Media company anticipates traffic peaks with Google Kubernetes Engine

French-based media firm Brut has offices across two continents and published daily content in three languages and across eight social media platforms, with more than a billion views per month, providing subtitles for all content.

This international setup created challenges, especially creating a bridge between France and other locations with translated content, as translations on videos are required quickly in order to bring relevant news to international audiences.

Along with a need to anticipate traffic peaks for videos going viral and to quickly deliver content to different parts of the world, Brut turned to Google Cloud for a new platform. Brut CTO Guillaume Perrin says: “We needed to create a platform of our own, instead of relying exclusively on existing social platforms to distribute content. We wanted to have our own website and application, and also centralize every piece of content we create”.

Due to its simple scalability, low latency, advanced security and easy communication channels with experts, Brut decided on Google Kubernetes Engine and Cloud Storage.

Google Kubernetes Engine was implemented in just 15 days and allowed Brut to scale and meet spikes in demand, using different clusters to allocate resources where they’re needed. This has enabled the company to avoid downtime or lag, even when videos rapidly go viral.

Prior to adopting Cloud Storage, Brut had stored video projects on local network storage in France and the US, with file exchange difficult. With Cloud Storage, French and US employees can share and collaborate on files instantly.

Guillaume Perrin points out that Cloud Storage has opened new opportunities for Brut: “Centralized storage has opened the door to syndication deals, bringing us a brand new revenue stream. It’s a real game changer for us, and Cloud Storage helped make it possible”.

With Google Cloud, Brut has quicker processes and higher revenues and is able to gather and measure performance, while anticipating peaks in traffic.

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