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<!doctype html><html lang="en"><meta charset="utf-8"><title>Durable storage and restore tests</title><h1>Durable storage and restore tests</h1><p>15-minute session: read for 3 minutes, trace for 3, experiment for 7, and complete the check for 2. Spend longer whenever you need.</p><p>A backup is useful only if it restores the data and required metadata. Plan consistent database and repository snapshots together. A checksum detects changed bytes; it does not prove a database is logically valid. Define a recovery-point target and recovery-time target. Practice a restore in an isolated environment before an outage.</p><p><strong>Practice and evidence:</strong> Predict the example or draw its state transitions. Change one assumption, test the boundary, and record the actual result. Explain what this small model does not establish about a production system.</p><pre><code class="language-python">import hashlib
original=b&quot;study record v1&quot;
restored=bytes(original)
assert hashlib.sha256(original).digest()==hashlib.sha256(restored).digest()
print(&quot;Bytes match; application checks still needed&quot;)
</code></pre><p><strong>Expected result:</strong> <code>Bytes match; application checks still needed</code></p><h3>Practice and evidence</h3><p>Keep three notes: your prediction, the actual result, and why they match or differ. The completion check grades understanding; the practice task builds skill.</p></html>