Testing your functionality is important, but what happens if other factors come into play? In this blog post we show how trivago handles non-functional testing for every commit and how we scaled it.
Backend at trivago
Insights, experiences and learnings from trivago's tech teams.
Would you book a hotel without seeing the images first? No, right? Hence, it's vital to make sure the images are available all the time. In a scenario where a lot of images were deleted, we must have an efficient way of recovering them. This is how we achieved that with Amazon S3 Versioning.
When migrating your data to new technologies, validation of the data becomes challenging as your data structures might change. Rebase tries to make this easier while also giving your more flexibility on your data.
We built a reactive pipeline to move almost a quarter billion database records to AWS and to build a reactive and serverless pipeline. This is the story of the lessons we learned along the way working with Kinesis and Lambdas
One day, Memcached ran out of free memory. The method `get` failed and all requests went directly to the database. Of course these calls also failed under the huge load, and eventually it caused downtime for the whole trivago website. Yikes!
We do think that our tech blog is full of interesting things powered by our engineers' great stories. Let us take you on a journey of how we maintain trivago tech blog from the technical perspective and how we recently automated its deployment process.
We all have been there, done that. You want to build an API that allows you to manipulate your entities so you start checking which specification to use. Maybe REST or JSON API or maybe no specification.
We're a data-driven company. At trivago we love measuring everything. Collecting metrics and making decisions based on them comes naturally to all our engineers. This workflow also applies to performance, which is key to succeed in the modern Internet.
At trivago we use Jenkins as our main CI tool. However, when our physical setup was not enough we needed to move it to the cloud and implement an automated slave scaling. This is the definite guide with all the steps we took to implement an auto scaling Jenkins platform.