Claude Code transcript

GCP Python API viability — research findings

Yes, viable. Google maintains official Python clients for everything we need. Here's the lay of the land mapped onto our CloudProvider abstraction (machine/provider.py:32):

Libraries

Both are official, actively maintained, and BSD/Apache-licensed. They'll fit in the same shiv bundle, though they're heavier than python-digitalocean and pull in gRPC + protobuf (notably bigger build artifact).

Three frictions worth knowing before you commit

1. SSH keys don't fit the existing model cleanly. DO and Vultr both have a server-side "named SSH key registry" you can list and reference by name. GCP doesn't — keys live in either:
2. Project metadata under the ssh-keys key (one big newline-separated string like user:ssh-rsa AAAA... comment)
3. Per-instance metadata at create time
4. OS Login (recommended modern path), which ties access to IAM identities instead of named keys

list_ssh_keys() and get_ssh_key(name) would have to synthesize "name" from the username prefix in each metadata entry. Not hard, just lossy.

1. Projects work differently. In GCP, every resource lives inside a project and the project ID is fixed at client construction — you can't assign_to_project a VM after creation the way DO supports. The existing list_projects/assign_to_project methods on CloudProvider would likely become no-ops, with the project ID coming from config instead.

2. Region vs. zone. GCP requires a zone (e.g. us-central1-a) for instance creation, not just a region. The existing region parameter would need to accept either, or we pick a default zone within the region.

Config shape (suggested)

gcp:
  project-id: my-gcp-project
  credentials-file: ~/.config/gcloud/service-account.json  # or rely on ADC
  default-zone: us-central1-a

Recommendation

Go with google-cloud-compute + google-cloud-dns. The mapping is straightforward except for SSH keys, where I'd suggest treating project-metadata keys as the equivalent of DO's named keys (username = name) for the MVP, and leave OS Login as a future option.

Want me to sketch the GcpProvider skeleton next, or look deeper into any of these (e.g. shiv bundle size impact, OS Login alternative)?

Sources: - google-cloud-compute on PyPI - Compute Engine Python sample: create_instance.py - Python Client for Cloud DNS API - Add SSH keys to VMs (project metadata) - About SSH connections / OS Login

All green: lint passes on the new files, all 34 tests pass, registration verified.

What changed

• pyproject.toml — added google-cloud-compute>=1.19.0 and google-cloud-dns>=0.35.0
• machine/providers/gcp.py (new) — GcpProvider implementing CloudProvider
• machine/providers/__init__.py — registered gcp in KNOWN_PROVIDERS and create_provider
• README.md — added GCP config section and noted the deviations

Design choices worth flagging

• region interpreted as a GCE zone as you suggested. Validation only checks for a hyphen so any zone-shaped string is accepted.
• VM ids are <zone>/<name>, since destroy/get only receive an opaque id and need the zone. The id is round-tripped from list output, matching how the existing CLI uses ids.
• Tags stored verbatim in instance metadata under key machine-tags (newline-joined). This avoids fighting GCP's labels-vs-tags constraints and keeps is_machine_created/is_same_session working unchanged. list_vms(tag=...) filters client-side.
• SSH keys read-only — the provider parses the project's ssh-keys metadata and looks up the entry whose username matches the ssh-key config value. The user has to add the key to project metadata themselves (via console or gcloud). Documented in the README.
• Auth: credentials-file path or Application Default Credentials. No token-in-config, since GCP doesn't really work that way.
• list_projects/assign_to_project left as the base-class no-ops — gracefully ignored.

Two follow-ups worth considering when you're ready: 1. The region field naming is now misleading for GCP. Renaming to region-zone (or zone) across all providers would be a wider refactor — happy to do it as a separate change if you want. 2. No e2e tests for GCP yet; tests/test_e2e.py is DigitalOcean-only.

Short answer: GCP doesn't have a single "API token" the way DO and Vultr do. You have two practical options for this tool — pick one.

