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Cloud Web Scraping

Automate web data collection with a cloud web scraper

Octoparse runs the tasks you build on its cloud servers, so large-scale, scheduled collection keeps going with your PC off, with requests spread across rotating cloud IPs instead of your own connection.

See how it works

Cloud extraction and scheduled runs are available on the Standard Plan and above.

How a cloud task runs

The flow after setup, at a glance

Running

Schedule

Starts daily at 09:00

Enabled

Cloud extraction

Runs without your PC

Data export

Saved in your chosen format

Run times and results vary with the target site and your task settings.

Cloud-based web scraping, not tied to your PC

Scheduled runs, parallel tasks, IP rotation, and automatic export after each job, all on Octoparse cloud servers.

PC OFF

Your local machine stays free

Cloud jobs don't need Octoparse open on your PC. Even long runs leave your team's machines free.

Included in your plan

24h × 30d

Runs all month, not metered

On the Standard Plan and above, cloud extraction is part of your monthly or annual subscription, not billed by run time or by record.

Cloud server count, concurrency, and task limits vary by plan; some templates are priced separately.

See pricing plans

24 hours

Jobs keep running in the cloud

Tasks run in the Octoparse cloud, independent of your PC's power state or office network.

Minute to month

Scheduled to your refresh rate

Set schedules by minute, hour, day, week, or month to track prices, store listings, and more.

Multiple tasks

Parallel runs as you scale

Run a task per target site in parallel, within your plan's run slots and cloud server count.

IP rotation

Cloud IPs rotate per subtask

Runs use Octoparse cloud IPs, not your PC's, rotated per subtask and reassigned each run so your IP isn't throttled by concentrated requests.

From setup to scheduled cloud runs

Four steps: build the task, configure the run, set a schedule, and export the data.

  1. STEP 01

    Build your task

    Configure the fields and page actions yourself for a custom task, or start from a ready-made template.

    Two ways to build a task

    1. 1

      Load the target URL and set clicks, pagination, login, and fields on screen. Handles complex pages.

    2. 2

    Saved tasks can be reused; cloud runs and schedules come next.

    Custom task
    A data collection workflow built with a custom task in Octoparse
    Google Maps store listingsTemplate
    The Google Maps store listings template screen
  2. STEP 02

    Configure the run

    Set the built-in browser and pick a cloud server group by country or region to match the target site. Turn on incremental extraction to fetch only newly added pages.

    • Set the built-in browser and User-Agent
    • Choose a cloud server group by country or region
    • Split a task for parallel runs, based on your plan
    • Incremental mode fetches only newly added pages
    Run environment and incremental settings
    The custom task run settings screen for the built-in browser, cloud server groups, and incremental extraction
  3. STEP 03

    Set a web scraping schedule

    Add a schedule from the task's scheduled-runs menu, and it runs automatically in the cloud from then on.

    • Set the run frequency and start time
    • Run once without a schedule by choosing Cloud Extraction at start; it finishes on Octoparse servers even after you close the app
    • Or start runs from the Octoparse CLI, tied to cron, CI/CD, or your own job scheduler
    Learn more about the CLI
    Set the frequency and start time
    Setting a cloud extraction schedule in the Octoparse desktop app
  4. STEP 04

    Save and integrate

    Export to Excel, CSV, JSON, Google Sheets, databases, or cloud storage such as Google Drive, Dropbox, and Amazon S3. Tie automatic export to your schedule, and data lands as soon as a run finishes.

    Destinations and automatic export vary by plan.

    Choose the destination and format
    The Octoparse data export screen with Excel, CSV, database, and cloud storage options

Cloud web scraping vs. local vs. self-hosted Python

The right choice depends on how often you collect, your maintenance time, and how far you need to scale.

CriterionOctoparse cloud extractionOctoparse local extractionSelf-hosted Python (incl. VPS and Flask)
Best forRecurring monitoring, large-scale and parallel jobs, running without a PCTrials, small one-off jobs, checking results on the spotCustom logic or deep integration with internal systems
CodingNot usually neededNot usually neededDesign, development, and testing required
Scheduled runsAvailable on supported plansDepends on the machine being onYou build job management and incident handling
Operations and maintenanceFocus on task settings and reviewing resultsYou check the machine, network, and taskYou maintain code, servers, dependencies, and monitoring
Scaling upMultiple tasks within your plan's run slotsLimited by machine performance and uptimeServer capacity planning and run-control design

If an official API covers the data and refresh rate you need, check its terms first.

For recurring monitoring work

The more often you check the same thing under the same conditions, the more cloud scheduling pays off.

Browse all templates
01 / Store and company data

Recurring collection of store listings

Collect store names, addresses, phone numbers, hours, and categories by region and industry on a schedule.

Use a store listing template
02 / E-commerce and retail

Monitor prices and stock on Amazon and beyond

Regularly collect prices, stock, and reviews from Amazon and other sites to track changes and build history.

See the Amazon scraper
03 / Information monitoring

Track new articles, jobs, and listings

Capture the same fields from articles, job posts, and property listings as they are published.

See job templates
04 / Research and analysis

Build up data from multiple sites

Split tasks by target site and refresh frequency to accumulate data for weekly or monthly reporting.

See the Enterprise Plan

Large-scale automated web scraping in the cloud

Split tasks for parallel runs and organize them by target site and refresh frequency. Running in the cloud alone doesn't guarantee results, so plan to review the results and revise tasks as sites change.

Keeping collection running

  • Separate tasks by target site and refresh frequency
  • Split long tasks into smaller ranges across time slots
  • Review record counts, gaps, and run logs regularly
  • Fix the cause of failures and timeouts, then re-run

When you scrape the web, review the target site's terms of use, its robots.txt, personal data and copyright considerations, and the request load you generate.

FAQs about cloud web scraping

Automate your recurring web data collection

Build a task, decide your frequency and format, and check which plans include cloud extraction and scheduled runs.

See pricing plans