Use Case: Scale-Up - Progressive Rollout to Safeguard Infrastructure

Customer: E-commerce B2C Scale Up
Team Size: 50
Industry: B2C SaaS
Features Used: Progressive Rollouts

The problem

A fast-growing SaaS company (or scale-up) is adding new, potentially risky features or major architectural changes (e.g., a new data-intensive API endpoint, new microservice, or heavy-compute workflow). Because their user base is large and traffic is high, any bug, performance regression, or resource spike could severely impact infrastructure (latency, capacity, costs)..

Issues they are facing:

  • Rolling out a new feature to everyone could overload servers, cause performance degradation, or crash production.
  • If something breaks after deploy, rolling back via code is slow and risky (may require a fresh deploy).
  • They don’t want to slow down innovation - engineers need to deploy code quickly, but they also need safeguards.
  • Non-dev stakeholders (ops, SRE) want control: they want to monitor and limit exposure to risky features without blocking engineering velocity.

The solution

The team turned to FlagBox to simplify and speed-up their rollout process. After a quick integration, they started using FlagBox to:
  • Deploy the new feature behind a flag: the code is live in production, but only a subset of traffic sees it. This reduces risk.
  • Start with a tiny cohort (e.g. internal users / canary group) to test system behavior under production load.
  • Gradually increase the rollout (e.g. 5 % → 25 % → 50%) only if metrics remain stable.
  • If something goes wrong (e.g. bug, performance spike), flag can be turned off immediately - no need for a full redeploy. Flagbox enables that via dashboard.