Build Out on Google Cloud
Engineering architecture challenges using Google Cloud
Build Out is a technical system design video and article series I co-created with Colt McAnlis while we were both on the Google Cloud Developer Relations team. The concept was that Colt and I were tasked with designing the architecture for ambitious, futuristic engineering challenges, with the goal of exploring how to architect real-world, highly scalable solutions utilizing Google Cloud Platform.
Rather than prescribing a single “correct” answer, the series highlights the collaborative system design process. For each scenario, two distinct architectural solutions are proposed, mapped out, and compared. By examining the inherent trade-offs of different approaches—such as balancing infrastructure costs, architectural flexibility, offline capabilities, and global scalability—the project demonstrates how various cloud and edge components can be orchestrated to solve massive problems.
Explored Challenges
- Building a Garden that Cares for Itself: Designing an autonomous, learning smart garden. This project compares a centralized, modified CNC-machine approach against a distributed Bluetooth mesh of IoT sensors, leveraging technologies like Android Things, Firebase, Cloud Pub/Sub, and TensorFlow for predictive plant care.
- Building a Virtual World Worthy of Sci-Fi: Architecting the backend infrastructure for a global metaverse and immersive VR environment. This episode contrasts generating a virtual clone of the real world using massive sets of sensor data versus building a purely artificial MMO landscape, utilizing tools like Cloud Spanner, App Engine Flex, Preemptible VMs, and global data streaming.
Key Project Themes
- Scalable Cloud Architecture: Practical demonstrations of managing heavy compute workloads, complex data pipelines, and serverless environments.
- System Design Trade-offs: Analyzing the pros and cons of different infrastructure choices based on unique project constraints.
- Integrated Ecosystems: Bridging the gap between physical hardware (IoT), machine learning models, and cloud infrastructure to build cohesive, intelligent systems.