Concepts
The planned model behind Qeet Logs — ingest, query, identity-aware attribution, tenant isolation, and privacy-by-design.
In design
Qeet Logs is documented from its product requirements — there's no code or public API yet. These are the concepts the platform is being built around and may change before release.
Qeet Logs is log management for teams that take privacy seriously: high-volume ingest, fast queries, and identity-aware attribution through Qeet ID.
Ingest
Logs arrive over standard protocols — OTLP/HTTP and an HTTP ingest API, with SDK and log-shipper adapters planned (syslog, Vector, Fluent Bit, and language loggers). Structured and unstructured logs are both first-class. Storage is planned on a column store (ClickHouse) with partitioning and TTL for cost control.
Query
A LogQL-style query engine with a REST query API powers sub-second search across tenants, live tail, and service-overview dashboards. The design targets P90 query latency under 300 ms at 1 TB stored.
Identity-aware attribution
Every log line is attributable through Qeet ID — user, tenant, and session — so you can answer "who did what" without bolting on a separate audit pipeline. A Qeet ID auth-event stream enriches logs with identity context.
Tenant isolation
Multi-tenancy is foundational: strict tenant isolation, admin/tenant RBAC, scoped API keys, and a query audit log so access to logs is itself auditable.
Privacy by design
PII is handled at ingestion time rather than after the fact, with GDPR erasure (and erasure receipts) and data-residency controls. Privacy is a platform property, not an add-on.
Where this is heading
The phased plan — from an ingest/query MVP to a privacy-native, Qeet ID-integrated GA and then AI-assisted analysis — is on the roadmap. Until Logs ships, Qeet ID's tamper-evident audit covers identity-event logging today.