Option A — Service account JSON key (recommended for scripted use)

1. Console → IAM & Admin → Service Accounts → Create service account. Give it a name like machine-cli.
2. Grant it these predefined roles on the project:
3. Compute Instance Admin (v1) — roles/compute.instanceAdmin.v1
4. DNS Administrator — roles/dns.admin (only if you'll use the dns-zone feature)
5. Service Account User — roles/iam.serviceAccountUser (usually only needed if your VMs run as a service account themselves; safe to add)
6. On the new service account, Keys → Add key → Create new key → JSON. A .json file downloads.
7. Stash it somewhere safe (e.g. ~/.config/gcloud/machine-cli.json, chmod 600) and point the config at it: yaml gcp: project-id: my-gcp-project credentials-file: ~/.config/gcloud/machine-cli.json ...

Option B — Application Default Credentials (simplest for local poking)

If you have gcloud installed, just run once:

gcloud auth application-default login

Then leave credentials-file out of the config entirely. The provider will pick up your user credentials. Convenient, but tied to your Google identity — not great for CI or shared use.

Two more one-time setup items (easy to forget)

These are per-project, not per-credential — APIs are off by default: - Enable Compute Engine API: gcloud services enable compute.googleapis.com --project=<project-id> (or via Console → APIs & Services → Library) - Enable Cloud DNS API: gcloud services enable dns.googleapis.com --project=<project-id> (only needed if you'll use DNS)

Permissions sanity check

Once configured, machine check will exercise the APIs (auth, SSH key read, DNS list, etc.) and tell you exactly which permission is missing if anything's off — that's the fastest way to validate the credential before trying a real create.

A note on SSH keys

GCP doesn't store named SSH keys as a separate registry. Before machine create will work, the project metadata needs an entry like:

alice:ssh-rsa AAAAB3Nza... alice@laptop

Easiest way to add it: Console → Compute Engine → Metadata → SSH Keys → Add. Or:

gcloud compute project-info add-metadata --metadata-from-file ssh-keys=keys.txt

Then set ssh-key: alice in your config.

In the Console, it's under Network Services → Cloud DNS. Direct paths:

• Top nav search bar: type "Cloud DNS" — fastest.
• Hamburger menu (☰): Network Services → Cloud DNS.
• Direct URL: https://console.cloud.google.com/net-services/dns/zones?project=<your-project-id>

What you'll do there

1. Enable the Cloud DNS API if it prompts you (one-time per project).
2. Create Zone → choose Public zone type → give it a Zone name (an internal identifier, e.g. example-com) and the DNS name (the actual domain, e.g. example.com.).
3. After creation, GCP shows you 4 nameservers (something like ns-cloud-a1.googledomains.com. etc.). You must set these as the NS records at your domain registrar — otherwise the zone exists in GCP but the world doesn't know to ask Google for your domain's records.
4. The dns-zone value in your machine config is the DNS name (e.g. example.com), not the zone identifier.

Heads up on costs

Unlike VMs, Cloud DNS has a small ongoing cost (~$0.20/month per zone plus per-query charges) — trivial for normal use, but it's a paid service from minute one rather than a free tier. Worth knowing if you create test zones and forget them.

Verifying it works

Once the zone exists and the NS records are set at the registrar:

machine domains       # should list the zone
machine list-domain   # should list any records you've added
machine check         # confirms the configured zone is found

Yep, that tracks — Cloud DNS is billing-gated from the first request (no free tier), so until a billing account is linked to the project, the service is effectively hidden. Compute Engine is more forgiving because of its free-tier allowances, which is why VMs probably worked for you while DNS didn't appear.

Once billing is attached, the menu item should show up immediately (no project restart needed). If machine check still complains about DNS after that, the most likely culprit is the API itself not being enabled — gcloud services enable dns.googleapis.com --project=<id> will sort it.

