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CASE STUDY: TerramEarth
Company Overview: TerramEarth manufactures heavy equipment. 2 million vehicles in the field.
Current Environment: Vehicles send telemetry via cellular. Processing 100,000 msgs/sec. On-prem Hadoop cluster.
Business Requirements: Predict equipment failure. Reduce warranty costs. Provide fleet dashboard.
Executive Statements: CEO: 'Monetize data.' CFO: 'Storage costs spiraling.' CTO: 'Need scalable ingestion and ML.'
Technical Requirements: Ingest 500,000 msgs/sec. Store petabytes cost-effectively. Train ML models. Real-time anomaly detection.
Constraints: Intermittent connectivity. Strict vehicle authentication.
QUESTION:
Which architecture should you design to handle the ingestion of 500,000 messages per second from vehicles with intermittent connectivity?
GCP PCA · Question 15 · Reliability
CASE STUDY: TerramEarth
Company Overview: TerramEarth manufactures heavy equipment. 2 million vehicles in the field.
Current Environment: Vehicles send telemetry via cellular. Processing 100,000 msgs/sec. On-prem Hadoop cluster.
Business Requirements: Predict equipment failure. Reduce warranty costs. Provide fleet dashboard.
Executive Statements: CEO: 'Monetize data.' CFO: 'Storage costs spiraling.' CTO: 'Need scalable ingestion and ML.'
Technical Requirements: Ingest 500,000 msgs/sec. Store petabytes cost-effectively. Train ML models. Real-time anomaly detection.
Constraints: Intermittent connectivity. Strict vehicle authentication.
QUESTION:
To ensure the reliability of the new ingestion pipeline, the operations team wants to implement SRE practices. How should they measure the performance of the ingestion API?
CASE STUDY: TerramEarth
Company Overview: TerramEarth manufactures heavy equipment. 2 million vehicles in the field.
Current Environment: Vehicles send telemetry via cellular. Processing 100,000 msgs/sec. On-prem Hadoop cluster.
Business Requirements: Predict equipment failure. Reduce warranty costs. Provide fleet dashboard.
Executive Statements: CEO: 'Monetize data.' CFO: 'Storage costs spiraling.' CTO: 'Need scalable ingestion and ML.'
Technical Requirements: Ingest 500,000 msgs/sec. Store petabytes cost-effectively. Train ML models. Real-time anomaly detection.
Constraints: Intermittent connectivity. Strict vehicle authentication.
QUESTION:
To ensure the reliability of the new ingestion pipeline, the operations team wants to implement SRE practices. How should they measure the performance of the ingestion API?
Answer options:
Measure the CPU utilization of the underlying VMs and alert if it exceeds 80%.
Define Service Level Indicators (SLIs) for API latency and error rate, and set a Service Level Objective (SLO) of 99.9%.
Create a Service Level Agreement (SLA) with the development team to guarantee zero downtime.
Use Cloud Profiler to continuously monitor the code execution time.
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