A disadvantage of only merging feature branches once ready is that the integration efforts (time needed, costs involved) rise exponentially. In other words, the longer you wait with integrating your feature branch, the harder and riskier it gets for a feature to get merged in the main branch.
And yes, you can regularly merge the main branch back in the feature branch, but that effort is identical to shipping code as often as possible (merging forward) and having a feature flag that is disabled in production. The overhead of coding the feature flag is definitely worth it, and will even allow business to do cool things like releasing features to a small set of testing customers.
In other words, the biggest perk of shipping disabled features that should not get underestimated, is that continuous shipping will give you continuous feedback on side effects and regressions. Knowledge that possibly would be harder to collect outside of a production environment.
The longer deployments of code to production gets postponed, the more likely that the engineer responsible of that code does not know the specifics about it anymore. And, that engineer even could have left the company already.
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A disadvantage of only merging feature branches once ready is that the integration efforts (time needed, costs involved) rise exponentially. In other words, the longer you wait with integrating your feature branch, the harder and riskier it gets for a feature to get merged in the main branch.
And yes, you can regularly merge the main branch back in the feature branch, but that effort is identical to shipping code as often as possible (merging forward) and having a feature flag that is disabled in production. The overhead of coding the feature flag is definitely worth it, and will even allow business to do cool things like releasing features to a small set of testing customers.
In other words, the biggest perk of shipping disabled features that should not get underestimated, is that continuous shipping will give you continuous feedback on side effects and regressions. Knowledge that possibly would be harder to collect outside of a production environment.
The longer deployments of code to production gets postponed, the more likely that the engineer responsible of that code does not know the specifics about it anymore. And, that engineer even could have left the company already.