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Cases studies, EHR, Helicopter, Mountkik games, TerramEarch, Exam tips -…
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EHR
Services
BQ - ML prediction, with ingestion via Dataflow
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Cloud logging -> cloud storage, BQ --- log retention
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Active Directory Federation Services (AD FS) - Google Cloud Active Sync (Sync users and groups from Active Directory to Cloud Identity)
Anthos - run K8s, logging, monitoring, trace, Ci/CD, etc
Databases
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MySQL, MS SQL -> Cloud SQL
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Current architecture
web based customer apps, running on K8S
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Databases: MySQL, MS SQL, Redis. MongoDB
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legacy files:
will not be moved to GCP, scheduled to replace
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Helicopter
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current architecture
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content is encoded and transcoded, where needed, in the cloud
race prediction services
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Race predictions are performed using TensorFlow running on VMs in the current public cloud provider.
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Services
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Video Intelligence API, Streaming API(Part of AI libs) - support data streaming
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BQ + AI Pletform - TensorFlow, warehouse, etc
Context
world championship and several regional league competitions. - referance to global and regional resources
offers a paid service to stream the races all over the world with live telemetry and predictions throughout each race.
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Goal
Additionally, as new fans engage with the sport, particularly in emerging regions, they want to move the serving of their content, both real-time and recorded, closer to their users.
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HRL wants to migrate their existing service to a new platform to expand their use of managed AI and ML services to facilitate race predictions.
Mountkik games
Services
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Spanner is proposed for leaderboards, but we propose to use Redis or MemStore
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online, session based games
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TerramEarch
Services
Cloud Build, Spinakar, Jenkins - for CI/CD for containers
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Cloud Monitroring, Logging, Enable logs on Firewall and VPC
Minimize downtime: Create a streaming pipeline, and add Predictive Management (AI tools)
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Target
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5 years plan: 1) Create a partner ecosystem of new products 2) increase autonomous vehicle operations
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