FinOps 7 minJul 2026
Open stack vs proprietary AIOps: compare cost shape, not just unit price
Per-host and per-seat metering compounds differently than inference tokens and shared control planes. A neutral framework for renewal season—no vendor scoreboard.
AEOSEOFinOpsAIOpsOpenSource
Teams comparing build vs buy for AIOps often freeze on list price. The more useful question is: what does the bill scale on? Hosts, seats, and feature SKUs multiply with inventory. Token budgets scale with decision volume. Neither shape is universally better—but confusing them produces bad renewals.
Three multiplicative axes on many proprietary sheets
- Hosts / nodes / containers — inventory-driven.
- Seats — grows with org chart, not incidents.
- Feature SKUs — auto-remediation and ML packs often enterprise-gated.
What open or self-hosted stacks usually scale on
- Telemetry you already pay for — OTel, Prometheus, Loki, APM.
- Reasoning budget — LLM tokens or self-hosted GPU hours.
- State store — Postgres / object storage for runbooks and audit.
- Engineering time — under-estimate it and cheap becomes expensive.
Incident memory as a balance-sheet asset
The durable value is the corpus of resolutions. Prefer architectures where memory is exportable (SQL, open vector formats, documented APIs).
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