Challenge
Building a developer-friendly data infrastructure
Fortis Games is a global video game developer and publisher focused on creating games for mobile, PC, and console where players can challenge their minds, build connections, and inspire communities. To deliver on this, the team taps into real-time game data like engagement rates with new elements, popular map areas, and weapon accuracy to personalize player experiences.
As a result, Fortis Games wanted a scalable, flexible, fast, and developer-friendly data infrastructure to leverage its real-time data. However, earlier solutions like Apache Kafka® were riddled with complexity and struggled to scale without significant lag during game interactions.
“As a new game studio, we needed to build a flexible data platform that empowers our developers to get real-time insights from game events without worrying about the backend infrastructure.” Says Colin Riddell, Director of Data Engineering at Fortis Games.
Why Redpanda
Simple, powerful, cost-efficient
With previous data pipelines built on the likes of Kafka, Amazon Kinesis, and Confluent — Redpanda was the next logical choice. Ultimately, the team was swayed for the following reasons:
- Easy integration with their existing setup
- No administrative overhead compared to other Kafka solutions
- Superior performance without gaming lag, even at massive scale
- Tiered cloud storage to retain data long term without performance loss
- Significantly lower infrastructure costs
So, Fortis Games chose to build its fresh new real-time data infrastructure on Redpanda for its complete Kafka compatibility but without the usual pains of Kafka management. Not to mention Redpanda’s high resource efficiency and flexible deployment options that would save the company time and money.
“Redpanda quickly rose to the top of our list for a streaming data solution because we knew that its engineers obsess over performance and reliability at scale, and we loved the fact that it is Kafka API-compatible and just works with the ecosystem we already know,” Colin says.
Results
A real-time data platform built for the future
Building games that will redefine player-driven experiences largely relies on leveraging real-time data. With Redpanda, Fortis Games finally has the simplicity, scale, and speed to build the foundation of a future-proof, real-time data infrastructure.
“Redpanda removes 90% of the headaches we get from Kafka because it’s so easy to deploy, manage, and scale,” says Ricky Saltzer, Principal Data Engineer at Fortis Games. “We have tested the data platform for up to 100 million users with zero performance blips.”
With Redpanda’s highly efficient architecture running on about one-third of the compute resources compared to Kafka, Fortis Games also reduced its infrastructure bill right out of the gate and can control costs as it grows. That means big savings for the company and a scalable platform for its game developers.
Furthermore, Redpanda’s bring-your-own-cloud (BYOC) deployment model provides Fortis Games with fully managed service for cluster administration while giving them complete control over their data and infrastructure within its own VPC (virtual private cloud).
With Redpanda as its streaming data engine and in combination with other best-of-breed tools like ClickHouse and Iceberg, Fortis Games has created a strong and reliable real-time analytics platform that can support game developers today and many years into the future.
“Redpanda is simple, has a high-performance design that saves us time and money, and is extremely reliable at scale.”
Read the full story
Have a similar challenge? Chat with us
Read more success stories
How Zafin swapped in Redpanda and instantly simplified operations to accelerate business agility for its customers.
Why poolside lets Redpanda manage its streaming data pipelines so they can focus building the best AI models.
How THN shifted from managing Apache Kafka® to creating data-driven opportunities for hotels worldwide.
How India’s largest social media company optimized its event streaming platform for stress-free scaling.