Yeah, that's a well-known rite of passage with GCP. The "API not enabled" failure mode is especially bad because the error often surfaces deep in a client library as a generic 403 or PERMISSION_DENIED, which sends people down the IAM rabbit hole when the actual fix is a one-line gcloud services enable. DO and Vultr's "sign up, get a token, go" experience really spoiled us.

Worth noting: this is also why I had the provider's __init__ lazy-import the DNS client — if a user only wants VMs and never touches DNS, they shouldn't hit a Cloud DNS API-disabled error at startup. They'll only see it when they actually try a DNS operation.

It's the GCE machine type — the predefined CPU/memory shape your VM gets. The provider takes the value verbatim and builds the full URL:

machine_type=f"zones/{zone}/machineTypes/{size}"

(machine/providers/gcp.py:138)

So if you set machine-size: e2-standard-2, the API call references zones/us-central1-a/machineTypes/e2-standard-2.

Common shapes

Naming convention: <family>-<class>-<vCPU count>. So e2-standard-4 = E2 family, "standard" memory ratio (4 GB/vCPU), 4 vCPUs.

Listing what's available in your zone

gcloud compute machine-types list --zones=us-central1-a

Not every type exists in every zone, so it's worth checking before settling on one. Custom machine types (arbitrary CPU+RAM) are also supported via a more elaborate string, but for typical use one of the predefined shapes is what you want.

It's the boot disk source image — what OS gets installed on the VM. The value is passed verbatim to GCE's source_image field on the boot disk:

initialize_params=compute_v1.AttachedDiskInitializeParams(source_image=image)

(machine/providers/gcp.py:127)

Two formats you'll actually use

The family path is what the README example uses, and it's what you want unless you have a specific reason to pin.

Common public image projects + families

Listing what's available

gcloud compute images list                              # everything (long)
gcloud compute images list --filter="family:debian-12"  # one family
gcloud compute images list --project=ubuntu-os-cloud    # all Ubuntu variants

One thing that might bite you

Cloud-init support: the user-data we attach in create_vm only fires if the image ships with cloud-init enabled. The Debian, Ubuntu, Rocky, and AlmaLinux images above all do. The bare CentOS and stripped-down "minimal" images sometimes don't — if your machine never picks up the new user / SSH key after creation, that's the first thing to check.

The message didn't come through — looks like it got cut off after "Here's the message:". Mind pasting it again?

That said, your description ("administrator access" page, claims Compute API isn't enabled when you can see in the console it is) is a near-perfect match for one specific GCP footgun, so I'll guess at it preemptively.

Most likely cause: quota project mismatch

When you use gcloud auth application-default login, the resulting credentials don't know which project to bill API calls to. So Google attributes the call to a separate "quota project" — which is not necessarily the same as the project-id in your machine config. If those don't match, the error message references the quota project (often some default Google-internal one like google.com:cloudsdktool-...), not your actual project. Following the "enable the API" link takes you to that other project, where you legitimately don't have admin rights — hence the "request access from administrator" page.

Fix

Tell ADC to use your project as the quota project:

gcloud auth application-default set-quota-project <your-project-id>

Then re-run machine check. The 403 should go away.

Or just sidestep it

The cleanest fix is to use a service account JSON key (Option A from my earlier reply). Service accounts are bound to a specific project, so there's no quota-project ambiguity, and credentials-file: in your config is unambiguous.

Once you paste the actual error I can confirm — but if it contains the phrase serviceusage.services.use or references a project ID that isn't yours, that's exactly this.

OK — different problem than I guessed. The URL in the error correctly references your project (machine-testing), so it's not a quota-project mismatch. GCP genuinely thinks Compute API isn't enabled on that specific project.

The most likely cause: you enabled it on a different project. This is easy to do because:

1. Project names are display-only and not unique — you might have two projects both displayed as "Machine Testing" with different IDs like machine-testing vs machine-testing-484726.
2. The console "enable API" button always acts on whatever project the dropdown is currently showing, which may not be the one you intended.

