Aligning Protected Storage Capture and Restore Contracts in AlterLab

TL;DR

AlterLab repaired the protected-storage producer/consumer contract that was blocking promotion from staging to main. The fix aligns capture and restore semantics, preserves database snapshots, redaction, financial, and usage contracts, and classifies mixed-volume paths by meaning rather than file extension.

The Problem: A Broken Producer/Consumer Contract

AlterLab’s protected storage layer stores scrape results, snapshots, and metadata. Two sides interact with it:

• Producer – the capture process that writes new data after a scrape.
• Consumer – the restore process that reads data for retries, audits, or downstream pipelines.

A contract between these sides guarantees:

1. Database snapshots remain consistent.
2. Redaction rules are applied uniformly.
3. Financial and usage metering stays accurate.
4. Object‑class requirements (e.g., encryption, retention) are honored.

During a recent staging→main promotion, the contract failed because capture and restore were classifying storage objects differently. Capture used MIME‑type detection; restore relied on file extensions. This mismatch meant a restored object could inherit the wrong encryption class or retention policy, violating snapshot and financial guarantees.

Solution: Align Capture and Restore Semantics

The fix involved three steps:

1. Unified Classification Logic – Both producer and consumer now run the same semantic‑path classifier. Instead of checking .json or .html, the system examines the meaning of the path (e.g., “scrape‑result”, “snapshot”, “redacted‑log”) and applies the appropriate object class.
2. Contract‑Preserving Transforms – All transforms (redaction, compression, encryption) are expressed as pure functions of the classified object class. This ensures that applying a transform during capture yields an identical result when the same transform is applied during restore.
3. Metadata Versioning – A version field was added to stored objects. If a consumer encounters an older version, it can safely upgrade or downgrade using a documented migration path without breaking snapshots or usage contracts.

The result is a bidirectional contract: any object written by the producer can be read by the consumer with guaranteed fidelity, and vice‑versa.

Classifying Mixed‑Volume Semantic Paths, Not Extensions

AlterLab’s storage spans multiple volumes (hot SSD, warm NAS, cold archive). Previously, routing decisions were based on file extension, causing:

• Mis‑routed snapshots (e.g., a .json snapshot sent to cold storage despite needing fast restore).
• Inconsistent redaction (a redacted log mistakenly treated as raw data).
• Usage‑meter drift (objects counted against the wrong volume tier).

The new classifier examines:

• Path prefix (/scrape-result/, /snapshot/, /audit/)
• User‑defined tags (e.g., pii:true, retention:30d)
• Content hints (first‑kilobyte analysis for structured vs binary data)

Based on these signals, the system assigns an object class that determines:

• Target volume (hot/warm/cold)
• Encryption profile
• Retention policy
• Usage‑meter label

This semantic approach eliminates extension‑based edge cases and makes the producer/consumer contract deterministic across all volumes.

Code Example: Capturing a Scrape Result with Protected Storage

Below is a Python snippet showing how a capture job stores a scrape result using the updated contract. The example uses AlterLab’s Python SDK and demonstrates setting semantic tags that drive classification.

import alterlab
from alterlab.storage import StorageObject, ObjectClass

# Initialize client (alterlab.io web-scraping-api-python)
client = alterlab.Client("YOUR_API_KEY")  # highlighted

# Perform a scrape (any target URL)
scrape_resp = client.scrape(
    url="https://example.com/products",
    params={"render": True, "format": "json"}
)  # highlighted

# Build a storage object with semantic tags
obj = StorageObject(
    bucket="scrape-results",
    key=f"scrape-result/{scrape_resp.id}",
    body=scrape_resp.text,
    tags={
        "type": "scrape-result",
        "source": "e-commerce",  # generic category, not a specific site
        "pii": "false"
    },
    obj_class=ObjectClass.from_tags({"type": "scrape-result", "pii": "false"})
)  # highlighted

# Store via protected storage API (internal contract)
client.storage.put(obj)  # highlighted

What this does:

• The scrape result is tagged as type:scrape-result.
• The StorageObject constructor derives the correct ObjectClass from those tags.
• client.storage.put routes the object to the appropriate volume, applies encryption, and updates usage meters—all guaranteed by the restored producer/consumer contract.

Code Example: Restoring a Scrape Result via cURL

The following cURL command shows how a consumer (e.g., a retry worker) retrieves the same object, relying on the aligned contract to receive identical metadata and content.

curl -X POST https://api.alterlab.io/v1/storage/get \
  -H "X-API-Key: YOUR_KEY" \
  -d '{
        "bucket": "scrape-results",
        "key": "scrape-result/12345-abcd",
        "tags": {
          "type": "scrape-result",
          "source": "e-commerce",
          "pii": "false"
        }
      }'  # highlighted

Key points:

• The request repeats the semantic tags used during capture.
• The storage service consults the shared classifier, selects the same object class, and returns the object with its original encryption and retention settings.
• Because the contract is symmetric, the consumer can trust that the restored byte stream matches what the producer originally wrote.

Infographic: Capture → Store → Restore Flow