What's New & What's Next from AWS?
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The document outlines the evolution and advancements of AWS technologies, highlighting a growth in active customers and the expansion of services offered. Key topics include cloud computing capabilities, data analytics, machine learning, and integrated management tools that enable businesses to leverage AWS for various applications. It emphasizes the accessibility of big data analytics and machine learning, making sophisticated technologies available to developers and enterprises alike.
What's New & What's Next from AWS?
- 1. What’s New & What’s Next @IanMmmm Ian Massingham, Worldwide Lead, AWS Evangelism
- 2. Millions Of Ac tive Customers Per Month
- 3. Largest Number Of Startup Customers
- 4. Largest Number Of Enterprise Customers
- 5. Where Are We In The Cloud’s Evolution? In 2014 New normal In 2015 Control over your own destiny
- 6. Today Harder, Faster, Better, Stronger
- 7. Compute VMs, Auto-scaling, Load Balancing, Containers, Virtual Private Servers, Batch Computing, Cloud Storage Object, Blocks, File, Archivals, Import/Export, Exabyte-scale data CDN Databases Relational, NoSQL, Caching, Migration, PostgreSQL Networking CORE Integrated Networking Rules Engine Device Shadows Device SDKs Device Gateway Registry Local Compute Custom Model Training & Hosting Conversational Chatbots Virtual Desktops App Streaming Schema Conversion Image & Scene Recognition Sharing & Collaboration Exabyte-Scale Data Migration Text to Speech Corporate Email Application Migration Database Migration Regions Availability Zones Points of Presence Data Warehousing Business Intelligence Elasticsearch Hadoop/Spark Data Pipelines Streaming Data Collection ETL Streaming Data Analysis Interactive SQL Queries Queuing & Notifications Workflow Email Transcoding Deep Learning (Apache MXNet, TensorFlow, & others) Server MigrationCommunications Business Apps Business Intelligence DevOps Tools Security Networking StorageDatabases API Gateway Single Integrated Console Identity Sync Mobile Analytics Mobile App Testing Targeted Push Notifications One-click App Deployment DevOps Resource Management Application Lifecycle Management Containers Triggers Resource Templates Build & Test Analyze & Debug Identity Management Key Management & Storage Monitoring & Logs Configuration Compliance Web Application Firewall Assessment & Reporting Resource & Usage Auditing Access Control Account Grouping DDOS Protection Support Professional Services Optimization Guidance Partner Ecosystem Training & Certification Solutions Management Account Management Security & Billing Reports Personalized Dashboard TECHNICAL & BUSINESS SUPPORT MARKETPLACE Monitoring Manage Resources Data Integration Integrated Identity & Access Integrated Resource & Deployment Management Integrated Devices & Edge Systems Resource Templates Configuration Tracking Server Management Service Catalogue Search HYBRIDANALYTICS MOBILE SERVICESDEV/OPS IoT MACHINE LEARNING ENTERPRISE APPS MIGRATION APP SERVICES INFRASTRUCTURE SECURITY & COMPLIANCE MANAGEMENT TOOLS Compute VMs, Auto-scaling, Load Balancing, Containers, Virtual Private Servers, Batch Computing, Cloud Functions, Elastic GPUs, Edge Computing Storage Object, Blocks, File, Archivals, Import/Export, Exabyte-scale data transfer CDN Databases Relational, NoSQL, Caching, Migration, PostgreSQL compatible Networking VPC, DX, DNS CORE SERVICES Facial Recognition & Analysis Facial Search Patching Contact Center Most Complete Technology Platform
- 8. Data Warehousing Business Intelligence Elasticsearch Hadoop/Spark Data Pipelines Streaming Data Collection ETL Streaming Data Analysis Interactive SQL Queries ANALYTICS
- 9. Hadoop, Spark, Presto, HBase, Hive, Mahout, Pig, Zeppelin Amazon EMR Elasticsearch Amazon Elasticsearch Interactive queries Amazon Athena Data warehouse Amazon Redshift Redshift Spectrum Business intelligence Amazon QuickSight Real-time streaming data Amazon Kinesis Analytics Storage and databases AWS Has Made Petabyte-scale Analytics Accessible To Companies Of All Sizes
- 10. No infrastructure or clusters to set up and manage Results within seconds Query S3 directly and right away Pay for just the queries you run No need to move data to Athena Amazon Athena Interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL
- 11. Amazon EMR Analyze large data sets using popular big data processing frameworks Fully customizable clusters Code your own applications Hadoop, Spark, Presto, HBase
- 12. Amazon Redshift Analyze large data sets using popular big data processing frameworks Highly structured Complex queries across very large databases Pull together data from different sources 20x faster than ad- hoc query services
- 13. Amazon Redshift Analyze large data sets using popular big data processing frameworks Highly structured Complex queries across very large databases Pull together data from different sources 20x faster than ad- hoc query services
- 14. Query S3 directly or join data across Redshift and S3 Support for CSV, JSON, ORC, and Parquet data formats Scale Redshift compute and storage separately Amazon Redshift Redshift Query Engine Redshift Data Data Lake Amazon S3 Redshift Spectrum Extend Redshift Queries To Data In Amazon S3
- 15. Extract, Transform, Load: Ubiquitous And Tedious Tedious, “fiddly” boilerplate code Understand what data you have and where Done repeatedly, reliably, and at scale Resource- intensive and irregular
- 16. AVAILABLE NOW Fully managed Data Catalog and ETL service AWS Glue
- 17. AWS Glue Fully managed Data Catalog and ETL service Discovers and catalogs your data Schedules and runs your ETL jobs Generates customizable transformation code Serverless - provisions and manages your infrastructure
- 18. Build your data catalog Generate & edit transformations Schedule and run your jobs
- 19. Machine Learning Is Undergoing A Renaissance…
- 20. The Challenge For Machine Learning: Scale Data Training Inference At the Edge
- 21. Tons of GPUs and CPUs Serverless Tons of GPUs Elastic capacity Pre-built images PBs of existing data Aggressive migration New data created on AWS IoT and mobile deployment Mobile optimization IoT device optimization The Challenge For Machine Learning: Scale Data Training Inference At the Edge
- 22. Machine Learning On AWS Today
- 23. SERVICES PLATFORMS ENGINES INFRASTRUCTURE Amazon ML Spark & EMR Kinesis Batch ECS GPU CPU IoT Mobile Apache MXNet Caffe 2 Theano PyTorch CNTKTensorFlow Vision Amazon Rekognition Chat Amazon Lex Speech Amazon Polly Machine Learning in the hands of every developer
- 24. Early detection of diabetic complications
- 25. New Pinterest Lens mobile app uses TensorFlow to let users find pins based on the pictures they take
- 26. Real time, per pixel object segmentation
- 27. Thousands of Amazon Engineers Focused on Machine Learning
- 28. https://reinvent.awsevents.com/ 27 November – 1 December Las Vegas, NV
- 30. Thank You! @IanMmmm Ian Massingham, Worldwide Lead, AWS Evangelism