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.

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

29. aws.amazon.com/blogs
aws.amazon.com/new
@AWScloud @AWS_UKI

30. Thank You!
@IanMmmm
Ian Massingham, Worldwide Lead, AWS Evangelism