How to Evaluate Authorization Infrastructure: A Buyer's Checklist
Choosing authorization infrastructure is one of the most consequential technical decisions your organization will make this year. Unlike a logging pipeline or a feature flag service, authorization sits directly in the hot path of every request. It touches every API endpoint, every microservice boundary, every user-facing permission check. The wrong choice doesn’t just cost you money — it locks you into an architecture that shapes (and constrains) every system you build on top of it for years.
Most evaluation processes focus on feature checklists. Does it support RBAC? ReBAC? ABAC? These are table stakes. The decisions that actually determine whether you’ll regret your choice in 18 months are deeper: how the system behaves under load, how it isolates tenant data, whether its audit trail will satisfy your auditors, and whether you can leave if you need to.
This is a structured framework for evaluating authorization infrastructure. It’s designed to surface the differences that matter — the ones that don’t show up in a vendor’s feature matrix.
1. Performance
The question to ask: What is your p99 read latency under sustained load, and how does it degrade as throughput increases?
Authorization checks sit in the critical path. If your authorization layer adds 10ms per check and a single page load triggers 15 checks, you’ve added 150ms of latency before your application logic even runs. For AI agent workflows that may trigger dozens of checks per operation, this compounds fast.
What a good answer looks like: Sub-millisecond p99 latency at production throughput, with published benchmarks showing how latency behaves as load increases. Be skeptical of numbers measured at low concurrency or with warm caches. Ask for p99 under sustained load, not median latency in ideal conditions. Ask whether the system requires an external cache to hit those numbers — if it does, you’re inheriting the cache’s consistency and invalidation problems.
2. Security Model
The question to ask: How is tenant data isolated? Is isolation enforced at the application level or at the storage level? Can you demonstrate isolation to a third-party auditor?
Multi-tenancy is the norm for authorization services, but most systems enforce tenant isolation with application-level filters — WHERE tenant_id = ? queries against a shared database. This means a single bug in the filtering logic can expose one customer’s permissions to another. It has happened, repeatedly, across the industry.
What a good answer looks like: Isolation enforced below the application layer — ideally cryptographic isolation where each tenant’s data is encrypted with independent keys. Cross-tenant access should be architecturally impossible, not merely prevented by query filters. The vendor should be able to explain their isolation model in a way that satisfies your security team and external auditors without hand-waving about “best practices.”
3. Audit Trail
The question to ask: What does your audit trail capture, how is it protected from tampering, and can I export it to my SIEM?
Compliance frameworks increasingly require not just logging but provable integrity of those logs. A database row that says “access was denied at 10:00:01” is useful. A cryptographically signed, append-only ledger that proves the log hasn’t been altered after the fact is what auditors actually want.
What a good answer looks like: Every authorization decision is logged with full context — who requested what, against which resource, with what result, and the policy version that produced the decision. The audit trail should be tamper-evident (cryptographic chaining, not just “we don’t delete logs”). Retention should be configurable per your compliance requirements. Export to standard SIEM formats (CEF, LEEF, or structured JSON over syslog) should be a core feature, not a roadmap item.
4. Compliance
The question to ask: Which compliance frameworks have you mapped your controls to, and what is your own compliance posture?
There’s a difference between “our product helps you comply with SOC 2” and “we are SOC 2 Type II certified and here’s our report.” The first is marketing. The second is something your procurement team can work with.
What a good answer looks like: The vendor should have their own SOC 2 Type II report (or equivalent) available under NDA. They should be able to articulate specifically which controls their product addresses for frameworks relevant to your industry — whether that’s SOC 2, ISO 27001, HIPAA, FedRAMP, DORA, NIS2, or the EU AI Act. Bonus: they can provide a shared responsibility matrix that clearly delineates what they handle and what remains your responsibility.
5. Pricing Model
The question to ask: How do you charge, and can I predict my bill at 10x my current scale?
Authorization pricing models vary wildly: per-seat, per-monthly-active-user, per-authorization-check, per-vCPU, flat platform fee. The model matters more than the price point because it determines whether costs scale linearly with your growth or explode unpredictably.
What a good answer looks like: The pricing model should be predictable and aligned with a metric you can forecast. Per-check pricing sounds cheap at small scale but becomes terrifying when an AI agent workflow triggers 50 checks per operation across millions of requests. Per-seat pricing penalizes you for growing your user base. The best models are tied to infrastructure consumption (compute, storage) or flat tiers with generous limits — something your finance team can model in a spreadsheet without calling the vendor’s sales team every quarter.
6. Lock-in Risk
The question to ask: Is there an open source core? Can I export my data and policies? Is the policy language proprietary?
Authorization infrastructure is sticky by nature — it’s deeply integrated into your application code. If the vendor disappears, raises prices 5x, or pivots their product, your ability to migrate matters.
What a good answer looks like: An open source core licensed under a permissive license (MIT, Apache 2.0) that you can self-host if necessary. A standard or well-documented policy language — ideally one that maps to concepts (roles, relationships, attributes) rather than proprietary DSL syntax that only works in their runtime. Full data export in a documented format. If the vendor’s cloud offering adds proprietary features on top, the core authorization functionality should still work without them.
7. Operational Burden
The question to ask: What does day-two operations look like? Who handles scaling, upgrades, failover, and incident response?
The gap between a working demo and a production deployment is almost entirely operational. A managed service that handles scaling, upgrades, and failover is worth paying for — but only if the managed service is actually reliable. A self-hosted option is worth having — but only if you have the team to run it.
What a good answer looks like: For managed services: published SLAs with teeth (service credits, not just “we’ll try harder”), transparent incident communication, and zero-downtime upgrades. For self-hosted: clear operational runbooks, Kubernetes-native deployment (Helm charts, operators), automated upgrades, and observability built in (Prometheus metrics, structured logging, distributed tracing). Ideally both options exist so you can start managed and migrate to self-hosted (or vice versa) without re-architecting.
8. Integration Effort
The question to ask: How many lines of code does it take to go from zero to a working permission check in my stack? How long did your last customer’s integration take?
The theoretical elegance of an authorization model is irrelevant if integration takes six months. What matters is time to first check — how quickly a developer on your team can wire up a working permission check in your actual codebase, with your actual framework, in your actual language.
What a good answer looks like: SDKs for the languages and frameworks your team actually uses — not just the three most popular ones. A working integration in under 50 lines of code. A quickstart that gets you to a real permission check (not a toy example) in under an hour. Client libraries that handle connection pooling, retries, and caching transparently. The vendor should be able to point you to integration guides for your specific stack, not just generic REST API documentation.
Using This Framework
Print this out. Bring it to your next vendor call. Ask every vendor the same questions and compare the answers side by side. The vendors who welcome this level of scrutiny are the ones worth working with. The ones who deflect toward feature demos and roadmap slides are telling you something about the maturity of their infrastructure.
Authorization is foundational. Evaluate it like the infrastructure decision it is, not like a SaaS tool you can swap out next quarter.
InferaDB was designed to answer every question on this checklist. Sub-microsecond latency under sustained load. Cryptographic tenant isolation. Tamper-evident audit trails. Permissive open-source licensing. Usage-based pricing. See how we score or try it yourself.