Outfit 7’s Talking Friends built on Google App Engine, recently hit one billion downloads

Today’s guest blogger is Igor Lautar, senior director of technology at Outfit7 (Ekipa2 subsidiary), one of the fastest-growing media entertainment companies on the planet. Its flagship franchise Talking Tom and Friends has achieved over 1.2 billion downloads since its launch in 2010 and continues to grow with 170 million active users each month. In today’s post, Igor explains how the company has been successful building the backends of its entertainment apps on Google App Engine.

Outfit7 is one of the most downloaded mobile publishers in the world, most famous for creating Talking Tom, an app in which a cat named Tom responds to your touch and repeats what you say. Talking Tom and Friends are unique fully animated 3D animal characters who love to be petted and played with through an array of in-app user functions. Each with their own distinct personality, Talking Tom, Talking Angela, Talking Ginger, Talking Ben, Talking Gina and a host of lovable friends are fully-interactive and can engage in two-way conversations with users. Fans can even create and share videos of interactions with their favourite characters via Facebook and YouTube.



The popular characters started life in the digital world and now Talking Tom and Friends extend from mobile apps to chart-topping YouTube singles, animated web series, innovative merchandise and a soon to be released TV series. The company has published more than 20 apps to-date with users in every country in the world.



In order to run and maintain all of these apps, a robust backend is required to track the state of the app and virtual currency and push new content and promotions across multiple platforms, which is why we turned to Google Cloud Platform.



Why Google App Engine?

Outfit7 was founded by a group of entrepreneurs in 2009 whose mission is to bring fun and entertainment to all. Like most startups of its kind, much of Outfit7’s team were engineers who had first-hand experience with hardware and knew its limitations, specifically the dedicated resources needed to maintain it.



Thus, from the beginning, we knew the types of resources that would be required to grow the company. We started researching cloud solutions that would enable us to scale-up as we grew and have a backend that could handle any workload. After researching and interacting with a number of companies, the team decided to move forward with Google App Engine because of its low maintenance and ease of use. To put this in perspective, we looked at virtual solutions in addition to cloud; however, virtual machines would still require a dedicated IT administrator. Our developers could work directly with App Engine without IT support, which is why we went with Google.



From App Engine to Cloud Datastore and BigQuery

With App Engine, we were able to take advantage of Google’s infrastructure. As any mobile app developer knows, a scalable backend is essential from day one. Apps can go from zero to one million downloads faster than you think - which is one of the primary reasons that we went with Google. And we still run a significant amount of original code, some of it four years old, which proves the value of App Engine and allows us to focus on new features instead of maintaining old ones.



We also implemented Google Cloud Datastore alongside App Engine. This directly supported our backend from the outset with migration from Master/Slave to HRD. The performance and scaling capabilities proved excellent, and we have even seen a drop in access time as Cloud Datastore has improved over the past few years.



After building this foundation with App Engine and Cloud Datastore, we expanded our use of Cloud Platform to include Google Cloud Messaging, an Android-specific service that allows you to send data from your server to your users’ Android devices. While Talking Tom is our most popular app, we also have similar apps with different characters like Talking Angela and Talking Santa. We leveraged Cloud Messaging to increase user engagement by sending fun messages that attract users’ attention.



More recently, we started using Google BigQuery for data analytics. Some of the tables we have are quite large and growing fast, but the performance of the queries remain very consistent (i.e., seconds, not minutes). BigQuery’s scaling ability is just as impressive as the other platform tools, and we’re excited to expand our usage of the tool.

All of our apps communicate via App Engine. The state is stored in a number of datastores supported by memcache. Most of the processing is done directly by frontend instances, and some operations are delegated to task queues. We also have a few backend instances for long-running jobs or complex operations that require more memory.



Some of our apps use push notifications quite heavily. For Android, we send them directly to Cloud Messenger, whereas iOS push notifications are sent to our own forwarding service, which is still legacy.



Data is pushed to BigQuery from our own servers. After processing it and gathering it from various sources, including logs, stats from stores, and downloads, BigQuery is then queried directly via the data visualization tools that we use.



Our experience with Google Cloud Platform has been very positive. The benefits are obvious — consistent performance with great scalability, leaving us more time to focus on app development. We are very happy with the performance and reliability of the platform, and as our vice president of technology, Luka Renko, says, “It’s nice to have a platform that solves more problems than it creates. That’s rare!”



Google Cloud Platform has been the foundation that has enabled us to produce some of the most popular apps in the world. Throughout our relationship with Google the support team has been amazing, helping us unlock all the power of Cloud Platform. We’re excited to continue working with Google.



-Contributed by Igor Lautar, Senior Director of Technology, Outfit7 (Ekipa2 subsidiary)