AdminResource

Reference

AdminResource

Administrative bulk operations

10 min Advanced

ReferenceAPIAdmin

AdminResource

Accessed via client.admin, this resource provides privileged bulk operations that require the Admin role. It is used for operational cleanup tasks such as deleting stale test instances or expired resources.

All operations enforce safety constraints: at least one filter is required, a maximum of 100 deletions per request, and an optional expected_count guard to prevent accidental mass deletion.

1

Setup

Connect as an admin user

# Cell 1 — Parameters
USERNAME = "_FILL_ME_IN_"  # Set your email before running

# Cell 2 — Connect
from graph_olap import GraphOLAPClient
client = GraphOLAPClient(username=USERNAME)

# Cell 3 — Provision
from notebook_setup import provision
personas, _ = provision(USERNAME)
analyst = personas["analyst"]
admin = personas["admin"]
ops = personas["ops"]
client = analyst

2

Bulk Delete

Safely delete resources in bulk

bulk_delete(resource_type, filters, reason, expected_count=None, dry_run=False) -> dict

Bulk delete resources matching the given filters. Designed for operational cleanup with multiple safety guards built in.

Parameter	Type	Default	Description
resource_type	str	required	"instance", "snapshot", or "mapping"
filters	dict	required	At least one filter required (see below)
reason	str	required	Reason for deletion (written to audit log)
expected_count	int | None	None	Safety check — must match actual count or request fails
dry_run	bool	False	If True, return what would be deleted without deleting

Available filters:

Filter	Description
name_prefix	Match resources whose name starts with prefix
created_by	Match resources created by a specific username
older_than_hours	Match resources older than N hours
status	Match resources with a specific status

Returns: dict with matched_count, matched_ids (dry run) or deleted_count, failed_count (execute).

Raises:

• ForbiddenError — user does not have Admin role
• ValidationError — no filters provided, matched > 100, or count mismatch

Safety features:

• At least one filter is always required
• Maximum 100 deletions per request
• expected_count validation prevents surprises
• Full audit logging of every deletion

Recommended pattern: dry run first, then execute

Always perform a dry run to inspect what will be deleted, then pass the matched count as expected_count in the real call. This two-step pattern prevents accidental mass deletion.

# Step 1: Dry run -- see what WOULD be deleted
preview = admin.admin.bulk_delete(
    resource_type="instance",
    filters={"status": "terminated"},
    reason="cleanup-terminated-instances",
    dry_run=True,
)

print(f"Would delete {preview['matched_count']} instances")
print(f"IDs: {preview['matched_ids']}")

# Step 2: Execute with expected_count safety check
result = admin.admin.bulk_delete(
    resource_type="instance",
    filters={"status": "terminated"},
    reason="cleanup-terminated-instances",
    expected_count=preview["matched_count"],  # must match or request fails
    dry_run=False,
)

print(f"Deleted: {result['deleted_count']}")
print(f"Failed:  {len(result.get('failed_ids', []))}")

Multiple filters

Filters are combined with AND logic. This example targets old test instances created by a specific user.

# Combine filters for precise targeting
preview = admin.admin.bulk_delete(
    resource_type="instance",
    filters={
        "name_prefix": "E2ETest-",
        "older_than_hours": 24,
    },
    reason="cleanup-old-e2e-instances",
    dry_run=True,
)

print(f"Matched: {preview['matched_count']} instances")

Key Takeaways

• Always use dry_run=True first to preview what will be deleted
• Pass expected_count from the dry-run result to guard against race conditions
• At least one filter is required -- you cannot bulk-delete without constraints
• Maximum 100 deletions per request -- split larger cleanups into batches
• Every deletion is written to the audit log with the provided reason