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AWS Summit Public Sector 2018

198243 - Leveraging AWS ML to Improve Forecasting and Governance

Session Description

ECS Offers Customers a cloud management platform leveraging AWS ML for algorithmic cloud spend forecasting, predictive modeling, and anomaly detection

Challenge:
Customers require advanced prediction models in order to optimize their AWS usage and perform anomaly detection to determine unusual spend patterns.

Solution:
In support of ECS’s AWS Premier Consulting, Audited MSP, and Channel Reseller capability, ECS developed a cloud automated management portal (CAMP) which processes thousands of billing records on a daily basis. We’ve designed CAMP to deliver advanced forecasting and prediction models for cloud usage, anomaly detection, and alerts based on a multi-dimensional analysis platform.
ECS delivers this solution using the following Amazon Web Services: AWS ML SageMaker, Athena, Elastic Load Balancer (ELB), Elastic Compute Cloud (EC2), Elastic Block Store (EBS), and Relational Database Service (RDS) for SQL Server, S3, Lambda and Route 53.

Benefits:
ECS’s CAMP solution leverages the AWS ML platform enabling customers to:

  • • Translate cloud data into knowledge and mission intelligence
  • • Provide a deeper understanding to facilitate better decision-making
  • • Enable advanced, predictive modeling and forecasting of an organization’s AWS usage while driving adoption through more clear understanding of spend patterns
  • • Improved anomaly detection accuracy and alerting based on a holistic enterprise view to optimize and automate governance policies and compliance


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