Platform Engineering at Google

Chapter 5. AI with Platform Engineering

By Isaac Albarran with Konrad Dryja

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This will be the 22nd chapter of the final book. Please note that the GitHub repo will be made active later on.

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Artificial Intelligence (AI) and Machine Learning (ML) are profoundly reshaping industries, driving innovation from hyper-personalized customer experiences to breakthroughs in scientific research. As organizations increasingly embed AI into their products and operations, the engineering challenges of developing, deploying, and managing AI systems at scale have come to the forefront of the evolution of platforms. Simultaneously, the platforms and infrastructure supporting these systems are themselves becoming more complex. This landscape presents Platform Engineering with a crucial and exciting dual mandate:

Building platforms for AI systems

Creating the robust, specialized infrastructure, abstractions, and workflows required to efficiently manage the entire lifecycle of AI/ML models. This is often encompassed by the term MLOps (Machine Learning Operations).

Deploying AI for platforms

Leveraging AI and ML techniques ...