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Allthecooks is a social media platform for people who love cooking. It is available on Android, iPhone, Windows Phone, Google Glass, and Android Wear, and is a top recipe app on Google Play. The platform connects passionate chefs with casual and first-time cooks on every major mobile device. Users can find, rate, and comment on dishes they can cook themselves, or post their own ideas complete with directions, ingredients, servings, and nutrition information. The platform has chefs with tens of thousands of followers, meaning that whenever they make an update, hundreds of thousands of simultaneous API requests need to be processed.
Allthecooks, a social media platform for cooking enthusiasts, faced the challenge of managing a rapidly growing user base. The platform, which allows users to find, rate, comment on, and post their own recipes, had to process hundreds of thousands of simultaneous API requests whenever popular chefs updated their content. The company, which started with just three part-time engineers and no external funding, needed a scalable and reliable infrastructure to support its growth. The challenge was not just about speed, but also about scalability. As the user base grew, the need for a more robust backend processing architecture became evident. Cost was also a significant concern as the company was using its savings to build the platform.
Google Cloud Platform played a pivotal role in addressing Allthecooks' challenges. The platform helped Allthecooks grow without worrying about their architecture. Google App Engine and Google Cloud Datastore were used to manage millions of daily interactions. As the user base expanded, Allthecooks began migrating significant parts of their backend processing architecture from App Engine to Google Compute Engine. This transition allowed the company to operate at higher performance levels using cheaper CPU and caching more data in the large RAM configurations supported by Compute Engine instances. The company also planned to use Google BigQuery to simplify the process of finding the perfect recipe. The recommendation engine was built on Compute Engine, enabling it to run entirely on RAM for immediate response times.
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