Jobrapido: Matching job-seekers with employers faster with Google Cloud Platform

About Jobrapido

Established in 2006, Jobrapido is one of the world's leading job aggregators operating in 58 countries. Using pioneering technology and innovative products, Jobrapido connects the dots between great employers and stellar candidates.

Industries: Technology
Location: Italy

Jobrapido used BigQuery to create a highly scalable data warehousing solution that handles billions of rows of data while minimizing costs and saving time.

Google Cloud Results

  • Handles over 125 million events per day with Cloud Pub/Sub and App Engine
  • Ingests, processes, and analyzes billions of rows of data with ease using BigQuery
  • Frees up engineers to work on developing new products instead of fussing over maintenance issues

BI analysis time cut to 30 minutes from 24 hours

Looking for a job can be a full-time activity all on its own. Jobrapido, one of the world's leading job search engines, aims "to take the work out of looking for work" for job-seekers and employers alike. Founded in 2006 in Milan, Italy, the company combines its hard-won years of expertise with cutting-edge techniques to match job-seekers with the appropriate employers as quickly and effectively as possible.

"Scaling had become a pain. We had availability issues and were running out of storage space. With Google Cloud Platform, we can let Google handle those problems while our engineers can go back to focusing on the business logic instead of fussing over the details of infrastructure."

Stefano Fornari, VP of Engineering, Jobrapido

Today, Jobrapido aggregates more than 20 million jobs per month for its 85+ million users across 58 countries. As the scale of its operations grew, the company put more and more strain on its infrastructure and IT resources. To cope with its rising demand, Jobrapido turned to Google Cloud Platform (GCP).

"Scaling had become a pain. We had availability issues and were running out of storage space," says Stefano Fornari, VP of Engineering at Jobrapido. "With Google Cloud Platform, we can let Google handle those problems while our engineers can go back to focusing on the business logic instead of fussing over the details of infrastructure."

Cloud-based convenience, seamless integration

A key ingredient for Jobrapido's success is the way it pairs job-seekers with opportunities. The company has invested in and developed a search engine that relies on the type of jobs rather than the specific job titles. By focusing its logic on the taxonomy of jobs instead of exact text matches, Jobrapido delivers a much wider range of relevant results to its users, which should enable them to find suitable work faster. As well as this, the company carefully monitors page views and impressions via its website and emails to make sure that its users are getting the right kind of jobs advertised to them.

With its unique matching logic and focus on data-driven operations, Jobrapido kept adding to its servers' workloads every day. Its engineers found they were spending more time maintaining and adding to its data warehouse instead of developing new ways to help the business gain more insight. Meanwhile, the company's on-premises infrastructure meant that certain types of analysis were limited by space, cost, and time.

By 2017, Jobrapido decided to look for a hybrid solution, keeping the main functionality of the website in its existing servers, while migrating its data warehouse to the cloud. After examining its options, Jobrapido chose Google Cloud Platform for its new data solution because of the rapid advancements Google was making in its cloud offerings and its reputation for high quality.

In September 2017 Jobrapido took its first steps with GCP, building a job advert classifier with App Engine and Cloud Pub/Sub. The classifier took in data from the millions of job adverts processed every day, assigned each one a label based on Jobrapido's taxonomy model, and fed the results back into the main database.

"We're developers so we love working with code. Google Cloud Platform lets us implement the infrastructure as code. That means it's testable, repeatable, and scalable. Everything has a script to deploy the software and that makes the developers very happy."

Stefano Fornari, VP of Engineering, Jobrapido

Once this was up and running, and the company's engineers were confident with GCP, they began work on moving the data infrastructure to the cloud. BigQuery was at the core of the new platform, providing a serverless, easy-to-use way of storing over 100 tables, the largest of which is over 4 billion rows. Along with Cloud Dataflow, App Engine, and Pub/Sub, the company used BigQuery to form a data pipeline that ingested raw data, such as page views and impressions, processed it, and then aggregated and analyzed it for further business insight. Jobrapido's team quickly learned how to work with and take advantage of the new solution.

"We're developers so we love working with code," says Stefano. "Google Cloud Platform lets us implement the infrastructure as code. That means it's testable, repeatable, and scalable. Everything has a script to deploy the software and that makes the developers very happy."

Maximizing analytical power, minimizing costs

With GCP, Jobrapido built a data solution that seamlessly integrated with its existing infrastructure while increasing its capacity for storage, processing, and compute power. The new system handles more than 125 million events per day, increasing the amount of data that the company ingests, ultimately making for more powerful insights. The time taken to analyze such data has been drastically reduced, according to Stefano, thanks to the availability of vast compute power as well as the ease of use of Google Cloud Platform.

"When you take into account the servers, the licenses and the time saved, I'd say it's reduced our overall costs by around half. In the past, the team was focused around 90 percent on maintenance, 10 percent on development. With Google Cloud Platform, it's 90 percent development and only 10 percent maintenance."

Stefano Fornari, VP of Engineering, Jobrapido

"Before, if we wanted to analyze the effect of a change on the website, there would be at least a day's delay with loading data, processing it, and dashboarding," he says. "Now, with everything integrated so well in Google Cloud Platform, we can get feedback in just 30 minutes."

By moving its data to a serverless environment, Jobrapido has not only been able to improve the speed at which it can scale, but it has also reduced its infrastructure costs by avoiding the cost of new servers and licenses, which it used to rely on. In addition, the IT department's team of engineers spends far less time on DevOps and infrastructure.

"When you take into account the servers, the licenses, and the time saved, I'd say it's reduced our overall costs by around half," says Stefano. "In the past, the team was focused around 90 percent on maintenance, 10 percent on development. With Google Cloud Platform, it's 90 percent development and only 10 percent maintenance."

Now that Jobrapido has successfully migrated its data solution, the company is exploring options with Google to move the rest of its infrastructure to the cloud. "We want to continue our relationship with Google Cloud and right now we're experimenting with Google Kubernetes Engine," says Stefano. The goal is to add scalability to the existing services without compromising on speed and security. For Jobrapido, working with Google has been about more than delivering solutions. It's been about a relationship that goes from strength to strength.

"When we look at what was on offer from Google Cloud two years ago and what's on offer now, we see strong growth and expect even more in the future. We want to take advantage of that."

About Jobrapido

Established in 2006, Jobrapido is one of the world's leading job aggregators operating in 58 countries. Using pioneering technology and innovative products, Jobrapido connects the dots between great employers and stellar candidates.

Industries: Technology
Location: Italy
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