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You have recently joined a startup company building sensors to measure street noise and air quality in urban
The company has been running a pilot deployment of around 100 sensors for 3 months Each sensor uploads
1KB of sensor data every minute to a backend hosted on AWS.
During the pilot, you measured a peak or 10 IOPS on the database, and you stored an average of 3GB of sensor
data per month in the database
The current deployment consists of a load-balanced auto scaled Ingestion layer using EC2 instances and a
PostgreSQL RDS database with 500GB standard storage.
The pilot is considered a success and your CEO has managed to get the attention or some potential investors
The business plan requires a deployment of at least 1O0K sensors which needs to be supported by the backend

You also need to store sensor data for at least two years to be able to compare year over year Improvements.
To secure funding, you have to make sure that the platform meets these requirements and leaves room for
further scaling
Which setup win meet the requirements?

Add an SOS queue to the ingestion layer to buffer writes to the RDS instance

Ingest data into a DynamoDB table and move old data to a Redshift cluster

Replace the RDS instance with a 6 node Redshift cluster with 96TB of storage

Keep the current architecture but upgrade RDS storage to 3TB and 10K provisioned IOPS

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