Quack on DemandServicesDeploy, secure & operate the FlightSQL gateway

Run Quack On Demand in production, with the team that builds it.

We help you stand up a multi-tenant Arrow FlightSQL gateway for DuckDB and DuckLake, from architecture and identity integration to RBAC, federation, observability, and SLA-backed managed operations.

Decisions we make with you

  • TenancyOne DuckLake catalog per tenant, isolated by design
  • PoolsREADONLY, WRITEONLY and DUAL nodes sized to each workload
  • IdentityYour OIDC provider, RBAC graph mirrored from your groups
  • StorageS3-compatible object store plus a managed PostgreSQL control plane
  • EdgeTLS on FlightSQL, private endpoints, no public data path
  • Run modeuvx, Docker or Kubernetes, chosen by tenant count and SLA

Delivered as code, in your repository

qod-platform/
terraform/# network, storage, control plane
helm/ or compose/# the run mode you chose
tenants.yml# catalogs, pools, quotas
rbac.yml# users, groups, table grants
runbooks/# upgrade, restore, on-call
dashboards/# Grafana, alert rules

The same reference architecture runs as one process with uvx, one container with docker, or a cluster on kubernetes.

Quack On Demand serves what any pipeline wrote, to any SQL client.

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What we deliver

Services across the full Quack On Demand lifecycle

From a first deployment to long-term managed operations, every engagement is staffed by the engineers who build Quack On Demand.

Deployment & Architecture

Stand up Quack On Demand the right way: sized, secured, and reproducible.

  • uvx, Docker Compose or Kubernetes (Helm) rollout
  • PostgreSQL control plane + object storage layout
  • TLS on the FlightSQL edge (CA-signed certs)
  • Pool sizing for READONLY / WRITEONLY / DUAL nodes

Multi-Tenant Onboarding

Design a tenant model that isolates data and scales cleanly.

  • Per-tenant DuckLake catalog design
  • Pool topology and capacity planning
  • Tenant provisioning and lifecycle workflows
  • Cost attribution and resource boundaries

Identity & RBAC Integration

Wire Quack On Demand into your existing identity and access model.

  • OIDC / JWT: Keycloak, Azure AD, Cognito, Google
  • RBAC graph: users, groups, roles, table & pool grants
  • Per-statement table-ref policy enforcement
  • Handshake and pool-access gating

Federation & Client Enablement

Connect your sources and get every team querying through one edge.

  • Federated access to S3, Iceberg, and Postgres
  • Client setup: JDBC, ODBC, ADBC, PyArrow, Spark
  • Query patterns and routing best practices
  • Migration from direct DuckDB access

Observability & SRE

Run it reliably with metrics, alerting, and battle-tested runbooks.

  • Prometheus + Grafana dashboards and alerts
  • Self-healing restart and resilience tuning
  • Capacity and latency monitoring
  • Incident runbooks and on-call playbooks

Security Hardening & Managed Ops

Lock it down and let us keep it healthy under an SLA.

  • Security review and boundary testing
  • Audit logging and upgrade strategy
  • SLA-backed managed operations
  • Direct line to the Quack On Demand maintainers

Deploy anywhere

One process, one container, or a cluster. The same image everywhere.

Quack On Demand is portable by design. Run it with uvx on a single node, as a Docker container, or on Kubernetes, on-premise or on AWS, Google Cloud, or Azure. We deliver a reference architecture for your target and stand it up with you.

uvx

One process on a laptop or a single VM. Nothing to install beyond Python.

$ uvx qod start

Docker

One container on one node. The right size for a single tenant or a team.

$ docker run starlakeai/quack-on-demand

Kubernetes

Autoscaling pools across nodes for many tenants, with Helm.

$ kubectl apply -k github.com/starlake-ai/quack-on-demand

Where it runs

On-premise

Your data center, your network, your rules.

  • uvx, Docker Compose or Kubernetes on your own hardware
  • S3-compatible storage: MinIO, Ceph, NetApp
  • Self-hosted PostgreSQL control plane
  • Air-gapped and data-residency friendly

AWS

Native to the services you already run.

  • EKS or ECS Fargate, or a single EC2 node with Docker or uvx
  • S3 for Parquet, RDS / Aurora PostgreSQL
  • Cognito or IAM-backed identity
  • NLB / PrivateLink in front of the FlightSQL edge

Google Cloud

Stay inside Google's backbone.

  • GKE, or a single Compute Engine VM with Docker or uvx
  • GCS for Parquet, Cloud SQL for PostgreSQL
  • Google / Workspace identity
  • Internal load balancer on the edge

Microsoft Azure

Wired into Entra and Azure storage.

  • AKS, or a single Azure VM with Docker or uvx
  • Azure Blob storage + Azure Database for PostgreSQL
  • Microsoft Entra ID (Azure AD) identity
  • Private endpoints on the FlightSQL edge

One image, every environment

Quack On Demand ships as a single containerized stack whose only external dependencies are object storage and PostgreSQL. It runs as one process with uvx, one container with Docker, or a Helm release on Kubernetes. We pin a reference architecture for your target and deliver it as code (Terraform + Helm, Compose, or a systemd unit).

Start where you are, move when you are ready

The same configuration runs on a laptop, in your data center, and in the cloud. We help you start on-premise or in one cloud and migrate later with no rewrite - your tenants, RBAC, and DuckLake catalogs come with you.

Ready to deploy Quack On Demand?

Let’s scope your gateway.

Tell us about your tenants, identity provider, and data sources. We’ll propose an architecture and a phased delivery plan.

Typical outcomes

What you can expect to have in production after an engagement.

  • A secure, multi-tenant FlightSQL gateway running in your environment
  • Identity and table-level RBAC wired into your existing IdP
  • Observability, runbooks, and a tested recovery path
  • A clear upgrade and operations plan aligned with upstream

Start with a strategy call

We’ll review your tenancy model, identity setup, and data sources, then identify the fastest path to a production gateway.

Prefer async? Email us at [email protected].

Starlake.ai | Open Source Data Infrastructure for the Agent Era