Invite-only beta · AWS SAA-C03 + GitHub Foundations
Study what matters next. Know why it matters.
CloudKata turns practice, mistakes, and delayed recall into a study plan and an honest readiness estimate—without pretending that activity is mastery.
Original practice content · Not affiliated with or endorsed by certification vendors
The method
A feedback loop built around retrieval
The point is not to fill a dashboard. It is to make your next study decision smaller, clearer, and better informed.
- 01
Start with a plan you can actually keep
Tell CloudKata your exam date, available hours, and study days. The daily queue stays inside that capacity and explains why each activity is useful.
- 02
Practice recall, not page completion
Quizzes, scenario decision drills, spaced flashcards, and timed mock exams produce the evidence that passive reading cannot.
- 03
Repair the miss, then retrieve it later
Wrong answers become named misconceptions and review material. Delayed recall matters more than a lucky first attempt.
Available in the first version
Two complete paths, one learning engine
Study AWS Solutions Architect – Associate or GitHub Foundations. Each track has source-linked lessons, original practice, recall, labs, timed simulation, and the same evidence and release gates. Kubernetes remains preview-only.
- AWS SAA-C03 and GitHub Foundations guides mapped to official blueprints
- Adaptive daily queue with time and evidence rationale
- Quizzes, scenario drills, spaced review, and mock exams
- Wrong-answer journal and evidence-triggered replanning
- Grounded AI tutor with citations, uncertainty, and spend caps
- Readiness estimates with coverage and evidence sufficiency
Honest by construction
The game cannot inflate readiness.
Readiness is rebuilt from scored, attributed learning evidence. Participation may help a habit, but guide reads, reflections, XP, streaks, and virtual resources do not become correctness or exam coverage.
Private beta
Ready to earn the first evidence?
Enrollment is currently limited to invited addresses while the real learning loop, content, cost controls, and operations are tested with a small audience.