Where it runs

Four substrates, one artifact

The same container in every case. Pick the row that matches what your team already runs — each step up buys observability and resilience at the cost of something to operate.

Choose where the connector runs
The same connector container running on a single on-premise host. Quick to stand up, with no cluster around it and nothing aggregating its logs or metrics. Data lands in your warehouse.one hostno cluster, no failoverConnector Your warehouse

Docker / Compose

The quickest way to have it running.

One host, on your premises or a virtual machine, and a container. Nothing to install beyond a container runtime, and nothing new for anyone to learn. It is also the level at which you are on your own: with no cluster and no controller beside it, there is nothing aggregating its logs, collecting its metrics, or restarting it somewhere else when the host goes away.

What it gives you

  • Running the same afternoon
  • Nothing new to operate
  • Runs entirely on premise

What it costs you

  • No failover — one host is the whole estate
  • Logs and metrics stay on that host
  • Support cannot see it, so support is absent rather than reduced
A lightweight cluster of one to three servers carrying three connectors and one SourceQ controller. The controller manages every connector on the cluster, and optionally exchanges telemetry and deployments with SourceQ. Each connector writes to your warehouse directly.optionalk3s · 1–3 serversControllerConnectorConnectorConnector Your warehouse

k3s

The smallest cluster that can be handed over without an apology.

A lightweight Kubernetes distribution on one to three servers. It is a real cluster — scheduling, restarts, rolling updates — small enough that your own team can own it, and it is where a SourceQ controller can sit beside your connectors and collect what they do. Sending that telemetry on to us is optional and is what a support plan buys; without it the controller still runs, and you still get the logs and metrics yourself.

What it gives you

  • Restarts and rolling updates handled for you
  • Logs and metrics collected in one place
  • Several connectors on one cluster, one controller
  • Failover once there is more than one server

What it costs you

  • A cluster to patch and upgrade
  • Costs more than the workload does at one connector
The same connector container in a dedicated namespace inside an existing corporate Kubernetes cluster, beside the organisation's other workloads. Data lands in your warehouse.your Kubernetes clusteryourworkloadsyourworkloadsa dedicated namespace, your existing patternsConnector Your warehouse

Enterprise Kubernetes

It goes where your other workloads already are.

A dedicated namespace in the cluster you already run — GKE, EKS, AKS or on-premise. It inherits the patterns your platform team has already settled: access control, secret management, ingress, monitoring, cost allocation, change process. Nothing new is introduced for anyone to operate, which is usually the deciding argument.

What it gives you

  • Your existing access control and secret management
  • Your monitoring, your alerting, your on-call
  • Nothing new for the platform team to adopt

What it costs you

  • Needs a platform team, and their change process
  • Namespace and quota to be agreed before anything ships
The same connector container running on SourceQ's cloud, operated by SourceQ. The image, the source and the data remain yours, and data lands in your warehouse.SourceQ cloudwe operate it, you still own itConnector Your warehouse

SourceQ Cloud

We run it, we manage it — you still keep it.

The same container on our cloud, operated by us. You keep the image, the source, the infrastructure definitions and the data, so moving it to your own infrastructure later is a redeploy rather than a rebuild. Because the data is extracted on our systems before it reaches your warehouse, we are a data processor at this level: we will say so in writing, sign a data processing agreement and name the region.

What it gives you

  • Nothing for you to operate at all
  • Observability, alerting and on-call included
  • Moving it in-house later is a redeploy

What it costs you

  • We become a data processor, and a DPA is required
  • Your data is in transit through our systems

Who operates it

A separate question from where it runs

The substrate above is what the connector runs on. This is who operates it and who holds the credentials — the two are chosen independently.

 HostedIntegratedSelf-hosted
Runs onOur cloudOur cloudYour infrastructure
Data lands inYour warehouseYour warehouseYour warehouse
Your data on our infrastructureIn transitIn transitNever
Source credentials held byUsYouYou
We are a data processorYesYesNo
Moving to another levelRedeployRedeployRedeploy

What is inside it

Two-thirds of every connector is not about your API

Health, metrics, logs, configuration, retries, inbound events. Written once and shared, so the work we bill for is the part that is specific to your source.

HealthA readiness endpoint your load balancer or scheduler can check
MetricsOne scrape target per container: run counts, rows, freshness, failures
LogsStructured JSON to stdout, collected by whatever already collects logs
IdentityAn endpoint that states the version actually running, not the one intended
Inbound eventsWebhook delivery is verified and receipted before it is acknowledged
ConfigurationFrom the environment. Credentials by reference, never a value in a file
SupervisionA connector that exits is restarted; a clean exit is not treated as a fault

A container runs one connector, built against our SDK. The connector does the extracting, transforming and loading for one source system; the SDK gives every connector the same health checks, metrics and log format, so a fix to health checking is not a fix to twelve connectors. You never have to care about that split unless you want to.

Ownership

What you own, and what we maintain

Everything in the container is yours. The difference is between what you already have and what you keep receiving.

You own the connector

The integration itself: how your API is authenticated and paginated, incremental state, the transformation, the warehouse load. Source in your repository from the first commit, yours permanently and unconditionally. If you leave, a scheduled connector carries on running.

We maintain the SDK

The library your connector is built against — health, metrics, logs, configuration. It is deliberately small, and it is in your repository like everything else. While you are under contract we keep it current. When the contract ends, the version you have is yours, as-is and free to use, for as long as you like. Nothing expires and nothing switches off.

What this is not

There is no platform to buy into

No engine, no builder interface, no control plane, no runtime you must keep paying for to keep your pipeline alive.

Every part of a connector is assembled from components you already run or could hire for: a container, a scheduler, a secret manager, your warehouse. That is a deliberate limit on what we build, and it is the reason the lock-in answer is demonstrable rather than a promise — here is the image, here is the repository, here is the command to run it.

If a vendor connector already covers your API, use it — we will tell you. We build the ones that don't exist, or don't do what you need.

Send the architecture question you actually have

If your platform team needs to know how a connector behaves in your environment specifically, ask. A concrete answer is faster than a diagram.

Ask us