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Multi-tenant SaaS Checklist - Identity, Billing & Observability Aligned

One platform, many tenants. This checklist helps you architect multi-tenant SaaS with clear boundaries, billing accuracy, and security controls that pass audits-all while supporting AI workloads like RAG and MCP servers.

Go deeper

Pair this checklist with the Multi-Tenant SaaS Architecture guide , the AI Platform Security Guide , and the RAG Architecture Guide so you have the architecture and retrieval guardrails that make these checks real.

Identity & access

  • Org/tenant model defined (Clerk orgs, custom tables) with invite + provisioning flows.
  • Role catalog (admin, analyst, billing, support) mapped to RBAC policies and UI states.
  • SSO/SAML requirements documented (Okta, Azure AD) with SCIM lifecycle support.
  • Session management (device management, session revocation, session duration) enforced per role.
  • Audit logging for logins, role changes, SCIM events, MFA setup, API tokens.

Data model & isolation

  • Tenant-aware schemas (per-tenant DB vs shared + RLS) justified with scaling plan.
  • Row Level Security, policies, and fallback checks for every table and background job.
  • Cache strategy for per-tenant data (Redis key namespacing, TTLs, invalidation).
  • Storage isolation for uploads, logs, vector stores (bucket per tenant or prefix policy).
  • Metadata + lineage capturing who created/edited resources and what tenant they belong to.

Billing & monetization

  • Usage model defined (seats, tokens, workflows, storage) with measurement events.
  • Stripe/Chargebee plans mapped to tenant tiers plus proration and overage logic.
  • Self-serve + sales-assisted flows for upgrades, downgrades, cancellations.
  • Invoice exports, revenue recognition hooks, and finance reporting outputs.
  • Access control tied to billing state (grace periods, delinquency handling).

Observability & support

  • Tenant-specific dashboards (latency, error rates, AI usage, billing metrics).
  • Alerting routed to correct on-call based on tenant priority/SLA.
  • Support tooling integrated with tenant metadata (Zendesk, Intercom, custom panels).
  • Runbooks for tenant migrations, data exports, deletion, and compliance requests.
  • Feature flag strategy per tenant tier with testing protocols.

Security & incident response

  • Penetration testing scope includes tenant escalation and context leakage.
  • Secrets/key rotation automated per environment and tenant-specific integrations.
  • Incident response playbooks with tenant communication templates.
  • Backup/restore drills across databases, vector stores, and file storage.
  • Compliance evidence (threat models, data flow diagrams, audit logs) maintained.

Deployment & cost management

  • CI/CD gating (tests, lint, security scans, seed tenants) before each deploy.
  • Environment parity strategy plus smoke tests for priority tenants.
  • Infrastructure cost dashboards per tenant/tier with alert thresholds.
  • Scalability plan (horizontal sharding, read replicas, queue scaling) triggered by KPIs.
  • Vendor contract tracking (LLM, vector DB, auth, billing) with renewal reminders.

AI workload specifics

  • RAG retrieval filters enforced before similarity search; tenant assertions in API + runtime.
  • Vector namespaces per tenant or strict metadata filters; delete/re-embed workflow defined.
  • Agent/MCP tool registry with per-tenant permissions, rate limits, and audit logs.
  • Adversarial prompt and poisoning tests included in CI; regression thresholds block deploys.
  • Cost budgets per tenant/feature (tokens, embeddings, rerankers) with alerts and caps.

Rollout & lifecycle

  • Tenant onboarding checklist: org creation, SCIM/SSO, billing activation, data import.
  • Migration/runbook for moving tenants between tiers or shards with minimal downtime.
  • Data export/deletion flow (Right to be Forgotten) verified per tenant.
  • Support escalation paths by tier/SLA; comms templates for incidents and maintenance.
  • Periodic reviews: RLS assertions, cache policies, vector hygiene, and billing accuracy.

Related resources

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FAQ

Why this checklist?

Multi-tenant AI platforms fail audits when tenant isolation, billing, and logging are rushed. This guide keeps the fundamentals in sync.

FAQ

Is it specific to AI platforms?

Yes-examples assume AI workloads (RAG, agents) but the controls apply to any SaaS that needs strict tenant boundaries.

FAQ

How do I get the editable version?

Enter your email in the form below for the PDF/Notion template with scoring columns and owner assignments.