[AWS Dev Day] 기조연설 – Olivier Klein AWS 신기술 부문 책임자, 정성권 삼성전자 수석
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The document discusses how machine learning and artificial intelligence are enabling rapid innovation through experimentation. It notes that innovation requires the ability to conduct many experiments without suffering major consequences from failed experiments. The document outlines how modern application design approaches like microservices lower the cost of experimentation by reducing the impact of changes. It also discusses how serverless architectures allow companies to focus on business value rather than infrastructure management. Overall, the document advocates for a distributed, data-centric approach to software development enabled by machine learning and artificial intelligence.
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[AWS Dev Day] 기조연설 – Olivier Klein AWS 신기술 부문 책임자, 정성권 삼성전자 수석
- 2. Build in 2019: Distributed, Open, Data Centric and Artificially Intelligent Olivier Klein Head of Emerging Technologies, Asia-Pacific, AWS
- 3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Portability Data Centricity Abstraction & Integration Distributed Applications Pace of Innovation Changing Nature of Software Development
- 4. FeedbackIdeas Experiment Innovation Flywheel Experiments power the engine of rapid innovation
- 5. Invention requires two things: the ability to try a lot of experiments, and not having to live with the collateral damage of failed experiments. Andy Jassy CEO, Amazon Web Services
- 7. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Modern App Design lowers cost of experimentation
- 8. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. What changes have to be made in this new fast paced world? Architectural patterns Operational model Software delivery
- 9. When the impact of change is small, release velocity can increase Monolith Does everything Microservices Does one thing
- 10. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Microservices with independent functions, developers and SLAs
- 11. FUNCTION API API MICROSERVICE FUNCTION EVENT API MICROSERVICE EVENT API MICROSERVICE APPLICATION APIs and Event Messaging
- 12. Integration options from AWS Queues Simple Fully-managed Any volume Pub/sub Simple Fully-managed Flexible Orchestration Powerful Fully-managed Low code Amazon API Gateway Amazon SQS Amazon SNS AWS Step Functions Connect Efficient Fully-managed Real-time Client-to-Service Service-to-Service Orchestration
- 14. API MICROSERVICE EVENT API MICROSERVICE APPLICATION Microservice Architecture CODE SDKs DATASTORES
- 15. Amazon DynamoDB Amazon ElastiCache Key Value In-Memory Amazon Neptune Graph Relational Time-Series Amazon RDS Amazon Aurora Amazon DocumentDB Document Amazon Timestream Ledger Amazon QLDB Choose the right data store for your microservice
- 16. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Isn’t all of this very hard now that we have lots of pieces to operate?
- 17. Don’t be a server hugger, think serverless!
- 18. What is serverless? No infrastructure provisioning, no management Automatic scaling Pay only for value Highly available and secure
- 19. Focus on creating business value CUSTOMER Remove heavy lifting with serverless everything AWS Messaging & Orchestration Compute Physical Infrastructure API Business logic Storage & Databases Serverless provide great agility with the least effort
- 20. AWS Lambda AWS Fargate Amazon API Gateway Amazon SNS Amazon SQS AWS Step Functions COMPUTE DATA STORES INTEGRATION Amazon Aurora Serverless Amazon S3 Amazon DynamoDB AWS AppSync
- 21. Serverless compute engine for containers Long-running Bring existing code Fully managed orchestration AWS Fargate Let’s focus on compute for a second Serverless event-driven code execution Short-lived All language runtimes Data source integrations AWS Lambda
- 22. New: Lambda Layers Lets functions easily share code: Upload layer once, reference within any function Promote separation of responsibilities, lets developers iterate faster on writing business logic Built-in support for secure sharing through ecosystem
- 23. Monolith development lifecycle MonitorReleaseTestBuild Developers Delivery pipelines Services
- 24. Microservice development lifecycle Developers Services MonitorReleaseTestBuild Delivery pipelines MonitorReleaseTestBuild MonitorReleaseTestBuild MonitorReleaseTestBuild MonitorReleaseTestBuild MonitorReleaseTestBuild
- 25. 50,000,000 Amazon in 2014, average of 1.5 deployments per second
