Our overall keynote presentation for the AWS Summit in Atlanta!

1. S U M M I T
A T L A N T A

2. My 3 Wishes
Learn
Experiment
Ask

4. Programming is…
The closest you’ll ever get.
to learning magic.

5. The broadest and deepest platform for today’s builders
Technical &
Business Support
AWS Marketplace
7 SERVICES
Analytics
11 SERVICES
IoT
11 SERVICES
Machine
Learning
20 SERVICES
Core
Services
5 SERVICES
Management
Tools
8 SERVICES
DevOps
11 SERVICES
Blockchain
2 SERVICES
Mobile
Services
8 SERVICES
App
Services
5 SERVICES
Infrastructure
7 SERVICES
Enterprise Apps
9 SERVICES
Migration
7 SERVICES
Security &
Compliance
19 SERVICES
9 SERVICES

6. ENCRYPTION & KEY MANAGEMENT
116 encryption enabled services
54 services integrated with key management
service
Global compliance certifications
CERTIFICATIONS
100% AWS services attested and GDPR ready
THREAT DETECTION/APP SECURITY
Threat detection
Machine Learning-
powered security
Web application firewall
DDOS protection
Fine-grained access control
Assessment & reporting
Configuration compliance
Resource & usage
auditing
Security

7. Stockholm
Hong Kong
Announced Regions
AWS Global Infrastructure

9. even faster

10. Reference: Six Common Migration Strategies
Discover
Determine
Lift and
Shift
Lift and
Recharge
Drop and
Shop
Rearchitect
REHOST
REPLATFORM
REPURCHASE
REFACTOR
RETAIN
RETIRE
Use migration tools
Modify infrastructure
Install / Setup
App code
development
Redesign
Buy COTS /
SaaS
Determine
platform
ALM / SDLC Integration
Install Config Deploy
VALIDATION
Transition
Production

11. Best
practices
Executive
leadership
Cloud Tiger
Team
Cloud center
of excellence
Educate
staff

12. Experiment
2014
Business
Case
Execute
Measure
& Pivot
Iterate
& Win
2019+
General Electric on AWS

13. M IGRATION
RESOURCES
DATABASE
M IGRATION
APP
M IGRATION
DATA TRANSFER
& STORAGE

14. AWS
Direct Connect
AWS
Snowball
AWS
Snowball
Edge
AWS
Snowmobile
AWS Storage
Gateway
Amazon
Kinesis Data
Firehose
Amazon
Kinesis Data
Streams
Amazon
Kinesis Video
Streams
Amazon S3
Transfer
Acceleration
AWS
DataSync
AWS Transfer
for SFTP
DATA TRANSFER
& STORAGE

15. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Support every workload
Enterprise Security Networking Databases
BI Storage Media

16. Define rules for your licensed
software from Microsoft,
Oracle, IBM, SAP, and others
Choose a license counting
type: vCPU, physical cores,
physical sockets, or number
of instances
Choose whether to
enforce a license limit
At-a-glance summary of
licenses and usage limits
Manage variety of
licenses from vendors
including Microsoft,
Oracle, IBM, and others
See whether or not limits
are enforced
License Manager helps manage usage limits
Windows Server on AWS
IBM DB2 on AWS
Oracle Database on AWS
On-premises SQL Server
Across cloud and on-premises

17. APP
M IGRATION

18. AWS hosts nearly 2x as many Windows Server
instances in the cloud as Microsoft

19. Most experience delivering AD as a service
Preserves SSO
High compatibility
Richest set of features
Only cloud to
use actual AD
Only cloud that
preserves SSO
Most features of
all managed AD
Users don’t have to
sign in separately
Set up directory
in under 2 min
Broadest range of
AD aware apps

20. Savings (up to 36%) with TSO Logic

21. Migration to the Cloud
Migrate to Cloud
On Demand: Monitoring
and Stabilizing
Early
modernization
Reserved: Optimization
Full Modernization
36%
savings over 1 year on
AWS vs. on-premises
50%
savings over 3 years on
AWS vs. on-premises
Disclaimer: Cost and savings projections based on migrating 700 32 bit servers at the time of calculations.
Use savings to
propel innovation
1 year 3 yearsTimeline
CostandRisk
On-premises
In AWS
Migration

