Where the bottleneck usually hides
Manual approval gates that were fine at low volume become the binding constraint at higher volume, a test suite that was fast enough once but hasn't scaled with the codebase, or a shared staging environment that only one team can use at a time, are the usual suspects once deploy automation itself is no longer the limiting factor.
These bottlenecks are rarely visible from the deployment frequency metric alone — they show up in cycle time breakdowns, which most teams stop looking at once the automation work feels "done".
How to actually find and fix it
Instrumenting the pipeline to measure time spent at each stage — not just overall lead time — reveals exactly where the queue is building up, which is almost always a more useful signal than the aggregate deployment frequency number everyone's watching.
A plateau isn't a ceiling. It's a bottleneck that hasn't been measured yet.MNB DevOps Practice
Key actions
- Instrument the pipeline to measure time per stage, not just overall lead time
- Investigate manual approval gates as volume scales past their original design
- Check test suite scaling against current codebase size
- Treat a plateau as an unmeasured bottleneck, not a natural ceiling