AWS re:Invent is an annual global conference of the Amazon Web Services community held in Las Vegas. In 2017, we held 1000+ breakout sessions and attracted over 40,000 attendees. The event offers expanded opportunities to learn about the latest AWS releases, use cases and business benefits, not to mention diving deep into hot topics and meeting with our subject matter experts.
Missed it? Don’t worry, we are bringing AWS re:Invent to Hong Kong on Jan 18, 2018. Packed in a day, AWS re:Invent 2017 Recap Hong Kong will showcase new releases announced at re:Invent 2017 on Serverless & Container, DevOps & Mobile, Artificial Intelligence & Machine Learning and more. Local customers will also be invited to share their re:Invent experience and success stories with AWS.
Discover the latest services and features from Amazon Web Services and learn how to integrate them into your applications
1. W E L C O M E
AWS re:Invent 2 0 1 7 Recap
Solutions Updates
D e a n S a m u e l s
H e a d o f S o l u t i o n s A r c h i t e c t u r e
H o n g K o n g & Ta i w a n
A m a z o n W e b S e r v i c e s
6. CORE SERVICES
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
MARKETPLACE
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
TECHNICAL & BUSINESS SUPPORT
Support
Professional
Services
Optimization
Guidance
Partner
Ecosystem
Training &
Certification
Solutions Management Account Management
Security & Billing
Reports
Personalized
Dashboard
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
MIGRATIONHYBRID ARCHITECTUREENTERPRISE APPSMACHINE LEARNINGIoTMOBILE SERVICESDEV OPSANALYTICS
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
Facial Recognition &
Analysis
Facial Search
Patching
Contact Center
M O S T R O B U S T , F U L L Y F E A T U R E D T E C H N O L O G Y I N F R A S T R U C T U R E P L A T F O R M
7. 516
24 48 61 82
159
280
722
1,017
LAUNCHES
2008 2009 2010 2011 2012 2013 2014 2015 2016
1,300+
2017
New capabilities daily
P A C E O F I N N O V A T I O N
9. B R O A D E S T S P E C T R U M O F C O M P U T E I N S T A N C E S
Burstable
T 2
Big Data
Optimized
H 1
Memory
Optimized
R 4
In-memory
X 1
High
I/O
I 3
Compute
Intensive
C 5
Graphics
Intensive
G 3
General
Purpose
GPU
P 3
Memory
Intensive
X 1 e
General
Purpose
M 5
Vir t ual
Pr ivat e
Ser ver s
Bare Metal
High I/O
I 3 m
Dense
Storage
D 2 F 1
FPGA
Amazon
Lightsail
EC2 Elastic GPUs
Graphics acceleration for
EC2 instances
EC2 Spot Instances
• Hibernation
• No Bid Pricing
N E
W !
NEW! NEW! NEW!
NEW!
11. Service integrations are at
the container level
Scales to support clusters
and applications of any size
Integration with entire
AWS platform
1 2 3
ALB, Auto Scaling, Batch, Elastic Beanstalk,
CloudFormation, CloudTrail, CloudWatch Events,
CloudWatch Logs, CloudWatch Metrics, ECR, EC2 Spot,
IAM, NLB, Parameter Store, and VPC
Why customers love ECS
AMAZON ELASTIC CONTAINER SERVICE (ECS)
The easiest way to deploy and manage containers
13. Managed Kubernetes on AWS
Amazon Elastic Container
Service for Kubernetes (EKS)
Available in preview today
NEW!
14. A M A Z O N E L A S T I C C O N T A I N E R S E R V I C E F O R K U B E R N E T E S ( E K S )
Hybrid cloud
compatible
Highly
available
Automated
upgrades and
patches
Integrated with
AWS Services
CloudTrail, CloudWatch, ELB,
IAM, VPC, PrivateLink
15. … B U T W H A T E L S E ?
M A N A G E D C L U S T E R S A R E G R E A T …
16. Run containers without managing
servers or clusters
AWS Fargate
Available for ECS today
Available for EKS in 2018
NEW!
17. A W S F A R G A T E
No clusters
to manage
Manages underlying
infrastructure
Easy to run,
easy to scale
Run containers on ECS and EKS without managing servers
19. A W S L A M B D A I S E V E R Y W H E R E
Event-driven services Event sources Lambda inside
AWS Lambda Amazon S3 Amazon CloudFormation AWS IoT
Amazon API Gateway Amazon DynamoDB Amazon CloudWatch Logs AWS IoT Button
AWS Step Functions Amazon Kinesis Streams Amazon CloudWatch Events AWS Greengrass
AWS X-Ray Amazon Kinesis Firehose AWS CodeCommit AWS Snowball Edge
Amazon SNS AWS Config AWS Lambda@Edge
Amazon SES Amazon Lex
Amazon Cognito Amazon CloudFront
AWS IoT
AWS Lambda
20. E V O L U T I O N O F C O M P U T E
AWS
CodeDeploy
AWS
CloudTrail
AWS Config
and Config
Rules
AWS IAM
AWS
PrivateLink
Managed NAT
Gateway
VMware Cloud
on AWS
Group
Resource
Tagging
21. Everything is ... a CLOUD!
Everything is … BIG DATA!
Everything is … MACHINE LEARNING!
