Leveraging AWS ML to Improve Forecasting and Governance

Опубликовано 2 июля 2018, 17:55

AWS Public Sector Summit 2018 - Washington, D.C.

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

Speakers: Imran Bashir, John Calhoun, John Sankovich, Ross Serino