Backend at trivago

Insights, experiences and learnings from trivago's tech teams.

Read trivago Tech Check-in: Meet Fabian

trivago Tech Check-in: Meet Fabian

In our new series, trivago Tech Check-in, we're introducing you to some of our tech talents from across the globe who help keep our metasearch engine running smoothly everyday. In this first edition, you'll meet Fabian Fritzsche, an engineering intern that works on the Microservice-System that feeds our GraphQL API with up-to-date hotel data.

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Read ElasticWars Episode IV: A new field

ElasticWars Episode IV: A new field

On a normal day, we ingest a lot of data into our ELK clusters (~6TB across all of our data centers). This is mostly operational data (logs) from different components in our infrastructure. This data ranges from purely technical info (logs from our services) to data about which pages our users are loading (intersection between business and technical data).

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Read Why We Chose Go

Why We Chose Go

To the outside, trivago appears to be one single software product providing our popular hotel meta search. Behind the scenes, however, it is home to dozens of projects and tools to support it. Teams are encouraged to choose the programming languages and frameworks that will get the job done best. Only few restrictions are placed on the teams in these decisions, primarily long-term maintainability. As a result, trivago has a largely polyglot code base that fosters creativity and diverse thinking. It allows us to make informed decisions based on actual requirements rather than legacy code or antiquated projects.

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Read Getting Ready For The Big Data Apocalypse

Getting Ready For The Big Data Apocalypse

trivago Intelligence was born in 2013 with two main objectives: First, to provide bidding capability to the advertisers, who are listed on trivago, and second, to provide them with metrics related to their own hotels; like clicks, revenue, and bookings (typical BI data). This project faced a wave of inevitable data growth which lead to a refactoring process which produced a lot of learnings for the team. As I expect it to be useful for other teams who deal with similar challenges, this article will describe why a team started a full migration of technologies, how we did it and the result of it.

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