Case Study: Scaling Reliability for a SaaS from 10 to 100 Customers in 9 Months
A tactical case study showing architecture, hiring, and observability decisions that scaled a SaaS product rapidly while maintaining stability and predictability.
Case Study: Scaling Reliability for a SaaS from 10 to 100 Customers in 9 Months
Hook: Rapid growth tests reliability practices. This case study explains the technical and organizational moves that preserved SLAs while scaling customer count tenfold.
Context
The company was a SaaS focused on B2B workflows. Growth went from 10 to 100 paying customers in nine months after a successful product-market fit period. Challenges included capacity planning, onboarding new accounts, and preserving incident MTTR.
Key decisions and why they worked
- From monolith to bounded services: Selective extraction of high-throughput paths followed the migration playbook in From Monolith to Microservices, reducing blast radius and enabling independent scaling.
- Invest in Type-safe SDKs: Adopting TypeScript-first libraries (see the TypeScript-first benchmark) reduced runtime errors in customer integrations and sped up onboarding.
- Automated document capture for onboarding and support: Using a document capture pattern to collect evidence during support escalations — inspired by the DocScan document-capture use cases — reduced repeated investigation time.
- Onboarding playbook and retention: Built a 30-day onboarding runbook modeled on remote onboarding principles from the Remote Onboarding Playbook, which cut churn from early-stage customers.
- Hiring and rotation: Implemented inclusive hiring and rotation practices based on the staffing playbook to prevent knowledge silos and improve resilience during growth.
Operational outcomes
- MTTR improved by 40% due to better telemetry and TypeScript-based contracts.
- Onboarding lead time decreased by 35% because of procedural templates and document capture artifacts.
- Churn fell 20% among newly onboarded customers thanks to improved readiness during the first 30 days.
Lessons for other teams
- Prioritise the paths that impact customers most and extract them first.
- Invest in type-safe contracts to avoid integration churn.
- Automate evidence capture for repetitive support flows — it saves time in postmortems and compliance.
- Formalise onboarding and make it measurable.
“Growth exposes the weakest operational assumptions — make those assumptions visible and measure them.”
Templates and links
- Migration playbook: mono-to-micro.
- Type safety benchmarks: TypeScript-first libraries.
- Document capture in operations: DocScan Cloud.
- Remote onboarding curriculum: Remote Onboarding Playbook.
- Inclusive hiring guidance: Staffing Playbook.
Closing
Scaling reliability requires both architecture and organisational playbooks. The fastest, safest growth came from a mix of targeted extraction, type-safe integrations, and disciplined onboarding backed by inclusive hiring.