Verify from the CLI (more reliable than the console)

gcloud projects list
gcloud services list --enabled --project=machine-testing | grep compute

If the second command returns no rows, the API is genuinely not enabled on this project ID. Enable it explicitly:

gcloud services enable compute.googleapis.com --project=machine-testing
gcloud services enable dns.googleapis.com --project=machine-testing

Wait ~30 seconds for propagation, then re-run machine check.

Why the "request access from administrator" page

When you clicked the link in the error, the console probably opened with a different project context (the one your console session was last on, not necessarily machine-testing). On that other project you may not be the owner — hence the access-request page. The CLI commands above sidestep this entirely because they take an explicit --project flag.

Yeah, GCP's onboarding is genuinely rough — you're not imagining it.

The error text didn't come through this time either — looks like it got cut off after "another error:". Can you paste the actual message? I can't diagnose without seeing what gcloud printed.

A couple of common ones in case you can identify it from memory while you re-paste:

• PERMISSION_DENIED: ... permission 'serviceusage.services.enable' denied — your gcloud-logged-in account doesn't have rights to enable APIs on that project. Fix: get the Owner or Service Usage Admin role, or have whoever does it for you.
• The project ... could not be found — the project ID is wrong (a typo, or you're using the project name instead of ID). gcloud projects list will show the actual IDs.
• The caller does not have permission — you're authenticated but as the wrong identity. gcloud auth list shows which account is active; gcloud config set account <email> switches.

Ah, classic GCP confusion — there are two separate logins, and you've only done one. Annoying but real:

You did the second one (per my earlier instructions, so the machine tool would work). Now you're trying to run gcloud itself, which needs the first one.

Fix

gcloud auth login

This opens a browser, you pick the same Google account, done. Then your earlier command will work:

gcloud services list --enabled --project=machine-testing | grep compute
gcloud services enable compute.googleapis.com --project=machine-testing

Why two logins?

Historically, gcloud was for humans typing commands and ADC was for programs running on servers (using service accounts via the metadata server). When Google added "let your local Python script use your personal credentials too," they bolted on a second flow rather than unifying them. So both the gcloud CLI and your Python code each have their own credential store, and you have to log in twice. The error message could absolutely just say "run gcloud auth login or gcloud auth application-default login depending on what you're doing" — but it doesn't.

Ha — it does feel that way. The more charitable read is that GCP grew out of Google's internal infrastructure, where the assumed user is a Google SRE who already knows the difference between human credentials, service account impersonation, and workload identity, and considers it a feature that they're separate concerns. The product was then exposed externally without much rethinking of the onboarding for people who just want to spin up a VM.

DigitalOcean, by contrast, was designed from day one for "I am one developer, I want one server" — so "make a token, paste it" works because that's the only flow they had to support. GCP supports a dozen flows and makes you pick the right one before telling you which one you needed.

The real tell is that even Google's own docs frequently disagree about which auth command you should run for a given task. If the people writing the docs can't keep it straight, mortals don't stand a chance.

Found it — you're logged into gcloud with david.bozemanpass@gmail.com (personal Gmail), but the machine-testing project was almost certainly created under your david@bozemanpass.com account (a different identity, even though the local-part looks the same to a human). GCP treats them as two completely unrelated users, and the Gmail one has zero permissions on that project.

Diagnose

gcloud projects list

If machine-testing isn't in the output, that confirms it — this account can't see the project at all.

gcloud auth list

Shows which accounts gcloud knows about.

Fix — pick one

Option 1: switch gcloud to the right account. If you've already logged in as david@bozemanpass.com at some point, just switch:

gcloud config set account david@bozemanpass.com

If you haven't:

gcloud auth login   # pick david@bozemanpass.com in the browser

Then re-run gcloud services list --enabled --project=machine-testing.

