Objective & prerequisites
Create a reviewable fictional resource inventory with ownership and cost assumptions. Prerequisites: Python functions, JSON, basic SQL, Git and the existing software/testing workshops. Extract the full kit and open a terminal in cloud-operations-kit. Python 3.10+ with its standard SQLite module is sufficient for the executed labs; no cloud account, credentials, package installation or network is needed. All data and prices are invented teaching fixtures. The runnable drills use new temporary folders and databases, never the website or hosting. These free companions retain existing course progress/access. Payments and public registration remain disabled.
python3 lab.py
python3 -m unittest discover -s tests -vUnderstand the concept
A cloud sandbox needs an identified account owner, approved region, necessary data scope, least-privilege access, spending review and cleanup evidence. Authentication is not permission to every resource. Use service-specific actions/resources and temporary credentials where supported; a broad administrator policy is not a suitable default for a learning lab. Budget alerts are notifications and can lag; they are not automatically a hard spending cap. Deleting one visible compute resource may leave storage, snapshots, addresses, logs or other chargeable resources. A teardown plan must enumerate dependencies, retention exceptions and post-cleanup inventory/billing review. This lesson writes a plan only and never connects to a cloud account.
Worked example
The plan uses deliberately invented unit rates: 720 compute hours×2 cents=1440, 10 storage units×3=30, and 5 egress units×10=50, totaling 1520 cents for a hypothetical forgotten 30-day footprint. These are not AWS or Aruba prices. The fictional budget is 2000 cents with an 80% alert threshold of 1600. The two-hour expiry is an owner review/cleanup target, not an automated deletion mechanism or a two-hour billing estimate. The checker rejects public access and non-fictional data, but cannot inspect real IAM, encryption, account budgets or actual bills.
from lab import cloud_plan,load
r=cloud_plan(load("cloud-plan.json"))
assert r["estimated_cents"]==1520
assert r["alert_threshold_cents"]==1600
assert not r["alert_in_example"]Try it yourself
Complete cloud-sandbox-plan-template.txt and iam-review-worksheet.txt without real credentials. Recalculate an egress increase, list which resources require cleanup and record evidence needed to confirm removal. Explain why passing the JSON checker is not permission to deploy or proof that all provider charges stop. Predict the result first, keep the original fixture, and record the exact command and observed outcome from your practice copy.
Worked solution
The baseline monthly-if-forgotten estimate is 1520 cents and does not reach the 1600 example alert. Raising egress to 50 units produces 1970 cents and triggers the illustrative threshold; 100 units produces 2470, above the example budget. The owner must separately authorize any real account, prices, spending limit and resource plan before a live lab. Inventory and billing may update at different times, so retain verified teardown evidence and investigate leftovers.
Knowledge check
Does an 80% budget notification prevent any spend beyond the budget?
Check and explain
No. Notification and enforcement are distinct, and provider reporting/actions have timing and coverage limits.
Evidence, mistakes & handover
State whether an activity was executed locally, reviewed as a design, or left unexecuted. A successful local drill does not verify a cloud provider, container, hosted pipeline or production recovery. Keep an owner, acceptance criteria, known failures and rollback/cleanup evidence with the work. The download includes source fixtures, runnable drills/tests, separate exercises and solutions, a runbook, a resource plan, an optional container/CI review pack and a capstone rubric. Credit the teaching baseline and your own contribution; no certification, commercial service or employment guarantee follows.
Authoritative reference
— primary/official reference for the mechanism. Lesson explanations and fictional cases are original. Provider details can differ; this lesson does not configure or provision an account. No production access, payment, public registration or live deployment is activated.
Try the activity before reading its reference. Keep your sources, commands and assumptions with your work. Companion activities are unsaved self-practice and do not award a certificate or change lesson progress.