Web crawling has become a must-have tool to stay relevant in this competitive and highly volatile market which is unforgiving of mistakes. A few notable ones among the countless applications of web crawling are Natural Language Processing, Brand Monitoring, Price tracking, and Competitor Monitoring. With this rising need to have the ability to crawl the web, businesses are now looking at different ways to go about web scraping.
We agree it can be a really confusing feat given web scraping being still in its nascent stages of adoption. We have even come up with a framework to help you make an informed decision while on the lookout for ways to scrape the web. The options range from DIY tools to fully managed web scraping solutions like ours.
However, we will be talking about in-house crawling in particular here. One of the major issues faced by companies that have set up an in-house crawling team is the scale and customization aspect of their homegrown solution. This is typical because web crawling is a domain of its own which needs special expertise and technical resources. If you have somehow taken up the challenging path of in-house extraction, worry not as we are happy to share some tips to help you succeed.
When it comes to the web, things are always changing. The standards are not fixed and websites might use their proprietary techniques to improve user experience which could pose a challenge to the crawlers. A good example is the AJAX-based “Load More” buttons you see on many websites nowadays. While these advancements are great from a normal user’s point of view, web crawlers will have a tough time adapting.
This brings us to the most important aspect of scaling your in-house web crawling capabilities – updating your technical know-how. It’s imperative to be up to speed with the technical advancements concerning the world wide web. While this automatically comes to you if you’ve been in the web crawling space for long enough, companies that have just set up an in-house team for crawling will have to start from scratch. Another roadblock that likely affects the scale of your operations is the blocking mechanism used by websites to discourage automated crawling.
If your target site blocks aggressively, you’ll have to come up with workarounds either by limiting the frequency of requests to an acceptable one, using proxies, mimicking a real user in terms of behavior or more. Once you have the tech know-how to deal with these unforeseen issues while crawling the web, you will be able to scale your crawling process with some stability.
As a DaaS provider, we have come to realize that no matter how much you automate the processes, web crawling will always (until the arrival of a full-fledged AI) require a lot of human intervention. This is why having a larger team is crucial to keep your crawling systems running in good health. Web crawling is also a time-sensitive domain, meaning you can miss out on important data even if your crawler has been down for only 5 minutes. However, you might want to make sure the ROI from web scraping outweighs the total spend on your in-house web crawling team. This is one of the primary reasons why many of our existing clients moved away from in-house crawling to our managed web data extraction services.
While the term web crawling might make it sound like a straightforward process, there are so many steps involved between sending get requests to a server and deriving the data in a usable format for consumption. Following are the necessary components of a scalable web crawling setup.
1. HTTP Fetcher: This will extract the webpages from the target site servers. The fetching component is basically the system which has been programmed to navigate through the site and fetch the necessary pages in an orderly format. The anti-blocking mechanisms developed for a site usually docks to the fetcher.
2. Dedup: This makes sure that the same content is not extracted more than once. Deduplication improves the quality of the output data to a great extent by removing duplicate data points.
3. Extractor: URL retrieval system from external links.
4. URL Queue Manager: This lines up and prioritizes the URLs to be fetched and parsed.
5. Database: The place where the data extracted by web scraping will be stored for further processing or analysis.
The constant need for optimizing the crawling infrastructure is something that most businesses overlook. As we discussed earlier, the dynamic nature of the web causes the crawlers to become obsolete from time to time. Keeping up with this pace and optimizing your system to match the increasing complexity of the web is something that cannot be stressed enough.
As you have probably figured out by now, a scalable web scraping system has to be one that includes specialized components to take care of different stages of crawling. Not to forget, the tech-know-how of your team and the team strength will also play a huge part in how scalable your setup turns out to be. If you’d rather not endure the challenges of in-house crawling, you could instead switch to a managed service provider like PromptCloud. Being a fully managed service, we take end-to-end ownership of all the stages in crawling and deliver the data in a ready-to-use format.