How to scale your web scraping

INTRODUCTION

As the digital world keeps evolving, many businesses have become reliant on data to make informed decisions, increase customer base, enhance operations among others. As popularly phrased, Data is the lifeblood of every businessI  However, many businesses are faced with numerous challenges trying to scrape this data.

A lot of organisations have gone ahead to employ developers to build and manage scrapers but is this truly effective?

Scrapers are slow to build and difficult to maintain, thereby impacting the business productivity.  Statistics show that 98% of scrapers break. 51% reporting it happens monthly or more frequently as eCommerce scraping scales

This is because websites change structure frequently and a  large proxy pool is required to scrape at scale. Scraping becomes hard to scale as websites continually update Bot protection, hence businesses spend a lot of CAPEX, time and human resource building on-prem solutions.

It has become expedient for businesses to leverage cloud-based data-as-a-service solutions using pre-built extractor. This eliminates time wasters, embracing a Pay-As-You model, with fully automated processes and ready made solutions (pre-built) Cloud Infrastructure. This also includes large pool of rotating proxies and fully managed and maintained scrapers

How is this possible? Let’s dive in:

3 Key Strategies to scale your web scraping 

Strategy 1:  Build a large proxy pool and management system

1. Define how many proxies you will need; A formula for this is; Number of proxies= number of access requests/crawl rate. Access rate depends on the frequency at which a scraper is crawling a website e.g. every minute/hour/day. A crawl rate is limited by the request/user/time period that is allowed by the target website (most websites only allow a limited number of requests within a minute before blocking that IP)

2. Define where those proxies should be located; A regionally based website will only expect traffic from its country so will block large traffic from elsewhere. Hence use relevant regional based IP’s

3. Understand the type of the proxies required(data centre or residential). Since residential and mobile IPs are most likely to be legitimate users, these are the most coveted IPs by web scrapers. However, they are harder to acquire and are usually slower.

4. Multi-Vendor Strategy; As a risk management strategy always have multiple proxy vendors and rotate between their proxies

5. Proxies Rotation Management: To allow your IP’s to be refreshed regularly use a rotating proxy manager. This will allow you to assign an IP from a large pool for each connection request. Also remember to refresh banned IP’s periodically.

Strategy 2: Build a resilient infrastructure architecture

1. Build a Data pipeline: building an automated pipeline to transfer web scraping data to its destination is key. Typically the first step will be creating a script that triggers a transfer of the raw data into object storage, a CRM or a database. The design here is key

2. Cloud Storage: A Large scale extraction generates a huge volume of data. This requires a strong infrastructure on data warehousing to be able to store the data securely.

3. Cloud servers that auto scale; Scraping is very compute heavy, as the number of requests sent to the website increase more computing power is needed

4. Scraping Frameworks: this is key to the longevity and flexibility of your web scrapers. The most responsible choice is to build on an open-source framework – this not only offers you a great deal of flexibility if you want to move your scrapers around later on, but it always offers the greatest degree of customization due to the sheer amount of users working with the tool and tailoring it in interesting ways. Also, use a popular framework like Scrapy. This will allow you to choose from a wide pool of developers from the development community.

Strategy 3: Have hybrid automated/manual monitoring

1. Build automated monitoring checks; building simple automated checks like

• Count of no of rows returned

• Are you getting any unexpected responses like 404

• Are there missing/empty columns

Getting any errors should trigger a developer to take action and fix any issues

2. Have a QA process:

• Build an automated monitor to validate data against its requirement

• Manually examine sample data and do a visual comparison with the scraped pages

Get started with WebAutomation for Free today!

At WebAutomation.io, we make the process of extracting web data quick and efficient so you can focus your resources on what’s truly important, using the data to achieve your business goals. In our marketplace, you can choose from hundreds of pre-built extractors for the world’s biggest websites.

These pre-built data extractors turn almost any website into a spreadsheet or API with just a few clicks. The best part? We build and maintain them for you! Using WebAutomation lowers costs, requires no programming, enables you to get started quickly since we build the extractors for you, and means you’ll always have the help you need to keep your extractor running since we handle all the backend security and maintenance.

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