Option 2: also check ADC. Whichever account is the project owner needs to be the one used for both logins. So once gcloud auth login is the right account, also redo:

gcloud auth application-default login   # again, pick david@bozemanpass.com
gcloud auth application-default set-quota-project machine-testing

Otherwise machine check will fail with a different identity-vs-project mismatch.

Why machine check previously got further

Your earlier machine check failure was an "API not enabled" error, not a permission error — meaning the ADC credentials do have access to machine-testing. So you probably did the original application-default login with david@bozemanpass.com and the more recent gcloud auth login with the Gmail account. Different accounts in different credential stores = exactly the kind of confusion this two-login system was built for.

Got it — single account, no Workspace, my email-confusion theory doesn't apply. Apologies for the wrong guess.

The output of gcloud projects list got cut off again, but I'll take your word that machine-testing appears in it. That tells us your account has some permission on the project (at least resourcemanager.projects.get) — but not necessarily enough.

What's likely going on now

Being able to see a project in gcloud projects list requires very little permission. Listing or enabling APIs requires more. Specifically:

Since you said you created the project, you should be Owner — but it's worth verifying.

Diagnose

gcloud projects get-iam-policy machine-testing --flatten="bindings[].members" --filter="bindings.members:david.bozemanpass@gmail.com" --format="value(bindings.role)"

That prints just the roles your account has on the project. If it shows roles/owner, you have full access and we're chasing a different bug. If it shows something more limited (or nothing), that's the problem.

Side check: Service Usage API itself

The Service Usage API (serviceusage.googleapis.com) is usually enabled by default on new projects — but if it somehow got disabled, listing/enabling APIs becomes impossible from the CLI and you'd see exactly this kind of permission error. Quick check via the console:

https://console.cloud.google.com/apis/library/serviceusage.googleapis.com?project=machine-testing

If it shows an "Enable" button rather than "Manage", that's it.

Could you paste the output of the get-iam-policy command? That'll tell us in one line whether this is a permissions issue or something weirder.

Found it. The project ID is machine-testing-495021, not machine-testing. The name is machine-testing (the human-readable label), but the ID (which is what every API and CLI command actually needs) has the random suffix appended.

You've been using machine-testing everywhere — in your ~/.machine/config.yml, in gcloud --project=machine-testing, and following the link in the original error — but that's a different project that belongs to someone else entirely. Project number 474257470277 in the earlier error is not yours; project number 433454590192 is. GCP returns deliberately vague "does not exist or no permission" errors when you hit a project you don't own, which is why this looked like a permission issue all along.

Fix

Two places to update:

1. Your machine config (~/.machine/config.yml):

gcp:
  project-id: machine-testing-495021   # was: machine-testing

2. ADC quota project:

gcloud auth application-default set-quota-project machine-testing-495021

Then enable the APIs on the right project (you may have already done this and just enabled them on a project you don't own — worth re-running):

gcloud services enable compute.googleapis.com --project=machine-testing-495021
gcloud services enable dns.googleapis.com --project=machine-testing-495021

After that, machine check should sail through.

Why this happens

When you create a project in the console and type "machine-testing" as the name, GCP appends random digits to make a globally-unique ID, because someone else already has the bare machine-testing ID. The console usually displays the name prominently and hides the ID, which is how this trips people up. From now on, if you're in any doubt, gcloud projects list is the source of truth — only the PROJECT_ID column matters for API calls.

All green. Worth celebrating — that confirms:

• Auth works (ADC reaching the right project)
• The SSH key david is in project metadata as expected
• Cloud DNS zone machine-testing-gcp.servesthe.world is found
• Zone string us-central1-a looks plausible
• The Ubuntu 24.04 image path is well-formed

A few things to note before you try machine create:

1. First real test: machine list should return an empty list (no error) — that exercises the aggregated-list code path across all zones.
2. Then: machine create --name test01 --type <one-of-your-machine-types>. Watch for the IP address being assigned and the DNS A record test01.machine-testing-gcp.servesthe.world getting created.
3. Cleanup: machine destroy <zone>/<name> (e.g. us-central1-a/test01) — remember the VM ID format is <zone>/<name> for GCP, unlike the bare numeric IDs DigitalOcean uses.