- 26. AWS CodeBuild + Third Party AWS CodeCommit AWS CodeBuild AWS CodeDeploy AWS X-Ray AWS CodePipeline MONITORDEPLOYTESTBUILDSOURCEAUTHOR AWS Cloud 9 IDE Toolkits Amazon CloudWatch AWS CloudFormation AWS SAMMODEL AWS Developer Tools for modern software delivery
- 27. Continuous security Protecting your customers and your business in an agile world
- 29. Sungkwon Jung Principal Architect Samsung Electronics
- 33. 마이그레이션을 위한 데브옵스 팀 역할 인프라스트럭처 엔지니어 데이터베이스 관리자
- 34. Legacy DB
- 37. Copy Export Import Loading Initial Data CDC (Change Data Capture) Corporate data center AWS Cloud
- 40. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Containers / Serverless Web Standards Frameworks APIs / Microservices CLIENT PORTABILITY BACKEND PORTABILITY INFRA PORTABILITY SDKs Cross-Platform Native Apps
- 41. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. PHOTOGRAMMETRY
- 42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. DEMO Amazon Sumerian Pictures
- 44. AWS IoT Device SDK Amazon FreeRTOS AWS IoT Device Tester AWS IoT Greengrass AWS IoT Events AWS IoT Analytics AWS IoT SiteWise AWS IoT Device Management AWS IoT Things Graph AWS IoT Core AWS IoT Device Defender Broad and deep IoT services
- 45. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Robotics is undergoing fundamental change in collaboration, autonomous mobility, and increasing intelligence • Logistics • Construction • Retail • Hospitality • Healthcare Robots are being put to work every day across many industries • Agriculture • Energy Management • Oil and Gas • Facilities Management • Household chores
- 46. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 47. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Development Environment Simulation Environment Fleet Management Cloud Extensions for ROS and contribution to ROS2 AWS Robomaker Easily develop, test, and deploy intelligent robotics applications at scale
- 48. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. DEMO
- 50. What has Changed for me as a Developer? Increasing amount of devices are being connected with growing amounts of capabilities Devices and apps do not serve a single purpose anymore – entire ecosystems are building through smart and connected systems Global user base with the desire to interact However, laws of physics haven’t changed – latency is bound by physical distance
- 51. What has Changed for me as a Developer? Strategies Create globally distributed data stores Deploy logic closer to the edge when app is latency sensitive Gracefully handle intermittent network connectivity Caching!
- 52. Relational: Amazon Aurora with cross-region replication Non-relational: Amazon DynamoDB with cross-region replication Objects: Amazon S3 with cross-region replication Resolution: Amazon Route 53 with Latency Based Routing Logic: AWS Lambda@Edge for code logic Cache: Amazon CloudFront Distributed Datastores and Applications
- 53. Automatically updates the data applications in real time, and updates data for offline users as soon as they reconnect Makes it easy to build applications that deliver responsive, collaborative user experiences Schema designed using GraphQL and attached to AWS resources AWS AppSync – Handle Intermittent Networks
- 54. Edge Location AWS Greengrass AWS Greengrass Core AWS Greengrass – Move your Logic to the Edge
- 56. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Stop throwing data away Make it available to more users Arm users with more data processing technologies Think about data as an asset, not a cost
- 57. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Glacier Deep Archive Lowest cost storage available in the cloud…even lower than on-premises tape No tape to manage Designed for 99.999999999% durability Recover data in hours vs. days/weeks $0.00099/GB/month Less than 1/4th the cost of Glacier
- 58. What has Changed for me as a Developer? The ability to effectively and quickly derive insights from your data lake is crucial to the success of the business Compute and storage should be decoupled to accommodate for cost-effective yet fast data growth Data Transformation is not costly, don’t worry too much about data structures
- 59. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Cloud data lakes are the future Customers want: A single data store that is scalable & cost effective To store data securely in various standard formats To analyze their data in a variety of ways Cloud Data Lake Infrastructure Decoupled Storage & Compute Resources Security & Governance Data Migration Streaming Services Data Warehouse Big Data Processing Serverless Data Processing Real-time Analytics Operational Analytics Predictive AnalyticsETL & Catalog Data Management Decouple compute and storage!
