM to confirm that everything is working as it should, whether it is to catch a typo or ensure I did not add the wrong merchant ID.

What I dislike about LaunchDarkly is the inability to quickly find all the flags I have currently running and their statuses. I want to know if they are rolled out partially, but I have to check externally by asking my coding agent about all my LaunchDarkly flags and their statuses. Recently, I forgot about a flag I rolled out to a couple of merchants, and I noticed I was not alone; several people had flags running for months with only one or two merchants enabled. A feature to alert me if a flag is underutilized or needs attention after a week of being rolled out would be beneficial.

Overall, I have been working with LaunchDarkly for a couple of years, having used it at Instacart and currently at Thanks, but it was not utilized at Thomson Reuters. I have a couple of years of experience with it.

I have not encountered any scalability issues with LaunchDarkly. I work for a mid-sized company with hundreds or thousands of users, and I have not run into scalability issues here. While my experience at Instacart might have been different, I was not using it as in-depth as I do now. I currently use LaunchDarkly on a daily basis.

I have not integrated any other tools with LaunchDarkly; it stands by itself in my usage.

Other than the server that checks the status whenever I request it, which saves me from going directly to LaunchDarkly, I do not have additional tools integrated.

I would give LaunchDarkly a rating of nine out of ten because I never give out tens, as that implies no room for improvement, and everybody can improve. Overall, LaunchDarkly is good; it is easy to use, and I can see what is happening relatively quickly.

My basic use case for Gitlab was the ticket management, the wiki, the CI/CD pipeline, and the code repository. These four use cases form my core usage.

Gitlab is a developer tool, and it was easy to use. I never had to go to Jira or any project or product management tool. The wiki was there, so the onboarding of my developer was super fast.

Having everything in a single place in GitLab means I do not have to go to any other tool while I am working on GitLab. That was the major advantage.

The ticket management was the part that I was using in GitLab.

Since I was a solo developer, I never used Integrated Code Review in GitLab extensively. However, for teams, it is really useful.

Integrated Code Review is definitely an important feature in GitLab because as soon as the code is committed in a branch, the deployment is a major aspect. Making sure that the build is working fine, testing it, and having it deployed is critical, and GitLab provides a good feature in that area.

I have not heavily used the security scanning part of GitLab.

The ticket management and wiki part I mentioned earlier was what I was using with one of my team members in GitLab.

Since GitLab [Private Offer Only] the main part is the Git part. With AI being available, I see one thing happening. For example, Claude Code allows people to connect Jira or ClickUp, and then they connect GitHub to get the work done. If you can bring in a feature of the AI that can help do the project management and the code commits in a single MCP since the project management is in GitLab [Private Offer Only] and the code is in GitLab [Private Offer Only], that would help get rid of Jira and all these things. This will have two benefits. One, the onboarding will be easy. The second thing is people will not have to pay an additional amount for Jira or ClickUp.

I was using GitLab for my personal project for the last five years, not for professional projects.

I never had any issue with GitLab. For me, it is stable.

For me, GitLab was a scalable solution.

I never had any problem and never had to reach out to the support of GitLab.

I have used the cloud version of GitLab. I have not tried the self-hosted version, so I cannot comment on that.

I never got a requirement to have a self-deployed GitLab instance.

Developer time is important. If you save time in the development with GitLab, that is a value of money. If things are getting done faster, then that is a good ROI.

It varies team by team, but based on my experience, GitLab saved my time between 10% to 15%.

I was using the free version of GitLab , but I think the price is comparative and not a major differentiator.

When I started using GitLab, I wanted a combo of the features. There was ticket management, there was the wiki, and there was a CI/CD pipeline, everything was there. GitLab was the first to provide all these things, and later on, GitHub has taken all these things, but GitHub is a follower. GitLab is the pioneer of these things. That is why I started taking it and that was the main motivating factor for me.

GitLab is on its own cloud.

I have purchased security products from AWS Marketplace, but that is not related to GitLab. It is AWS, and I used Kaspersky for my servers when I was doing PCI DSS for one of my companies.

I rate GitLab an eight out of ten.