We at Intranetum as an startup decided to push for a complex SaaS solution that can scale on a machine learning product in November 2015. At that time we had 3 months to be able to have a working first implementation that could be used in production. An architecture with more than 30 components and the need to scale fast needed to design how we were going to develop / deploy and scale. Based on DevOps ideas we decided to push for a Docker + Kubernettes + Jenkins for development/testing/staging/production autodeployment. I'm going to explain how we used this tools to achive our objective and our conclusions for the future.
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