A L O T O F M L B U Z Z O U T T H E R E T O D A Y
22. A L O N G H E R I T A G E O F M A C H I N E L E A R N I N G A T A M A Z O N
Personalized
recommendations
Inventing entirely
new customer
experiences
Fulfillment
automation and
inventory
management
Drones Voice driven
interactions
26. B O T T O M L A Y E R : F R A M E W O R K S A N D I N T E R F A C E S
P2
NVIDIA
Tesla V100
GPUs
P3
1 Petaflop of compute
NVLink 2.0
5,120 Tensor cores
128GB of memory
~14X faster than P2
P3 Instance AWS Deep Learning AMI
27. L I S T E N T O A N D I N V E N T F O R C U S T O M E R S
Frameworks
KERAS
Interfaces
29. ML IS STILL TOO COMPLICATED FOR EVERYDAY DEVELOPERS
Collect and prepare
training data
Choose and
optimize your ML
algorithm
Set up and manage
environments for
training
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage
the production
environment
30. D E V E L O P E R S T H R O W U P T H E I R H A N D S I N F R U S T R A T I O N
31. Easily build, train, and deploy machine
learning models
Amazon SageMaker
Generally available today
NEW!
32. A M A Z O N S A G E M A K E R S O L V E S A L L O F T H E S E P R O B L E M S
Collect and prepare
training data
Choose and
optimize your ML
algorithm
Set up and manage
environments for
training
Deploy model
in production
Scale and manage
the production
environment
Train and tune model
(trial and error)
33. A M A Z O N S A G E M A K E R
Pre-built
notebooks for
common
problems
BUILD
Choose and
optimize your ML
algorithm
Set up and manage
environments for
training
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage
the production
environment
34. A M A Z O N S A G E M A K E R
Pre-built
notebooks for
common
problems
K-Means Clustering
Principal Component Analysis
Neural Topic Modelling
Factorization Machines
Linear Learner - Regression
XGBoost
Latent Dirichlet Allocation
Image Classification
Seq2Seq
Linear Learner - Classification
ALGORITHMS
Apache MXNet
TensorFlow
Caffe2, CNTK,
PyTorch, Torch
FRAMEWORKS
Set up and manage
environments for
training
Train and tune
model (trial and
error)
Deploy model
in production
Scale and manage the
production environment
Built-in, high
performance
algorithms
BUILD
36. A M A Z O N S A G E M A K E R
Pre-built
notebooks for
common
problems
Built-in, high
performance
algorithms
One-click
training
BUILD TRAIN
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage
the production
environment
37. A M A Z O N S A G E M A K E R
Pre-built
notebooks for
common
problems
Built-in, high
performance
algorithms
One-click
training
Hyperparameter
optimization
BUILD TRAIN
Deploy model
in production
Scale and manage
the production
environment
38. A M A Z O N S A G E M A K E R
Pre-built
notebooks for
common
problems
Built-in, high
performance
algorithms
One-click
deployment
One-click
training
Hyperparameter
optimization
Scale and manage
the production
environment
BUILD TRAIN DEPLOY
39. A M A Z O N S A G E M A K E R
Fully managed
hosting with auto-
scaling
One-click
deployment
Pre-built
notebooks for
common
problems
Built-in, high
performance
algorithms
One-click
training
Hyperparameter
optimization
BUILD TRAIN DEPLOY
40. CAN WE DO MORE TO PUT ML IN
THE HANDS OF ALL DEVELOPERS
(LITERALLY)?
41. AWS DeepLens
The world’s first wireless, deep learning
enabled video camera for developers
A v a i l a b l e o n a m a z o n . c o m n e x t y e a r
NEW!
42. W H A T I S A W S D E E P L E N S ?
HD video camera
Custom-designed
deep learning
inference engine
Micro-SD
Mini-HDMI
USB
USB
Reset
Audio out
Power
HD video camera
with on-board
compute optimized
for deep learning
Tutorials, examples,
demos, and pre-built
models
From unboxing to
first inference in
<10 minutes
Integrates with Amazon
SageMaker and AWS
Lambda
10
MIN
44. Search, analyze, and organize millions of images
A M A Z O N R E K O G N I T I O N
Objects and scenes
Facial analysis and recognition
Inappropriate content detection
Celebrity recognition
Image in text recognition
A M A Z O N R E K O G N I T I O N
45. Real-time and batch video analytics
Amazon
Rekognition Video
Generally available
today
NEW!
46. A M A Z O N R E K O G N I T I O N V I D E O
A M A Z O N R E K O G N I T I O N
V I D E O
Video in. People, activities, and details out.
Objects and scenes
Facial analysis and recognition
Inappropriate content detection
Celebrity recognition
Person tracking
47. A M A Z O N R E K O G N I T I O N V I D E O
Easy to use Batch processing Processes
real-time video
Continually trained Low costTimestamp
generation
48. V I S I O N LAN GU AGE
A P P L I C A T I O N S E R V I C E S
Amazon Rekognition Image Amazon Polly Amazon LexAmazon Rekognition Video
49. S T R E A M I N G D A T A F R O M C O N N E C T E D D E V I C E S
50. Securely ingest and store video, audio, and
other time-encoded data
Amazon Kinesis
Video Streams
Generally available today
NEW!