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BlogLearnThe best way to architect web scraping solutions | Zyte
LearnScraping strategy

The best way to architect web scraping solutions | Zyte

C

Colm Kenny

·

6 min read · March 28, 2019

How to architect a web scraping solution: The step-by-step guide

For many people (especially non-techies), trying to architect a web scraping solution for their needs and estimate the resources required to develop it, can be a tricky process.

Oftentimes, this is their first web scraping project, and as a result, have little reference experience to draw upon when investigating the feasibility of a data extraction project.

In this series of articles, we’re going to break down each step of Zyte’s four-step solution architecture process so you can better scope and plan your own web scraping projects.

  • Step 1: Define your data requirements
  • Step 2: Conduct a legal Review
  • Step 3: Evaluate the technical Feasibility
  • Step 4: Architect a solution & estimate resources

At Zyte we have a full-time team of solution architects who architect over 90 custom web scraping projects each week for everything from e-commerce and media monitoring, to lead generation and alternative finance use cases. So odds are if you are thinking of investigating a web scraping project our team has already architected a solution for something very similar.

As a result, throughout this series, we will be sharing with you the exact checklists and processes we use, along with some insider tips and rules of thumb that will make investigating the feasibility of your projects much easier.

In this overview article, we’re going to give you a high-level overview of our solution architecture process so you replicate it for your own projects.

Step 1: Define your data requirements

The ultimate goal of the requirement gathering phase is to minimize the number of unknowns, if possible to have zero assumptions about any variable so the development team can build the optimal solution for the business need.

This is a critical process for us at Zyte when working on customer projects so we can ensure we are developing a solution that meets their business need for web data, manage expectations and reduce risk in the project.

However, the same is true if you are developing a web scraping infrastructure for your projects. Accurately capturing the project requirements will allow your development team to ensure your web scraping project precisely meets your overall business goals.

Here you want to capture two things:

  1. Your user needs - what business or personal objective do you want to achieve? How will web data help you achieve this objective?
  2. Your data requirements - precisely what data do you need to achieve your business or personal objective? From which websites and how often? etc.

It is critical for you and/or your business that your data requirements accurately match your underlying business goals and your need for the data. A constant supply of high-quality data can give your business a huge competitive edge in the market, but what is important is having the right data.

It is very easy to extract data from the web, what’s difficult is extracting the right data at a frequency and data quality that makes it useful for your business processes.

With every customer we speak with, we dive deep into their underlying business goal to better understand not only their specific data requirements but also why they want the data and how it fits into the bigger picture. Because oftentimes, our team of solution architects is able to work with them to find the alternative or additional data sources for their specific requirements that better suit their business goals.

However, when investigating the feasibility of any web scraping project you should always be trying to clarify:

  • What data do you require? i.e. the precise data you want to obtain during the scraping process.
  • From which websites would you like to obtain this data?
  • How often would you like to extract this data? Daily, weekly, monthly, once-off, etc?
  • How do you want to consume the data?
  • How will you verify that the extracted data is accurate? i.e. matches exactly the data on the target websites?
  • How would you like to interact with the solution? i.e would you just like to receive data at a predefined frequency, or would you like to have control over the entire web scraping infrastructure and the associated source code?

Read this article where we walk you through the exact steps our team uses to gather project requirements and scope the best possible solution to meet them.

Step 2: Conduct a legal review

The second step of any solution architecture process is to check if there are any legal barriers to extracting this data.

With the increased level of awareness about data privacy and web scraping in the last number of years, ensuring your web scraping project is legally compliant is now a must. Otherwise, you could land yourself or your company in a lot of difficulties.

Learn more about our exact legal assessment checklist that our solution architecture team uses to review every project request we receive. Our legal team has created a best practice guide for the solution architecture team to utilize so they know when to flag a project with legal for a review. Once flagged with legal, our legal team will review the project based on the criteria below, as well as others, to determine if we are able to proceed with the project.

