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Whenever a user creates new objects - for example, AWS Load Balancers, AWS S3 Buckets and AWS RDS Databases - cloud provider requests the user to provide destination logging location, like a bucket or big query BigQuery table. This flexibility is great, but large cloud consumers end up with hundreds of locations for log storage. This often results in fragmented data. 

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  • Single Metrics - detect anomalies in single time series, e.g. Total Spending By Day 

  • Multi-Metrics - detect anomalies across multiple time series, e.g. CPU

  • Network Traffic by Instance and Population - detect activity that is unusual compared to the behaviour of the population, e.g. console users’ logins.

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Reliability and Scalability

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