Читать книгу Google Cloud Certified Professional Cloud Architect Study Guide - Dan Sullivan - Страница 42

The emphasis on AI and ML makes the Helicopter Racing League a candidate for Vertex AI services. Since they are using TensorFlow, performance may be improved using GPUs or TPUs to build machine learning models.

Improving the accuracy of predictive models will likely require additional data or larger ML models, possibly both. Cloud Pub/Sub is ideal for ingesting large volumes of telemetry data. Services can run in Kubernetes Engine with appropriate scaling configurations and using a Google Cloud global load balancer. The Helicopter Racing League should consider adopting MLOps practices, including automated CI/CD for ML pipelines, such as Vertex Pipelines.

The league has racing fans across the globe, and latency is a key consideration, so Premium Tier network services should be used over the lower-performance Standard Network Tier. Cloud CDN can be used for high-performance edge caching of recorded content to meet latency requirements.

BigQuery would be a good option for deploying data marts and supporting analytics since it scales well and is fully managed.