Posts about DevOps

Read ElasticWars Episode IV: A new field
Backend Devops

ElasticWars Episode IV: A new field

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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). At trivago,we use Kafka as a central hub for moving data between our systems (including logs).

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Read trivago joins the Cloud Native Computing Foundation
Open Source Cloud Devops

trivago joins the Cloud Native Computing Foundation

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“The Cloud Native Computing Foundation (CNCF) hosts critical components of the global technology infrastructure. CNCF brings together the world’s top developers, end users, and vendors and runs the largest open source developer conferences. CNCF is part of the nonprofit Linux Foundation.” - CNCF Last year, when visiting CloudNativeCon/KubeCon Europe in Barcelona (one of the biggest cloud-focused conferences in Europe), I noticed that there were some companies present in the exhibition space whose primary focus wasn’t software development.

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Read Why We Chose Go
Backend DevOps

Why We Chose Go

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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.

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Read Nomad - our experiences and best practices
Monitoring Backend DevOps

Nomad - our experiences and best practices

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Hello from trivago’s performance & monitoring team. One important part of our job is to ship more than a terabyte of logs and system metrics per day, from various data sources into elasticsearch, several time series databases and other data sinks. We do so by reading most of the data from multiple Kafka clusters and processing them with nearly 100 Logstashes. Our clusters currently consists of ~30 machines running Debian 7 with bare-metal installations of the aforementioned services.

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