How To Use ScrapeOps for Web Scraping in 2025

ScrapeOps offers an integrated DevOps solution for monitoring and managing scraping tools. The platform is still gaining popularity, but feedback from users and reviewers has been mostly positive.

This article evaluates ScrapeOps’ main offerings, examining whether it is worth using to simplify the web scraping process and highlighting any limitations to be aware of.

What is ScrapeOps?

ScrapeOps is a comprehensive DevOps solution for web scraping projects, providing tools for monitoring and scheduling data scraping jobs, automating proxy management, and addressing scraping issues. It focuses on scraping processes rather than scraper construction or data storage.

Non-programmers will find little use in it because they must manually configure crawlers or parse pages. Once you have merged your existing web scrapers with the ScrapeOps services, the platform will be able to:

• Track each scraping run
• Aggregate metrics such as the number of pages or things scraped, success rates, or errors
• Compare those stats across runs.

While you are still responsible for writing the scraping scripts, ScrapeOps takes handle of the “ops” side of things (deployment, monitoring, and maintenance) in a single place.

ScrapeOps products:

1. Proxy API aggregator: It is a proxy management solution that integrates over 20 proxy providers into a single API. The tool manages IP rotation and CAPTCHAs, and automatically selects the right proxy for your requests based on price and performance. The proxy service supports GET and POST requests.
2. Scheduler & deployment: Incorporates automated job scheduling to schedule your scraping jobs at a predetermined interval. Additionally, you may specify the timeout duration for scraping tasks and whether you wish for the operation to terminate automatically after a specified number of pages have been scraped.
3. Monitoring: ScrapeOps offers real-time job monitoring for all scraping jobs that are currently being performed. You can easily monitor your scrapers and get information about HTTP status codes, timeouts, and request failures.

Main features:

1. ScrapeOps monitoring: Currently supports integration for Python Requests and Python Scrapy web scrapers. The platform can monitor the progress of each task in real time by incorporating the ScrapeOps SDK into your scraping code. It indicates statistics such as the number of pages scraped, the number of pages ignored, the success rate, the HTTP status codes, and the number of errors.
2. Custom health check alerts and reports: Users can establish their own criteria for what constitutes a “healthy” scraper job. The system then delivers alarm notifications to users based on these health checks. ScrapeOps also includes daily and weekly health reports, as well as historical health trends, which allow you to check back on the health of your scrapers over time.
3. Server provisioning and code deployment: Automatically adjust the number of servers based on the load or frequency of scraping processes to handle large-scale scraping projects. The platform includes features for smooth code deployment. You can link your GitHub repositories, allowing changes to your scraper code to be pushed immediately from your GitHub repository to the cloud server.
4. Fake browser headers API: To imitate real user traffic, employ randomized user-agent agents and additional browser headers.

How to integrate your existing scrapers with ScrapeOps

We conducted a small case study to test ScrapeOps using the free plan. Our tests involved sending requests to multiple social media platforms, including X (Twitter), TikTok, and LinkedIn, using NodeJS (Figure 1).

Figure 1: Sending requests to multiple social media platforms

ScrapeOps offers different proxy options and JavaScript rendering capabilities, which can be enabled through parameters in your API requests:

• residential=true : Routes the request through a residential proxy pool (Figure 2).
• premium=true: Uses premium datacenter proxies.
• render_js=true: Enables headless browser JavaScript rendering.
• wait_time=[seconds]: Specifies a delay to wait for dynamic content loading.

Figure 2: Below is a Node.js example to configure a ScrapeOps residential proxy request

Not all requests cost the same—the cost depends on the features enabled and the specific website being scraped (Figure 3).

General Costs:

• Basic request (no special features): 1 credit/request
  (Example: scraping X.com without proxies or JS rendering)
• Premium datacenter proxy (premium=true): 1.5 credits/request
• Residential proxy (residential=true): 10 credits/request
• JavaScript rendering (render_js=true): 10 credits/request

Domain-Specific Costs:

• LinkedIn has a higher base credit cost:
  • Each request to LinkedIn: 70 credits/request
• Easier social sites (TikTok, X) using residential proxies:
  • Approximately 10 credits/request

Figure 3: Domain-specific costs

Case study results (summary):

ScrapeOps pricing plan

ScrapeOps provides a free community plan and paid options for those with more complex requirements. The free plan offers basic features for monitoring an unlimited number of scrapers and pages.

ScrapeOpsproxy aggregator is a usage-based paid service that works on a credit system in which you pay for each successful request. This service provides 1000 free API credits but doesn’t offer a pay-as-you-go option. Residential proxy aggregator offers pay for bandwidth used.

The premium subscriptions start at $9 per month and contain 25,000 API credits for Proxy API Aggregator. Residential & Mobile Proxy Aggregator premium plans begin at $15 per month and contain 3GB. ScrapeOps offers monitoring and scheduling premium subscriptions starting at $4.95 per month.

Limitations or drawbacks

• Features still evolving: ScrapeOps is a relatively new platform, launched around 2022. Users may encounter a few “nice-to-have” features that are still on the roadmap, or certain features may not be entirely mature. ScrapeOps, for instance, does not provide a proxy stats API. It offers a proxy aggregation solution; however, the platform doesn’t provide access to detailed proxy statistics via an API.
• No built-in data storage: It’s important to mention if someone was hoping for a solution that could be used for both scraping and storing. ScrapeOps is more concerned with the scraping process than with the data itself. Data storage and post-processing are your responsibility.
• Initial learning curve: For the first time, using ScrapeOps can be a bit complicated because it is not a tool that can be used with a single click. You will need to incorporate an SDK or API into your scraper and establish a connection to your servers.