labagent
Provision, audit and safely tear down ephemeral AWS sandboxes for workshops, bootcamps and shared training accounts.
pip install labagent # Python 3.9+; Terraform or OpenTofu >= 1.11 for the cohort IAM layer
labagent --version
Commands
| Command | What it does |
|---|---|
provision |
Terraform creates a cohort's IAM users, group, sandbox policy and Lambda role. Passwords are issued afterwards and returned encrypted to your public key, so state holds no secrets |
inventory, sweep |
List and delete what learners created. Plan first, then apply exactly that reviewed plan |
reset, offboard |
Rotate a learner's password; destroy a cohort (refuses while resources remain) |
audit, cleanup |
Clean an untagged, long-lived account from an explicit ruleset (docs) |
Safety
- Plan, then apply: the plan is bound to the account, its items, an age limit and the hash a human approved.
- Only a
deleterule can delete.keeprules always win; anything unmatched is reported, never removed. - Refuses to run in an account that is not on your allow-list. Re-running is always safe.
- No plaintext secrets or emails in output or logs, and no PII in this repo (enforced by tests).
Use
cp examples/config.example.json lab.json # set allowed_account_ids and the S3 state backend
labagent --config lab.json run --job job.json --output result.json
Job and result formats: docs/job-contract.md. State and secrets: docs/state-and-secrets.md.
Run it from a private CI repo with GitHub OIDC (examples in docs/examples), never from a public one.
Keep real configs, rosters, rulesets and job/result files out of this repo; .gitignore blocks the usual names.
Early release (v0.1), tested against mocked AWS: try a throwaway account first. Apache-2.0; see SECURITY.md and CONTRIBUTING.md.
1 maintainer
Metadata
1 maintainer
Release files for labagent 0.1.0
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