If create succeeds but you can't SSH in, the most likely culprit is cloud-init not running on the chosen image (Ubuntu 24.04 LTS does ship with it, so this should be fine) or the project's default firewall blocking port 22 — gcloud compute firewall-rules list will show what's open. The default network usually has default-allow-ssh enabled out of the box.

Thanks for catching that — my README was wrong on the user-facing flow. What you discovered is what actually happens:

• In the console UI (Metadata → SSH Keys → Add): you paste a raw public key like ssh-rsa AAAA... david@bozemanpass.com, and GCP auto-derives the username from the comment portion. With an email comment, it takes the local part (david).
• In the underlying metadata blob: GCP stores it in the <username>:<key> form I described, but the console hides that translation from you.

So my README was describing the storage format rather than the input flow, which is unhelpful — nobody manually constructs the metadata string when adding via the console.

Two related gotchas worth knowing: 1. If your key's comment is alice@laptop instead of an email, GCP would derive alice as the username. So the username extraction is just "everything before the first @ in the trailing comment." 2. If you use gcloud compute project-info add-metadata --metadata-from-file ssh-keys=... instead, you do have to format each line as <username>:<key> manually — the console-style auto-derivation only applies to the UI.

Want me to fix the README to describe the console flow accurately and keep the raw-format note as an aside for the gcloud path?

Updated. The README now describes the actual console flow (paste raw key, GCP derives username from the email/comment part) as the primary path, with the gcloud explicit-format approach as the alternative. Lint clean (the 5 unrelated files would-reformat were pre-existing in this branch, not my changes).

Nice — that's the full happy path working: VM created, ID returned in the <zone>/<name> format, and the DNS A record went into Cloud DNS. So GCE + Cloud DNS + project-metadata SSH keys are all wired up correctly.

A few things worth verifying while it's fresh:

1. SSH in: ssh <new-user-name>@test1.machine-testing-gcp.servesthe.world (using whatever username you set in the machine type's new-user-name, not david). If DNS hasn't propagated yet, try the IP directly from machine list.

2. Round-trip check: machine list should show test1 with the right tags (machine:created, machine:type:basic, machine:session:<id>). That confirms the metadata-as-tags encoding round-trips correctly through GCP.

3. Cleanup: machine destroy us-central1-a/test1 — important to verify destroy works end-to-end before relying on it. Also confirms the DNS record gets removed.

Anything that fails on those, paste it and I'll dig in.

That one line confirms a lot:

• Aggregated list works — found the instance across zones without needing to know the zone upfront
• Tag round-trip works — basic was extracted from the machine:type:basic tag, which means our newline-encoded metadata is decoding correctly
• IP parsing works — 34.71.92.77 came out of the nested network_interfaces[].access_configs[].nat_i_p structure

The remaining unverified path is machine destroy — that's the one most likely to surface a wait-for-operation or DNS-deletion issue, since destroy returns a long-running operation and we block on op.result(). Worth running:

machine destroy us-central1-a/test1

Then confirm with machine list (should be empty) and machine list-domain (the test1 A record should be gone). If destroy hangs or errors, that's likely a propagation timing thing or the operation timeout being too short — easy to fix.

Excellent — that's the full end-to-end verified: SSH key from project metadata propagated to the VM, cloud-init created the user account, DNS resolved, and the firewall let you in. Means the user-data path through GCE metadata is wired up correctly too.

destroy is the only path still untested — once you've confirmed that cleans up both the VM and the DNS record, the GCP provider is ready to ship.