22. H Y B R I D

23. Connect your on-prem
environments with AWS through
network options and services
Use your VMware software and
tools to run workloads on AWS
Run latency-sensitive workloads
on premises in a way that
seamlessly integrates with AWS
Run compute on the edge in locations
with limited or no connectivity
VMware Cloud
on AWS
Snowball Edge
Compute-Optimized
AWS
Outposts
AWS
Direct Connect
H Y B R I D

24. Momentum for VMWare Cloud on AWS

25. Placeholder: Change Healthcare

26. S U M M I T
A T L A N T A

28. M O N O L I T H
D o e s e v e r y t h i n g
From monolith…

29. …to microservices M I C R O S E R V I C E S
E a c h d o e s o n e t h i n g

30. TWO PIZZA TEAMS

31. Containers LambdaInstances
Instances, containers, and event-driven compute

32. CA PA B I LI TI ESCA TEGORI ES OPTI ONS
Instances
190+ instance types
Broadest and deepest platform choice for instances

33. Containers LambdaInstances
The most complete platform for containers

34. Customers are doing amazing things with containers

35. Modernize monolithic .NET
on-prem application as
business expanded from
private practices to large
hospital systems
Break monolithic application
into microservices
Containerize microservices,
expand and scale on cloud
Zocdoc on AWS

36. Amazon Elastic
Container Service …{ }
Container-level networking
Advanced task placement
Deep integration
with AWS platform
ECS CLI
Global footprint
Powerful scheduling engines
Auto scaling
CloudWatch metrics
Native integration with
load balancers
Highly scalable, high performance
container management system

37. Amazon Elastic
Container Service for
Kubernetes (EKS)
Platform for enterprises to run production-
grade Kubernetes
Container-level networking
Managed etcd and masters
Deep integration
with AWS platform
Kubernetes APIs
Integrated with
Kubernetes community
100% upstream Kubernetes
Highly available masters
Timely upgrades

38. Containers LambdaInstances
The most complete platform for event-driven compute

39. DATA
A m a z o n S 3
A m a z o n
C l o u d F r o n t
A m a z o n A u r o r a
S e r v e r l e s s
A m a z o n D y n a m o D B
COMMUNI CATI ONS
A m a z o n K i n e s i s
A m a z o n S N S
A m a z o n S Q S
I DENTI TY
A m a z o n C o g n i t o
A m a z o n C o g n i t o
U s e r p o o l s
MONI TORI NG & AUDI TI NG
A m a z o n C l o u d W a t c h
A W S C l o u d T r a i l
A W S X - R a y
COMPUTE
A W S L a m b d a
DEVELOPMENT
& DEPLOYMENT
A W S I A M
A W S A p p S y n c
A W S C o d e S t a r
A W S C o d e C o m m i t
A W S C o d e P i p e l i n e
A W S C o d e B u i l d
SYSTEMS DEVELOPMENT
M o b i l e
A W S I o T
NETWORK
A W S A L B
A m a z o n A P I G a t e w a y
COORDI NATI ON
A W S S t e p F u n c t i o n s
Lambda
Serverless application architectures on AWS

40. We’re running our business on Serverless, so you can too!
Step
Functions
Start 1 2 3 End
AWS
Lambda
AWS
Lambda
AWS
Lambda

41. Serverless customers
doctrine

45. Moving to open source
OPEN SOURCE ENGINES

46. Amazon
Aurora
MySQL and PostgreSQL compatible
5X faster than standard MySQL and 3X PostgreSQL
Highly available and durable
1/10th the cost of commercial grade databases
Scaled-out distributed
architecture

47. T E N S O F T H O U S A N D S O F C U S T O M E R S , 2 X C U S T O M E R G R O W T H F O R L A S T 3 Y E A R S
Amazon Aurora remains the fastest-growing service
in the history of AWS

48. Amazon
ElastiCache
f o r Redis & Mem cached
In-Memory
Amazon
Neptune
Graph Time-Series
Amazon
Timestream
Ledger
Amazon
QLDB
Amazon
DynamoDB
Key Value
Amazon
DocumentDB
Document
w ith Mo ng o DB co m patibil ity
The most complete family of purpose-built databases

49. Global tables
On-demand backups
Point-in-time recover
Read/write capacity on demand
Amazon DynamoDB
Reliable performance at any scale