However, in general, you need to be assessing your project against the following criteria:

  1. Personal data - will your web scraping project require you to extract personal data? If yes, where do these people reside? Are you complying with the local regulations? GDPR comes to mind.
  2. Copyrighted data - is the data being extracted subject to copyright? If so, are there any exceptions to copyright that you may avail of
  3. Database data - a subset of copyright, does the website the data is being extracted from have database rights?
  4. Data behind a login - to extract the data do you need to scrape behind a login? What do the website’s terms and conditions state regarding web scraping?

If your answers to any of the above questions raise concerns, you should be ensuring that a thorough legal review of the issue is conducted prior to scraping. Once you've completed this review then you are in a good position to move forward to assessing the technical feasibility and architecting your web scraping solution.

Step 3: Technical feasibility

Assuming your data collection project passed the legal review, the next step in the solution architecture process is to assess the technical feasibility of executing the project successfully.

This is a critical step in our solution architecture process and a step most independent developers working on their own or for their company’s projects overlook.

There is a strong tendency amongst developers and business leaders to start developing their solution straight away. For simple projects this often isn’t an issue, however, for more complex projects, developers can quickly discover that they run into a brick wall and can’t overcome the challenges.

We’ve found that a bit of upfront testing and planning, can save countless wasted man-hours down the line if you start developing a fully-featured solution only to hit a technical brick wall.

During the technical review phase, one of our solution architects will examine the website and run a series of small-scale test crawls to evaluate the technical feasibility of developing a solution that meets the customer’s requirements (crawl speed, coverage, and budgetary requirements).

These tests are primarily designed to determine the difficulty of extracting data from the site, will there be any limitations on crawl speed & frequency, is the data easily discoverable, is there any post-processing or data science requirements, does the project require any additional technologies, etc.

Once complete, this technical feasibility review gives the solution architect the information they need to first determine if the project is technically feasible, and then what is the optimal architecture for the solution.

Read this article to get behind the scenes look at some of the tests we carry out when assessing the technical feasibility of our customer’s projects.

Step 4: Architect a solution & estimate resource requirements

The final step in the process is architecting the solution and estimating the technical and human resources required to deliver the project.

Oftentimes, the solution needs to be approached and scoped in phases, to balance the tradeoff of timelines, budget, and technical feasibility. Our team will propose the best first step to tackle your project while keeping the bigger goal in mind.

Here you need to architect a web scraping infrastructure using the following building blocks:

  • Crawler architecture - data discovery and extraction architecture spiders.
  • Spider deployment
  • Proxy management
  • Headless browser requirements
  • Data quality assurance
  • Maintenance requirements
  • Data post-processing
  • Any non-standard technologies that might be required

Read this article to get a glimpse of the process we use to architect a solution, give examples of real solutions we have architected and the resources required to execute them.

Once a solution has been architected and the resources estimated, our team has all the information they need to present the solution to the customer, estimate the cost of the project, and draft a statement of work capturing all their requirements and the proposed solution.

Your web scraping project

If you have a need to start or scale your web scraping project then our Data Scraping experts are available for a free consultation, where we will evaluate and architect a data extraction solution to meet your data and compliance requirements.

Learn more about architecting a web scraping solution

At Zyte we have extensive experience architecting and developing data extraction solutions for every possible use case.

Our legal and engineering teams work with clients to evaluate the technical and legal feasibility of every project and develop data extraction solutions that enable them to reliably extract the data they need.

Here are some of our best resources if you want to deepen your web scraping knowledge:

  • Solution architecture part 2: How to define the scope of your web scraping project
  • Solution architecture part 3: Conducting a web scraping legal review
  • Solution architecture part 4: Accessing the technical feasibility of your web scraping project
  • Solution architecture part 5: Designing a well-optimized web scraping solution
  • The build in-house or outsource decision

FAQs

What is the first step in architecting a web scraping solution?

The first step is to define your data requirements, which includes understanding the data needed and the objectives behind the project.

