docs: WireGuard vs SSH, Flux GitOps, CONTRIBUTING with TDD-first
Document why WireGuard and SSH are complementary layers, add Flux boundaries for the ground segment, shared var/ data paths in docs/06, and a contributor guide with the required test-first workflow.
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@@ -61,6 +61,29 @@ The environment engineers live in daily — and deliberately the first thing to
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- **T4 data slices**: a thin tool pulls partition subsets from T3 (`flight=X, drone=Y, hour=Z`) for local work — layout-identical, so every query and pipeline runs unmodified.
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- The same simulator images scale out on the ground k3s farm for CI regression runs: every merge request replays canonical scenarios and asserts on the resulting Parquet output (row counts, coverage, staleness budgets).
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## IaC boundaries
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Infrastructure as code follows the same discipline as the data plane: each tool owns the layer it is actually good at, and nothing owns a layer it can't reach.
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| Layer | Tool | Why |
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| --- | --- | --- |
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| Host preparation (drone bench provisioning, sim cluster creation) | **Ansible** ([`infra/ansible/`](../infra/ansible/)) | Idempotent, agentless, works over the same SSH channel the platform already trusts. Keys, forced commands, WireGuard, Compose bundles — all host-level state. |
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| Declared workloads (simulated fleet, ground warehouse) | **Terraform** ([`infra/terraform/`](../infra/terraform/)) | The ground segment is stationary, long-lived, and cluster-shaped — classic Terraform territory. Fleet size, offload schedule, and explorer endpoints are variables, not YAML edits. |
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| Ongoing ground configuration | **Flux** ([`infra/gitops/`](../infra/gitops/)) | Policy labels, dashboard bundles, offload knobs — reconciled from git without reprovisioning PVCs. Drones stay on the fleet manifest, not GitOps. |
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| On-board runtime | **Compose bundle from the fleet release manifest** | Terraform is deliberately *not* on the drone: there is no API server to reconcile against mid-flight, and the release manifest already gives atomic, versioned, rollback-able delivery ([11](11-cicd-delivery.md)). |
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Shared local data paths (same layout everywhere): **`var/t1/`** (live lake, T1) and **`var/t3/`** (warehouse, T3). Compose, k3d, and DuckDB on the host all read the same Parquet tree.
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Two Terraform modules, two states, one deliberate split: [`sim-env`](../infra/terraform/sim-env/) (the disposable virtual fleet) and [`ground`](../infra/terraform/ground/) (the warehouse that must survive every `destroy` of the fleet). They never share a lifecycle.
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### k3d: the ground segment as an executable miniature
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`ansible-playbook infra/ansible/sim-cluster.yml` creates a local k3d cluster (k3s in Docker — the same distribution as the real ground segment) and `terraform apply` populates it: virtual drones as StatefulSet replicas over a shared Parquet lake, the exporter/Prometheus/Grafana stack, the data-plane explorer, MinIO, and the T1→T3 offload CronJob. The whole diagram at the top of this page runs on one workstation, and the prototype's **live mode** renders real drone positions straight from the explorer's read-only SQL API.
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### Next fidelity step: microVMs
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The k3d fleet shares one kernel and one network namespace tree — good enough to exercise the data plane, not good enough to demo the *peer* plane (real SSH sessions between isolated machines, WireGuard handshakes, packet loss injection). The next step, when that fidelity is needed, is one **Firecracker microVM per drone**: a real kernel, a real network interface, and the actual `authorized_keys` forced-command path between virtual drones — on any KVM-capable workstation, still with no cloud dependency. The process-level simulator stays as the fast inner loop; microVMs become the pre-flight integration rig.
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## Why identical layouts matter (the payoff)
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| Operation | What it costs with one layout everywhere |
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