Now I'll make the edits. Plan:

• Prose in create.py and destroy.py (6 strings)
• Click argument [DROPLET-IDS] → [MACHINE-IDS] in destroy.py (cascades to the Python param name)
• JSON output field names: droplet → machine in util.py, droplet-status → machine-status in status.py
• README to match (Usage line, prose, JSON examples)
• test_e2e.py docstring (the test logic doesn't depend on the literal word)

Internal references in digitalocean.py (DO's SDK uses Droplet/get_droplet literally) stay as-is — those are provider implementation details.

All clean. 34 tests pass, lint clean on everything I touched (the 5 "would reformat" files are pre-existing in this branch — same set as before my edits).

What changed

Prose (create.py, destroy.py): - "New droplet created" → "New machine created" - "Assigned droplet to project" → "Assigned machine to project" - "Waiting for droplet IP address" → "Waiting for machine IP address" - "Cannot destroy droplet ..." → "Cannot destroy machine ..." - "DELETE/DESTROY droplet ..." → "DELETE/DESTROY machine ..."

Click argument (destroy.py): [DROPLET-IDS] → [MACHINE-IDS]. Also renamed the destroy-message tail from "by machine" / "of machine" (which would have read awkwardly with the noun rename) to "by this tool" / no qualifier — the meaning is unchanged but it avoids "machine" being both noun and tool name in the same sentence. Push back if you'd rather keep the literal wording.

JSON output field names (heads-up — technically a breaking change for anyone scripting against --output json): - status JSON: droplet-status → machine-status - list-domain JSON: nested droplet → machine

README updated to match.

Left as-is (intentionally)

• machine/providers/digitalocean.py — DO's Python SDK literally has a Droplet class and methods like get_droplet(). These are SDK API references, not user-facing.
• tests/E2E.md and the comment in tests/test_e2e.py:16 — DigitalOcean-specific docs explaining DO's API scope names. They're correctly DO-specific and still accurate.

I have a clear picture. The plan:

• tests/test_e2e.py: add gcp to defaults, add E2E_GCP_PROJECT_ID / E2E_GCP_DNS_ZONE / E2E_GCP_CREDENTIALS_FILE env vars, extend the DNS-zone selector and the missing-vars guard, add a gcp: branch in _write_config. For the bad-token test, override project-id with a bogus value (GCP doesn't have a single "token" field — but pointing at a project you can't access produces the same "auth fails" effect).
• .github/workflows/e2e-test.yml: add gcp to the matrix and pass through the GCP env vars. CI runs will skip cleanly until creds are actually configured.
• tests/E2E.md: add a GCP section.

All four checks green:

• Lint: clean on everything I touched (the 5 "would reformat" files are pre-existing, same set as before).
• Unit tests: 34/34 pass.
• E2E module imports correctly under each provider; the missing-vars guard reports the right vars per provider; defaults resolve as expected.
• E2E with E2E_PROVIDER=gcp and no creds: 14 tests skip cleanly with the standard "E2E env vars not set" message — exactly what CI will do until you wire up credentials.

Files changed

• tests/test_e2e.py — gcp defaults, env vars, DNS zone selector, missing-vars guard, _write_config branch, bad-token test branch
• .github/workflows/e2e-test.yml — added gcp to matrix, passed through E2E_GCP_PROJECT_ID / E2E_GCP_DNS_ZONE (with comment explaining why credentials are deferred)
• tests/E2E.md — GCP prerequisites, env var table, run snippet, CI section updated

To run locally

export E2E_PROVIDER=gcp
export E2E_GCP_PROJECT_ID=machine-testing-495021
export E2E_GCP_DNS_ZONE=machine-testing-gcp.servesthe.world
export E2E_SSH_KEY=david
# ADC already set up from earlier work; no E2E_GCP_CREDENTIALS_FILE needed
uv run pytest tests/test_e2e.py -v -m e2e