Why is a legal review necessary for web scraping projects?

A legal review ensures that your web scraping project complies with regulations such as GDPR, copyright laws, and website terms of service.

How do you assess the technical feasibility of a web scraping project?

The technical feasibility is assessed by testing the website, evaluating crawl speed, coverage, and potential limitations, as well as identifying any additional requirements.

What factors are considered when architecting a web scraping solution?

Factors include crawler architecture, spider deployment, proxy management, data quality assurance, and any specific maintenance or post-processing needs.

How are resources estimated for a web scraping project?

Resources are estimated by considering the required infrastructure, technologies, team size, and the phases needed to balance budget and project goals.

In this article

  • Step 1: Define your data requirements
  • Step 2: Conduct a legal review
  • Step 3: Technical feasibility
  • Step 4: Architect a solution & estimate resource requirements
  • Your web scraping project
  • Learn more about architecting a web scraping solution
  • FAQs
  • What is the first step in architecting a web scraping solution?
  • Why is a legal review necessary for web scraping projects?
  • How do you assess the technical feasibility of a web scraping project?
  • What factors are considered when architecting a web scraping solution?
  • How are resources estimated for a web scraping project?

Selected chapter & lessons

What is web scraping?

  • What Is Web Scraping?
  • What are the elements of a web scraping project?
  • Python Web Scaping Tools & Libraries
  • How to architect a web scraping solution: The step-by-step guide
  • Web crawling vs web scraping
  • Is Web & Data Scraping Legally Allowed?
  • Compliant Web Scraping Checklist
  • Best practices for web scraping
  • A Guide to Web Scraping With Java
  • Transition from Zenrows to Zyte API
  • Guide to Web Scraping APIs
  • Screen Scraping Explained
  • Large Scale Web Scraping with Python
  • Large Scale Web Scraping with Python
  • Building a Web Crawler in Python
  • A Practical Guide to XML Parsing with Python
  • Learn How to Scrape a Website
  • Advanced Use Cases for Session Management
  • Golang Web Scraping in 2025
  • Web Scraping Dynamic Websites With Zyte API
  • What is Data Parsing in Web Scraping?
  • Scrape Web Pages and Files Using Python, wget, and Zyte

Other lessons

Learn Scrapy

  • Scrapy Tutorial Part 1: First Spider
  • Scrapy Tutorial Part 2: Page Objects
  • Scrapy Tutorial Part 3: Web Scraping CoPilot

Web Scraping How-to Videos

  • Web scraping videos

SERP Data Collection at Scale

  • SERP data collection at scale and why efficiency matters
  • Why Page One SERP data is no longer enough
  • Why pagination logic becomes operational debt
  • Why SERP data costs exploded

What is web scraping used for?

  • What is web scraping used for?
  • Pricing Intelligence Web Scraping
  • Web Scraping For Market Research
  • Use web scraping to build a data-driven product
  • Use web scraping for alternative data for finance
  • Use web scraping for brand monitoring
  • Use web scraping to automate MAP compliance
  • Web Scraping For Lead Generation
  • Web Scraping For Recruitment
  • Use web scraping for business automation
  • Using Data Extraction Tools for Efficient Website Scraping
  • Why Might a Business Use Web Scraping to Collect Data?
  • How to Scrape Images from Any Website: A Complete Guide
  • How to Scrape Search Engine Results

The New Guide to Web Scraping at Scale

  • Introduction
  • 1. A plan is a pathway to success
  • 2. Get serious about legal compliance
  • 3. The quality of your web data is of utmost importance
  • 4. Scaling and maintaining crawling and extracting solutions
  • 5. Adding AI to the web scraping stack
  • 6. The In-house vs outsourced question
  • 7. Questions to ask when scaling web scraping

Essential Web Scraping Techniques

  • TLS Fingerprint and how it blocks requests
  • How to scrape with a browser effectively
  • API First data extraction

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