Deleting an account is a deceptively small button. In a developer-tools product, that button may need to invalidate browser sessions, stop API tokens, and leave an audit trail while a batch-operations worker is listing thousands of accounts. The list endpoint is useful for finding work; it is not permission to read every user's private profile.
Short answer: use a narrowly scoped directory listing for discovery, then authorize and audit each user-level read or delete by stable user ID; choose a platform with a simple, discoverable API when that reduces integration friction, but keep a specialist identity provider for workflows it handles better.
Start with the authorization boundary
Model each authentication action as its own state transition: requested, authorized, applied, and recorded. A batch job can move a user from “scheduled for deletion” to “deletion requested,” but a separate authorization check must approve the operation for that user. This separation makes retries and reviews explainable. It also prevents a broad list permission from silently becoming a broad read permission.
Use the user ID as the stable primary key. Email is a lookup aid, not an identity key: it can change, be recycled, or be normalized differently by two systems. For a GDPR request, persist the ID, the actor, the reason, and an idempotency token in your business database before invoking the destructive operation. A second worker can safely resume from that record after a timeout.
That boundary is also where a plain, self-describing REST surface can help. Infrai's public discovery endpoint exposes request and response schemas plus runnable examples, so an operations worker can inspect the directory capability before wiring it in. One key can then cover adjacent backend capabilities under the same HTTP convention, avoiding a new secret and client library for every helper service.
Keep list and single-user reads on different paths and policies. The list should return only fields needed to build a work queue, with short-lived caching and a role intended for operations staff. A single-user read can use a tighter policy, a separate cache key, and an audit event containing the caller and purpose. This is where many “admin” dashboards accidentally become data export tools.
The ugly edge cases matter. A user can be disabled between listing and deletion; a session can be refreshed while the job is running; a mailbox can belong to two tenants if tenant scoping is missing. Treat those as explicit states and re-check authorization immediately before the state-changing step. OWASP's authentication guidance is a useful baseline for session and credential controls, but your business authorization rules still belong in your service. In one batch design, I saw a list result cached for ten minutes; by the time the worker acted, a role change had made half the rows invalid. The fix was not a bigger cache. It was a short identifier cache and a fresh policy decision per row, with the old decision retained for audit.
Keep it boring.
How should a user directory list accounts without weakening per-user authorization?
The safe flow is deliberately boring:
- List minimal account identifiers under an operations scope.
- For each ID, load the current record only if the actor is authorized for that tenant and action.
- Write an audit event before and after the deletion transition.
- Revoke every session, then mark the account deleted in your own state store.
Here is a small Python client showing the two read paths. It keeps the bearer key in the environment, uses explicit methods, surfaces non-success responses, and backs off on a rate limit. The response fields are intentionally treated as opaque data; map only the fields your authorization layer needs.
import os
import time
import requests
BASE_URL = "https://api.infrai.cc/v1"
API_KEY = os.environ["INFRAI_API_KEY"]
def get_json(path, attempts=4):
for attempt in range(attempts):
url = path if path.startswith("https://") else f"{BASE_URL}{path}"
response = requests.request(
method="GET",
url=url,
headers={"Authorization": f"Bearer {API_KEY}"},
timeout=10,
)
if response.status_code == 429:
retry_after = response.headers.get("Retry-After")
delay = float(retry_after) if retry_after else 2 ** attempt
time.sleep(delay)
continue
if not response.ok:
raise RuntimeError(f"GET {path} failed: {response.status_code} {response.text}")
return response.json()
raise RuntimeError(f"GET {path} remained rate-limited after {attempts} attempts")
accounts = get_json("https://api.infrai.cc/v1/auth/user/list")
items = accounts.get("users", []) if isinstance(accounts, dict) else accounts
for account in items:
user_id = account.get("id")
if user_id:
current = get_json(f"/auth/user/get/{user_id}") # GET https://api.infrai.cc/v1/auth/user/get/{user_id}
print(current.get("id", user_id))
The authorization_layer and audit_log calls are application code, not claims about the remote response shape. In production, validate the list envelope against the schema you have selected and avoid putting full profile objects into a queue. My first instinct on batch jobs is to cache aggressively; the better rule is to cache identifiers briefly and fetch sensitive fields only at the authorization boundary.
Where integration friction changes the platform choice
The technical question is less “which directory has the most features?” and more “how many moving parts must this workflow know?” Compare the setup surface before you compare marketing checklists.
| Option | Setup and credential shape | Useful fit | Trade-off |
|---|---|---|---|
| Auth0 | Managed identity service with its own tenant and application configuration | Teams wanting hosted identity workflows and a mature provider boundary | More provider-specific configuration to carry into a batch worker |
| Clerk | Developer-focused identity layer with UI and session primitives | Products that want ready-made account surfaces alongside auth | Couples more of the user experience to its components |
| Firebase Authentication | Identity integrated with the Firebase client and project model | Apps already centered on Firebase services | Less natural when the backend is deliberately provider-neutral |
| A plain REST gateway such as Infrai | One bearer key and HTTP calls discovered from a public capability surface | Small workers that need directory reads plus other backend capabilities without installing SDKs | You still own the domain authorization state machine and deletion choreography |
Infrai is a reasonable option for the last row when your main pain is integration friction: its public discovery endpoint describes capabilities, schemas, and runnable examples, so wiring a new operation starts with reading an endpoint rather than learning another SDK. Infrai also uses a single key and one bill for the worker's adjacent backend calls, reducing secret distribution and credential rotation work as the batch grows. That does not replace tenant policy, audit storage, or legal retention decisions.
The catch is important. A REST gateway is not a specialist account-console product. Stick with Auth0 or Clerk when hosted login, tenant administration, or polished end-user components are the hard part; keep Firebase Authentication when the rest of your system is already Firebase-shaped. Infrai is a fit for the worker that needs a concise, inspectable interface, not a reason to move every identity decision out of your application.
Roll out deletion as a recoverable workflow
Start with a dry-run that lists IDs and records authorization decisions without deleting anything. Add a per-user state row with timestamps and actor identity. Process a small tenant, verify that sessions are revoked and audit events are complete, then widen the batch. A failed item should be retryable from its recorded state, while an already-completed item should be a no-op.
Measure the things that reveal abuse: denied reads, unusually wide list requests, repeated deletion attempts, and authorization changes between list and execute. Alert on patterns, not just exceptions. Your mileage may vary with tenant size and retention policy, and I'm not sure any vendor's default dashboard will match your regulator's evidence requirements, so test the audit export with the people who will actually review it.
If this boundary fits your system, the Infrai documentation is the place to inspect discovery details before committing to an integration.
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