50. Amazon DynamoDB: reliable performance at any scale

51. How do we think about Blockchain?

52. A fully-managed Ledger database
that provides a transparent,
immutable, cryptographically
verifiable transaction log owned
by a central trusted authority.
LEDGER
Amazon
QLDB
The evolution of databases for all your application needs

53. Amazon Managed
Blockchain
Create and manage scalable blockchain
networks
Choose Hyperledger
Fabric or Ethereum
Create blockchain networks with a few
clicks; manage them with simple API calls
Scales to support thousands of applications
running millions of transactions
Secured by AWS Key Management Service
P R E V I E W
Improved reliability of Ordering Service
with QLDB technology

56. ensuring that data is managed and used like an asset.
Define a data strategy

57. Source: Extreme Innovation

60. Before you have
a machine learning
strategy, you need
a data strategy
Data quality
Data quantity
Data source

61. 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
AWS
Direct Connect
AWS
Storage Gateway
Amazon Kinesis
Video Streams
Amazon S3
Transfer
Acceleration
AWS Transfer
for SFTP
AWS
Snowball Edge
Broadest and deepest data and analytics portfolio

62. Amazon
Redshift
Petabyte-scale data warehousing for
complex queries and fast performance
Pull together data from different sources
Highly structured
Complex queries across very large databases
20x faster than ad-hoc query services

64. THE MOST POPULAR CHOICE FOR DATA LAKES
Unmatched durability,
availability, and scalability
Cross
Region
Replication
Best security, compliance,
and audit capabilities
Business insights
into your data
Analyze exabytes of data in S3
with Amazon Redshift Spectrum
Most ways to bring data in
Amazon S3

65. S e t u p
S t o r a g e1
M o v e
d a t a2
C l e a n s e a n d
p r e p d a t a3
C o n f i g u r e a n d e n f o r c e
s e c u r i t y a n d c o m p l i a n c e
p o l i c i e s
4
M a k e d a t a a c c e s s i b l e
f o r a n a l y t i c s
5
Steps for building and managing a data lake

66. Move, store, catalog, and clean your data
faster with machine learning
Enforce security policies across multiple
services
Gain and manage new insights
AWS Lake
Formation
A secure service that allows you to build
a secure data lake in days
P R E V I E W

67. Placeholder: AGCO Corporation

69. Put machine learning in the hands of
every developer and data scientist

70. Image Source: PinterestFails.com

71. Personalized
recommendations
Inventing new
customer experiences
Fulfillment automation/
inventory management
Drones
Voice driven interactions
Machine Learning at Amazon:
A L O N G H E R I T A G E

72. More machine learning is happening on AWS than anywhere else

73. AI Services
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E XR E K O G N I T I O N
V I D E O
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS
ML Services
A m a z o n
S a g e M a k e r
Ground Truth Notebooks Algorithms + Marketplace RL Training Optimization Deployment Hosting
F R A ME W OR KS INT E R F A C E S
EC2
C5 FPGAs Greengrass
Elastic
inference Inferentia
EC2
G4
EC2 P3
& P3n
Deep learning
containers
INF R A ST R U C T U R E
ML Frameworks
+ Infrastructure

74. F R A ME W OR KS INT E R F A C E S
EC2
C5 FPGAs Greengrass
Elastic
inference Inferentia
EC2
G4
EC2 P3
& P3n
Deep learning
containers
INF R A ST R U C T U R E
Best price/performance
for model training
P 3 P3dn
ML Frameworks
+ Infrastructure
FRAMEWORKS INTERFACES
Infrastructure and frameworks for Machine Learning

75. 85% of all
TensorFlow
workloads in the
cloud runs on AWS
AWS is the platform of choice to run TensorFlow

76. 65%
Scaling efficiency
with 256 GPUs
STOCK TE N SOR F L OW
90%
Scaling efficiency
With 256 GPUS
A WS-OP TIM ZE D TE N SOR F L OW
Train twice as fast with TensorFlow

77. Running inference
in production
Drives the majority of cost
for machine learning
INFERENCE
TRAINING
INFRASTRUCTURE
COSTS

78. COMING LATE 2019
Provision just the amount of GPU you
need for faster inference
Amazon
Elastic Inference
Machine learning inference chip
AWS Inferentia

