Serverless ML/Analytics Using AWS Managed Services Cyrus M Vahid, Principal Solutions Architect cyrusmv@amazon.com June 2017

Initial Batch Cycle Phase 1: Long Cycle: Batch Analytics Decouple Data From Processing Establish Simple ML using AML. Amazon Athena Team Capabilities Kinesis Firehose Quicksight Kinesis Streams Amazon S3 AML Full Cycle: Analytics

Extended Batch Cycle Phase 1: Phase 2: Long Cycle: Batch Analytics Decouple Data From Processing Establish Simple ML using AML. Use BI for Phase 2: Introduce More Sophisticated ML using EMR/Spark, as well as libraries such as scikit-learn. Amazon Athena Team Capabilities Redshift Quicksight Amazon S3 EMR (Yarn/Spark) AML Aggregator Full Cycle: Analytics

Full Cycle Serverless Analysis Long Cycle: Batch Analytics Phase 1: Decouple Data From Processing Establish Simple ML using AML. Use BI for Phase 2: Introduce More Sophisticated ML using EMR/Spark, as well as libraries such as scikit-learn. Phase 3: Advance realtime analysis by incorporating the results from improved batch analysis. Introduce feedback loop. Amazon Athena Team Capabilities Redshift Kinesis Firehose Quicksight Kinesis Streams Amazon S3 EMR (Yarn/Spark) AML Kinesis Analytics Aggregator Realtime Event Processor Aggregator Realtime Search Feedback Aggregator Agg. Cached Data Short Cycle: Real Time Analytics Full Cycle: Analytics

Collaborative ML and Deep Learning Long Cycle: Batch Analytics Phase 1: Decouple Data From Processing Establish Simple ML using AML. Use BI for Phase 2: Introduce More Sophisticated ML using EMR/Spark, as well as libraries such as scikit-learn. Phase 3: Advance realtime analysis by incorporating the results from improved batch analysis. Introduce feedback loop. Phase 4: Add multi data source SDK Add deep Learning Capabilities Amazon Athena Team Capabilities Redshift Kinesis Firehose Quicksight Kinesis Streams Amazon S3 EMR (Yarn/Spark) AML Kinesis Analytics Aggregator Realtime Event Processor Aggregator Realtime Search Feedback Aggregator Agg. Cached Data Short Cycle: Real Time Analytics Full Cycle: Analytics

References Amazon S3: http://docs.aws.amazon.com/AmazonS3/latest/dev/Welcome.html Amazon Athena: https://aws.amazon.com/athena/ MXNet: https://aws.amazon.com/mxnet/ Amazon Kinesis: https://aws.amazon.com/kinesis/?nc2=h_m1 Amazon EMR: https://aws.amazon.com/emr/?nc2=h_m1 Amazon Redshift: https://aws.amazon.com/redshift/?nc2=h_m1 Amazon Quicksight: https://quicksight.aws/ Amazon Elastic Search: https://aws.amazon.com/elasticsearch-service/?nc2=h_m1 Amazon Elasticache: https://aws.amazon.com/elasticache/?nc2=h_m1 AWS Lambda: https://aws.amazon.com/lambda/?nc2=h_m1 Deep Learning AMI: https://aws.amazon.com/marketplace/pp/B01M0AXXQB Amazon Elastic GPU (preview): https://aws.amazon.com/ec2/Elastic-GPUs/ Amazon GPU Instances: https://aws.amazon.com/ec2/instance-types/

Thank You Cyrus M Vahid cyrusmv@amazon.com