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Once you save a scraper to production in Bright Data Scraper Studio, you can trigger a collection run three ways (API, manual, or scheduled) and deliver the results in five formats (JSON, NDJSON, CSV, XLSX, Parquet) to six destinations (API download, webhook, S3, GCS, Azure, Alibaba Cloud OSS, SFTP, or email). This page covers every option.

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Prerequisites

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How do I save a scraper to production?

While you edit code in the Bright Data Scraper Studio IDE, the system auto-saves your work as a development draft. To make the scraper runnable outside the IDE, click Save to Production in the top-right corner of the IDE. All production scrapers appear under My Scrapers in the control panel. Inactive scrapers are shown faded.
My Scrapers dashboard showing saved scrapers

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How do I trigger a scraper run?

Bright Data Scraper Studio supports three ways to initiate a collection.
Start a collection through the REST API without opening the control panel. See Getting started with the API for authentication, request format, and response schema.Before you send a request, create an API key. Go to Dashboard > Account settings > API key.
Initiate scraper by API
The API-trigger panel gives you three things:
  1. Inputs: provide input values manually or through the API request body
  2. Trigger behavior: queue multiple requests to run in parallel or sequentially; queued jobs run in the order they are submitted
  3. Preview of the API request: Bright Data shows you a ready-to-run curl command. Select the Linux Bash viewer for curl. The response includes a job_id you use to fetch the data later.
When delivery is set to API download, you must call the “Receive data” API endpoint to retrieve results. Webhook and cloud-storage destinations push data automatically.

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What are the rate limits and concurrency limits?

Bright Data Scraper Studio enforces concurrency limits per scraper, based on whether the request is batch or real-time.
Collection typeConcurrency limit
BatchUp to 1,000 concurrent requests per scraper
Real-timeNo limit
When you exceed the batch limit, Bright Data returns this error: Maximum limit of 1000 jobs per scraper has been exceeded. Please reduce the number of parallel jobs.

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Batch vs real-time collection

Bright Data Scraper Studio offers two collection methods, each optimized for a different use case.
Batch collectionReal-time collection
Input sizeMany inputs per job (list of URLs or keywords)One input per request
Response timingResults returned after the full job completesResponse returned in real time
Retention16 days7 days
Concurrency limit1,000 concurrent jobsNone
Use whenYou are building a dataset and can waitYou need an answer inside a live request
Both methods are reliable. Pick the one that matches the shape of your application.

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How do I configure delivery?

Open My Scrapers, click a scraper row, and choose Delivery preferences to set where and how Bright Data Scraper Studio delivers results.
  • Batch: get results once the whole job finishes; efficient for large datasets
    • Split batch: deliver partial results in smaller chunks as they become ready
  • Real-time: get a fast response to a single request
    • Skip retries: do not retry on error (speeds up collection at the cost of completeness)
  • JSON
  • NDJSON
  • CSV
  • XLSX
  • Parquet
  • Email
  • API download (pull via REST API)
  • Webhook (push via HTTPS POST)
  • Cloud storage: Amazon S3, Google Cloud Storage, Azure Blob Storage, Alibaba Cloud OSS
  • SFTP / FTP
Media files cannot be delivered via Email or API download. Use cloud storage, SFTP, or webhook when collecting images, videos, or other binary content.
  • Results and errors in separate files
  • Results and errors in one combined file
  • Only successful results
  • Only errors
  • Notify when a collection completes
  • Notify on success-rate thresholds
  • Notify when an error occurs

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How do I configure the output schema?

The output schema defines the structure of your collected data: field names, data types, default values, and any additional metadata you want Bright Data Scraper Studio to attach (timestamps, screenshots, WARC snapshots). Output schema configuration
ControlDescription
Input / Output schemaTab switch for the two schema views
Custom validationDefine validation rules that run on every collected record
Parsed dataThe raw fields the scraper’s parser code emits
Add new fieldAdd a new field by name and type
Additional dataOptional metadata: timestamp, screenshot, WARC snapshot, and more

Scraper Studio specifications

Infrastructure limits, billing, and data retention

WARC snapshots

Archive raw HTTP responses alongside collected data