79. F R A ME W OR KS INT E R F A C E S
EC2
C5 FPGAs Greengrass
Elastic
inference Inferentia
EC2
G4
EC2 P3
& P3n
Deep learning
containers
INF R A ST R U C T U R E
ML Frameworks
+ Infrastructure
AI Services
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E XR E K O G N I T I O N
V I D E O
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS
ML Services
A m a z o n
S a g e M a k e r
Ground Truth Notebooks Algorithms + Marketplace RL Training Optimization Deployment Hosting

80. SET UP AND MANAGE
ENVIRONMENTS FOR TRAINING
HYPERPARAMETER OPTIMIZATION
AND SAGEMAKER NEO
TR AIN DEPLO Y
SCALE AND MANAGE THE
PRODUCTION ENVIRONMENT
DEPLOY MODEL
IN PRODUCTION
Built-in, high
performance
algorithms and
frameworks
MORE THAN 150 ADDITIONAL
ALGORITHMS AND MODELS IN AWS
MARKETPLACE
REDUCE DATA LABELING COSTS
BY UP TO 70%
Fully-managed
reinforcement
learning algorithms
with SageMaker RL
TRAIN MODELS WITHOUT LABELED
TRAINING DATA
B U ILD
FAST AND ACCURATE DATA LABELING
WITH GROUND TRUTH
OptimizationOne-click
training
One-click
deployment
Fully managed with
auto-scaling, health
checks, automatic
handling of node failure,
and security checks
Fast and accurate
data labeling with
Ground Truth
Pre-built notebooks
for common problems
Bringing machine
learning to all
developers
Amazon
SageMaker

81. More than ten thousand customers using Amazon SageMaker

82. F R A ME W OR KS INT E R F A C E S
EC2
C5 FPGAs Greengrass
Elastic
inference Inferentia
EC2
G4
EC2 P3
& P3n
Deep learning
containers
INF R A ST R U C T U R E
ML Frameworks
+ Infrastructure
AI Services
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E XR E K O G N I T I O N
V I D E O
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS
ML Services
A m a z o n
S a g e M a k e r
Ground Truth Notebooks Algorithms + Marketplace RL Training Optimization Deployment Hosting

83. Mistakes were made

84. REKOGNITION
IMAGE AND VIDEO
T E X T R A C T
Deep learning based image and
video analysis services
Identify objects, people text,
scenes, activities
Automatically extract text
and data from virtually any
document
Uses ML to go beyond simple
OCR to also identify content
in forms and tables
Vision
DOG
99.3%
RUG
83.0%

85. A M A Z O N
P O L L Y
52 Voices across 25 languages
Lip-Syncing & Text Highlighting
Fine-grained Voice Control
A M A Z O N
T R A N S C R I B E
Support for 16KHz and 8KHz
Streaming support
A M A Z O N
T R A N S L A T E
24 language pairs
Neural machine translation
High accuracy
A M A Z O N
C O M P R E H E N D
Sentiment, Entities, Key
phrases, Languages, Topics
A M A Z O N
L E X
Build conversational
apps in minutes
A M A Z O N
C O M P R E H E N D
M E D I C A L
Build conversational
apps in minutes

86. Brainstorming
Custom modeling
Training
Work side-by-side with Amazon experts
Practical education on ML for new
& experienced practitioners
Based on the same material used
to train Amazon developers
Ways to get started

87. AWS DeepRacer

89. Build reinforcement learning model
DeepRacer League Races at AWS Summits
Winners of each DRL Race and top scorers compete
in Championship Cup at re:Invent 2019
World’s first global autonomous racing league

90. What about Machine Learning at the edge?

91. Sources: McKinsey & Co., Inc., Statista
car lightbulb
bicycle
door lock
camera
factory
cart
coffee pot house
bank
windfarmpolice
equipment
plane utilitymedical
equipment
thermostat
Source: Statista.com
75 billionC O N N E C T E D D E V I C E S
online by:
2025
The source of data is increasing
coming from billions of edge devices

92. Working with edge devices is challenging

93. 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
AWS has the most complete platform for IoT

94. Fashion Tech & Healthcare

95. AWS IoT customers span all industries

98. S U M M I T
A T L A N T A