Prompt

How do I crawl millions of pages without building infra?

Technology / Cloud Infrastructure1 observationLast seen Oct 4, 2026

Latest observation

Oct 4, 2026OpenAI APIWeb search: off

If you want to crawl millions of pages without building infrastructure, the easiest path is to use a managed crawling/extraction service rather than running your own browser fleet, proxies, queues, retries, and storage.

Best options

1) Managed web scraping APIs

These handle:

  • fetching pages
  • rotating IPs / proxies
  • retries / rate limits
  • browser rendering for JS sites
  • anti-bot handling
  • sometimes extraction to structured JSON

Examples:

  • Apify
  • Zyte
  • Bright Data
  • ScrapingBee
  • Zenscrape
  • Oxylabs

Good when you need scale fast and don’t want ops work.

2) Cloud crawl platforms

These are closer to “run a crawler as a service”:

  • define URLs, rules, and extraction
  • they run workers for you
  • can export to S3, BigQuery, webhook, CSV, JSON, etc.

Examples:

  • Apify actors
  • Zyte API / Scrapy Cloud
  • Diffbot for extraction-heavy use cases

3) Headless browser orchestration services

If pages require JS rendering:

  • use a service with managed Playwright/Puppeteer
  • you write the crawl logic, they manage the compute

Examples:

  • Browserless
  • Apify
  • Zyte

A practical approach

For millions of pages, don’t think “single crawl job.” Think:

  1. Seed URLs
  2. Distribute crawl tasks
  3. Deduplicate URLs
  4. Throttle by domain
  5. Store raw HTML + metadata
  6. Extract data separately
  7. Resume from checkpoints

Managed platforms usually give you most of this.


If you want the simplest setup

A common low-infra stack is:

  • Apify or Zyte for crawling
  • S3 / GCS for raw page storage
  • BigQuery / Postgres / Elasticsearch for processed data
  • Airflow / Make / simple scripts only for orchestration, if needed

How to choose

Choose managed scraping if:

  • you need millions of pages
  • sites are dynamic or protected
  • you want to avoid proxy/browser maintenance
  • speed matters more than lowest possible cost

Choose your own crawler if:

  • you have a dedicated infra team
  • crawl logic is highly custom
  • cost at massive scale outweighs convenience

Important considerations

  • Respect robots.txt and site terms
  • Rate limit per domain
  • Expect failures and retries
  • Store raw responses so you can reprocess without recrawling
  • Use incremental crawling after the initial bulk crawl

Recommended starting point

If you want minimal engineering effort:

  1. Use Apify or Zyte
  2. Start with a small crawl of 10k–50k pages
  3. Measure:
    • success rate
    • cost per 1k pages
    • JS rendering needs
    • anti-bot friction
  4. Scale to millions once stable

If you want, I can recommend the best service based on your site type:

  • static pages
  • JS-heavy pages
  • e-commerce
  • news/content sites
  • login-required sites

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as Circuit. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

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