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Continious integration

We're using Travis for our non-private code such as payment infrastructure and Codeship for our core product as their servers are a lot more powerful. We also implemented a system, that allows us to create a staging version of each branch just by opening a pull request on Github. A link to it is posted in Slack when its ready. Even though our server and client code is tested with unit and integration tests, our deployment process takes less than 5 minutes to complete thanks to heavy parallelization.


  • All of our public static files are cached in AWS Cloudfront.
  • Our main HTTP API is hosted on Heroku
  • Workers, such as content improvement AI, image resizers, PDF generators are deployed to AWS Lambda with AWS ApiGateway, which allow us to scale indefinitely.
  • User files such as user avatars are deployed directly from the client to AWS S3 and then processed by a Lambda without going through our servers.
  • All our logs are collected in AWS Cloudfront and we're able to monitor all of our resources via single dashboard.


  • Latest ES6 features + React + Redux + Webpack
  • NodeJS for API/Workers
  • Python for Content Improvement / AI
  • MongoDB as primary database, Postgres for product analytics
  • PhantomJS for PDF rendering
  • WebDriverIO for integration tests
  • Mocha/Chai for unit tests
  • Serverless for AWS Lambda infrastructure management


  • Github - Open source and private projects (your private contributions will be visible in your github profile)
  • Kanbanize - Project management
  • Codeship - Continuous Integration
  • Travis - Continuous Integration for open source projects
  • Invision - Wireframes / Prototypes / Product designs
  • Google Drive - File sharing
  • CodeClimate - Code coverage
  • Slack - For team communication