Monetization and OSS Model

Monetization and OSS Model

Flakemetry is OSS-first with an open-core commercial layer. The open-source product must be genuinely useful and self-hostable — monetization comes from operational cost and enterprise needs, never from crippling the core.

Open-core split

Layer	Licence	Contents
OSS core	MIT	Reporters, SDK, CLI, self-hosted platform, OTel ingestion, Test Identity Engine, **[[Flaky Scoring
Commercial / SaaS	proprietary	Hosted multi-tenant, managed AI RCA at scale, RBAC/SSO/SAML, long retention, team analytics, SLA/support

Principle: nothing in OSS is deliberately hobbled. Only operational cost (hosting, AI compute, enterprise auth, long retention) is monetized. A self-hoster gets the full product.

Why this works

• OSS drives adoption and brand. The reporter + docker compose up is the top of funnel; the "tests as traces" narrative is the differentiator (see Product Vision).
• Self-host is a feature, not a leak. Privacy-sensitive teams run fully local (Ollama RCA); that same audience later buys hosting for other repos.
• Cost-aligned pricing. The expensive things to run (ingestion volume, AI tokens, storage/retention) are exactly what a hosted plan charges for — incentives align.

Pricing shape (directional)

Tier	Who	Basis
OSS / Self-host	any team	free
Team (hosted)	5–50 eng	per-project + ingestion volume
Business	50–200 eng	+ SSO, longer retention, managed AI
Enterprise	200+	+ SAML, audit, SLA, support, private deploy

Metering (M5)

The open-core boundary is enforced by clean code separation (feature flags / a separate commercial package), and hosted usage is metered on real cost drivers:

• executions ingested
• artifacts stored (GB-days)
• LLM tokens spent on RCA

Billing sits behind an interface (Stripe as the first adapter). See the M5 milestone in Roadmap.

Portfolio / career angle

Even before any revenue, Flakemetry is a staff-level portfolio artifact: it demonstrates system design, an event-driven pipeline, a non-trivial domain algorithm (identity + scoring), pragmatic AI integration, and OSS product thinking — with ADRs and a public roadmap that show how decisions were made, not just the result.

Related: Product Vision · Roadmap.