SaaS Observability Platform
Established a data platform for a monitoring vendor migrating to usage-based billing.
5B events/day
Data pipeline
4 engineers
Team size
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- Duration · 10 weeks (Discovery → MVP)
- Squad · Principal architect, product engineer, platform engineer
- Budget focus · Keep burn rate predictable for investor milestones
- Deliverables · Architecture deck, delivery roadmap, MVP app, runbooks
Problem
- •Customers demanded transparent usage telemetry, but existing ETL jobs were brittle.
- •The team lacked the DevOps capacity to productionise a new ingestion pipeline.
Approach
- •Introduced streaming ingestion with Kinesis and Lambda.
- •Built red/black deployment workflows with IaC guardrails.
- •Paired with in-house engineers to upskill them on observability and tracing.
Outcome
- •Unlocked real-time billing insights for GTM and customer success teams.
- •Stabilised ingestion SLAs and removed on-call noise.
- •Documented playbooks now onboard new engineers in under a week.
Delivery timeline
- Weeks 1–2 · Discovery — Placeholder copy describing founder workshops, user interviews, and AWS assessments.
- Weeks 3–5 · Design & planning — Replace with UX, architecture, and backlog definition highlights.
- Weeks 6–10 · Build & launch — Placeholder summary for MVP build, QA, observability, and investor prep.
Tech used
Gallery
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Testimonial
“They combine deep AWS expertise with a product mindset. We ship faster and sleep better.”
Calvin Ng | CTO, LumenOps
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