B2B Platform Scale
A fast-growing B2B platform had outgrown the architecture that got it to its first wave of enterprise customers. Pages that once felt instant were now stalling under real-world load, the cloud bill was climbing faster than revenue, and every new feature took longer to ship than the last. We were brought in to make the platform fast, affordable, and extensible again, without pausing the roadmap or risking a big-bang rewrite.
The challenge
Growth had quietly turned a clean codebase into a tangle of slow paths and expensive workarounds. The most painful symptoms showed up exactly where they hurt most, in front of prospective enterprise customers evaluating the product.
- p95 latency was killing deals. Key dashboards took 4–8 seconds to load under load, and procurement teams noticed during evaluations.
- Cloud costs were scaling super-linearly. Over-provisioned instances and N+1 queries meant every new customer cost more than the last to serve.
- The codebase resisted change. Tightly coupled modules and missing test coverage made even small features slow and risky to ship.
- No shared visibility. Without tracing or meaningful metrics, the team was guessing at where time and money actually went.
Our approach
We avoided the temptation to rewrite from scratch. Instead, we instrumented first, fixed the highest-leverage bottlenecks with data behind every decision, and hardened the platform in stages so the product team could keep shipping the whole time.
- Measure before cutting. We added distributed tracing and a cost dashboard, then ranked bottlenecks by customer impact and dollars.
- Fix the hot paths. We rewrote the worst queries, added Redis caching with sane invalidation, and introduced read replicas for heavy reporting.
- Right-size the infrastructure. We moved to autoscaling on real utilization signals and codified everything in Terraform for repeatability.
- Refresh the design system. A componentized front end removed duplication and made new feature delivery dramatically faster.
- Add guardrails. Performance budgets and alerting now catch regressions before customers ever feel them.
How we worked
Two weeks to add observability and build a ranked, evidence-based bottleneck backlog.
Cache and query fixes on the hottest paths delivered visible latency drops in the first month.
Service boundaries, read replicas, and autoscaling tackled the deeper cost and scale issues.
Performance budgets, runbooks, and dashboards so the team owns it long after we leave.
Results
p95 on core dashboards dropped from 4–8 seconds to under 1.5. Infrastructure spend per customer fell by 40% even as traffic grew, and the platform now holds a 99.9% uptime SLA with monitored headroom. Just as importantly, the refreshed design system cut the time to ship a typical feature roughly in half.
"Appflare gave us enterprise-grade performance without the year-long rewrite we were dreading. They paid for themselves in cloud savings alone."VP of Engineering, B2B platform
Stack
Have a platform straining under growth?
We can do the same staged modernization for you, measuring first and fixing what actually moves the needle.