Life of SRE as a Salesperson

Price comparison is one of the key value propositions of trivago, and in doing so, we handle billions of prices everyday to provide our users with the most accurate and up to date price as possible. We can leverage this enormous amount of historic price data to provide price context for our users in a scalable and fast way.

Modern frontend engineering is a collaborative effort of many people with different talents and expertise. Over the years, a team working together can continuously refine their ways of working, so that the different contributions fit together seamlessly and each step in the production process is in sync with the next one. Read about our team structure, our A/B test setup, and about what makes our QA team so special.

Are you passionate about AI and its potential to transform the travel industry? Then dive into our interview with Sören Weber, Senior Product Manager at trivago, as he reveals the journey from concept to reality behind trivago's innovative Smart AI Search feature. And learn how trivago's unique approach and deep integration of AI, set us apart.

In May this year, more than 300 of (mostly tech) trivago talents gathered for a full-day conference focused on knowledge sharing and valuable exchanges on the latest tech trends. Known as the trivago Tech Get Together, this event is a crucial part of our learning culture and provides an opportunity for our talents to learn from each other. The event featured several talks, keynotes, workshops, and a panel discussion, ensuring that everyone who attended the event could take away important learnings applicable to their work environment.

Over the last year trivago refactored the existing GraphQL monolith and moved to a microservice architecture, in what is also known as a federated setup. Federated GraphQL, as championed by Apollo, represents a significant shift in how companies architect and scale their GraphQL ecosystems, especially when transitioning from monolithic designs to microservice-based architectures. In a federated setup, each microservice maintains its own GraphQL schema, relevant to the domain it serves. These individual schemas are then seamlessly stitched together into a unified gateway. This gateway serves as the single access point for clients, enabling them to query data across multiple services as if it were coming from a single, monolithic GraphQL API. Such change involves also a completely new approach to the test and delivery, with the goal of empowering developers to quickly and safely deploy to production autonomously.

At trivago, tech meetups are one of our favorite formats to learn and exchange knowledge. In April, we hosted the 2nd edition of the QA Meetup, which turned out to be a great success. The event attracted over 65 attendees from various roles and companies. The evening was filled with inspiring talks by several talented QA experts. Attendees were sharing insights, asking questions, and soaking up knowledge. To make things even more exciting, there was a competitive quiz that got everyone on their toes, and a magic show by one of our speakers that completely amazed the audience.

When we think about migration, we usually imagine moving something or someone from one place to another. Doing so has inherent complexities, which can exponentially grow when migrating a software solution. In this article, we’re sharing our experience on how we migrated all our image-related infrastructure to GCP (Google Cloud Platform) from a combination of AWS (Amazon Web Services) and our Data Centre.

Learning about risk-taking, sentiment analysis, cybersecurity, and psychological safety in one evening? That’s quite a mix, isn't it?

That’s what the audience got offered at the Women in Tech meetup, which took place on February 29th in trivago's office space. Together with iteratec, trivago had the pleasure of bringing together the vibrant community of female tech talents and their allies on the occasion of International Women's Day, for an evening featuring stories about risk, safety, and continuous improvement.

This article is written for individuals in data science or analytics roles who are familiar with terms such as confidence interval, databases, or workflows. It is aimed at those who need to implement anomaly detection techniques for various types of users with different needs. In this article, I will share my experience from working at trivago, with a specific focus on internet traffic. Rather than delving into the details of mathematical models (as there are already many well-covered articles on this topic), I aim to provide insights into real-world situations encompassing a wide range of business needs. These situations require tailored solutions to cater to different types of stakeholders.

During the development of customer-facing applications, time is crucial, especially when it comes to testing and analyzing changes before accepting them in production. This blog post explores how we developed a Java-based reactive tool to simulate production requests, that allows us to have quicker hints about the effects of changes introduced and be more confident about the hypotheses that are formulated. As a long term vision, we wish to significantly reduce the A/B testing time and ensure seamless transitions.