How to survive 100x scaling events: Picking the right technologies early
summary
Noteable experiences ~100x traffic growth after a ChatGPT plugin launch and keeps service online with minimal rearchitecture by using CockroachDB, Kubernetes, Datadog and FastAPI plus a strong integration-test suite and load-testing ramp. The app serves multi-tenant notebook kernels so write-heavy spikes trigger database bottlenecks; teams ship same-day hot fixes, add missing indexes, and scale Cockroach by one node while tripling other services, keeping costs sublinear and the product functional.
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chapters (11)
- 0:00Welcome/Introduction
- 1:19What does Noteable do?
- 2:13The impact of LLMs and Chat plugins launching on Noteable
- 4:36How Noteable futureproofed their tech stack
- 5:27How to design a scaling response playbook
- 8:04How to choose technology that can scale
- 10:45How does CockroachDB prevent failure?
- 13:03Why did Noteable choose Datadog?
- 13:45Why did Noteable choose Kubernetes?
- 14:52Why did Noteable choose FastAPI?
- 15:39Scaling learnings
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