- 60. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. VISUALIZATION & ML ANALYTICS DATA LAKE DATA MOVEMENT Amazon QuickSight Amazon SageMaker Amazon Redshift Amazon EMR AWS Glue Amazon Athena Amazon Elasticsearch Service Amazon Kinesis Data Analytics Amazon S3 Amazon Lake Formation AWS Glue AWS Database Migration Service AWS Snowmobile AWS Snowball Amazon Kinesis Data Firehose Amazon Kinesis Data Streams Amazon Managed Streaming for Kafka Broadest and deepest data and analytics portfolio AWS Direct Connect AWS Storage Gateway Amazon Kinesis Video Streams Amazon S3 Transfer Acceleration AWS Transfer for SFTP AWS Snowball Edge
- 62. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 63. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Station DepartureArrival
- 64. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. DepartureArrival Station
- 65. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. DepartureArrival Station
- 66. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Computer Vision to identify empty space and detect object misplacements
- 67. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 68. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 69. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 70. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 72. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Put machine learning in the hands of every IT professional Our mission at AWS
- 73. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. KERAS Frameworks C5 C5n P3 P3dn Interfaces Infrastructure Vision Speech Languages Chatbots Vertical AMAZON SAGEMAKER AMAZON SAGEMAKER GROUND TRUTH AMAZON SAGEMAKER RL AWS MARKETPLACE FOR ML AMAZON SAGEMAKER NEO AWS DEEPRACER AWS DEEPLENS AMAZON ELASTIC INFERENCE AWS INFERENTIA AWS GREENGRASS AMAZON PERSONALIZE AMAZON FORECASTAMAZON TEXTRACT AMAZON REKOGNITION AMAZON LEX AMAZON POLLY AMAZON TRANSCRIBE AMAZON COMPREHEND AMAZON TRANSLATE AI Services ML Services ML Frameworks + Infrastructure
- 74. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Transcribe 8Khz call recordings with high accuracy Analyze the text with Amazon Comprehend Visualize results on Amazon QuickSight Call center insights Amazon Transcribe Amazon Comprehend Amazon Connect Amazon Quicksight
- 75. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. KERAS Frameworks C5 C5n P3 P3dn Interfaces Infrastructure Vision Speech Languages Chatbots Vertical AMAZON SAGEMAKER AMAZON SAGEMAKER GROUND TRUTH AMAZON SAGEMAKER RL AWS MARKETPLACE FOR ML AMAZON SAGEMAKER NEO AWS DEEPRACER AWS DEEPLENS AMAZON ELASTIC INFERENCE AWS INFERENTIA AWS GREENGRASS AMAZON PERSONALIZE AMAZON FORECASTAMAZON TEXTRACT AMAZON REKOGNITION AMAZON LEX AMAZON POLLY AMAZON TRANSCRIBE AMAZON COMPREHEND AMAZON TRANSLATE AI Services ML Services ML Frameworks + Infrastructure
- 76. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon SageMaker Fast & accurate data labeling Built-in, high performance algorithms & notebooks BUI L D 1 One-click training and tuning T R A I N Model optimization 2 Fully managed hosting with auto-scaling and elastic inference One-click deployment D E P L O Y 3 Custom machine learning for your business
- 77. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Image Classification and Object Detection
- 78. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. DEMO
- 79. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Understand physical security footage
- 80. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. KERAS Frameworks C5 C5n P3 P3dn Interfaces Infrastructure Vision Speech Languages Chatbots Vertical AMAZON SAGEMAKER AMAZON SAGEMAKER GROUND TRUTH AMAZON SAGEMAKER RL AWS MARKETPLACE FOR ML AMAZON SAGEMAKER NEO AWS DEEPRACER AWS DEEPLENS AMAZON ELASTIC INFERENCE AWS INFERENTIA AWS GREENGRASS AMAZON PERSONALIZE AMAZON FORECASTAMAZON TEXTRACT AMAZON REKOGNITION AMAZON LEX AMAZON POLLY AMAZON TRANSCRIBE AMAZON COMPREHEND AMAZON TRANSLATE AI Services ML Services ML Frameworks + Infrastructure
- 81. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS is framework agnostic Choose from popular frameworks Run them fully managed Or run them yourself
- 82. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Running inference in production Inference Training Infrastructure costsDRIVES THE MAJORITY OF COST FOR MACHINE LEARNING
- 83. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. COMING LATE 2019 Add GPU acceleration to any Amazon EC2 instance for faster inference at much lower cost (up to 75% savings) Amazon Elastic Inference Custom high performance machine learning inference chip that will reduce the cost of inference by 10X AWS Inferentia
- 84. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. How do you teach machine learning models to make decisions when there is no training data?
- 86. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Learn by interacting with the real world Model problem as a simulation environment Trial and error Observe results Optimise learning strategy to maximise long-term reward
- 87. Vehicle routing Objective Fulfill customer orders S T AT E Current location, distance from homes … A C T I O N Accept, pick up, and deliver order R E W A R D Positive when we deliver on time Negative when we fail to deliver on time Applicable in many domains and industries
- 88. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon SageMaker RL New machine learning capabilities in Amazon SageMaker to build, train and deploy with reinforcement learning Fully managed RL algorithms TensorFlow, MXNet, Intel Coach, and Ray RL 2D and 3D simulation environments via OpenGym Simulate with Sumerian and AWS RoboMaker Example notebooks and tutorials
- 89. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. DEMO Amazon Sumerian Amazon Sagemaker RL
- 91. Experiment quickly using modern application architectures and cloud services Deploy globally or close to the edge, and build on portable standards Data and intelligence is an asset – AWS makes it easy and cost-effective to use cloud data lakes and ML Focus on what’s core to your business - leave the heavy lifting to someone else In Closing