ReCap for Dr. Werner Vogels Key Notes Young Yang, Solutions Architect 亞馬遜 AWS 於 2018 年 11 月底在美國拉斯維加斯所舉辦的第七屆 AWS re:Invent 2018 大會，在 AWS 客戶、合作夥伴、媒體人士、產業分析師及 AWS 員工共襄盛舉下，與會人數再創新高，超過 5 萬人。會中 AWS 發布超過 20 款雲端方案，且一半以上專攻雲端 AI、機器學習、物聯網，包括對 SageMaker 強化更多進階功能，推出第一款專用的機器學習推論晶片、加入深度的機器學習運算法支援，及其他包括儲存、資料庫、混合雲、邊緣運算 IoT 等解決方案。而具備微型機器學習能力的迷你自駕遙控車 DeepRacer 的現身，驚人之舉不僅抓人眼球，深入客戶體驗的用心，更成功抓住全球使用者的心。 為讓您與全球先進技術同步，共享最新趨勢資訊，解決您開發機器學習和發展 AIoT 所遇到的難題，AWS 台灣團隊將於 2019 年 1 月 31 日 (四) 舉辦《AWS re:Invent 2018 Recap 台北》，特別嚴選最適切國內諸位先進和企業需求的內容，從「技術創新」、「AIoT」兩大分組議程，發表 AWS 的新服務和新方案。大會除了邀請亞馬遜 AWS 大中華區首席雲計算企業顧問 (Principal Evangelist) 張俠博士分享 AWS 的解決方案藍圖外，眾多 AWS 資深專家也將分享包含機器學習、深度學習推理加速等新方案，完全託管的文件系統、資料庫，無伺服器、容器技術與安全性，以及大數據與分析、物聯網服務應用、儲存方案等最新技術。歡迎您親臨會場，全方位體驗 AWS 新服務將能為您創造的驚人創新之效益。

1. ReCap for Dr. Werner Vogels Key Notes
Young Yang, Solutions Architect

5. Almost 14 years

6. Agenda
1. Reducing your blast radius
2. Cloud-native as a foundation for innovation
3. The right tool (DB) for the right job (workload)
4. Everyone wants to just focus on business logic
5. Are you well architected?

7. Reducing your blast radius

8. Reducing your
blast radius

10. Blast radius
• Who is impacted?
• How many workloads?
• What functionality?
• How many locations?

11. Typical service application
Compute
Service
Storage
Compute
Service
Storage
Compute
Service
Storage

12. Cell-based architecture
Compute
Cell 0
Compute
Cell n
Cell Router
Service
Storage
Compute
Cell 1
Storage Storage

13. System properties
Cell 0
Cell router
Service
Cell 1 Cell n
• Workload isolation
• Failure containment
• Scale-out vs. scale-up
• Testability
• Manageability
Cell n+1
X

14. Cells and Availability zones
Regional
service
Zone b Zone cZone a Zone b Zone cZone a
Regional service cell
Regional service cell
Regional service cell
Without Cells With Cells

15. Availability Zone failure
Regional
service
Zone b Zone cZone a Zone b Zone cZone a
Regional service cell
Regional service cell
Regional service cell
Without Cells With Cells

16. Theoretical blast radius
Regional
service
Zone b Zone cZone a Zone b Zone cZone a
Regional service cell
Regional service cell
Regional service cell
Without Cells With Cells

17. Cells and Availability Zones – zonal services
Zone b Zone cZone a Zone b Zone cZone a
Zonal
service
Zonal
service
Zonal
service
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Without Cells With Cells

18. Availability zone failure
Zone b Zone cZone a Zone b Zone cZone a
Zonal
service
Zonal
service
Zonal
service
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Without Cells With Cells

19. Partial availability zone failure
Zone b Zone cZone a Zone b Zone cZone a
Zonal
service
Zonal
service
Zonal
service
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Without Cells With Cells

20. Theoretical blast radius
Zone b Zone cZone a Zone b Zone cZone a
Zonal
service
Zonal
service
Zonal
service
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Zonal
service cell
Without Cells With Cells

21. Cloud-native
as a foundation for innovation

24. SQL
TRANSACTIONS
CACHING
LOGGING
Relational databases: not designed for the cloud

25. Decompose the
system into
fundamental
building blocks

26. Amazon Aurora
Scaled-out
distributed
architecture
A P P L I C A T I O N A P P L I C A T I O N A P P L I C A T I O N
Shared Storage Volume
S T O R A G E N O D E S W I T H S S D s
SQL
TRANSACTIONS
CACHING
SQL
TRANSACTIONS
CACHING
SQL
TRANSACTIONS
CACHING

27. Fast
Online
DDL
GeoSpatial
indexing
Load
balancing
& auto scaling
Multi-region BacktrackBackup
and
restore
Fast
database
cloning
Instant crash
recovery
Serverless Global
databases
A m a z o n
A u r o r a
Cloud native database as a foundation for innovation

28. Aurora is the foundation for cloud native DB innovation
R e d u c e r e a d
l a t e n c y b y
a v o i d i n g q u o r u m
r e a d s
M a k e t h e s t o r a g e
s e r v i c e i n t e l l i g e n t
b y b e i n g D B r e c o r d
a w a r e
R e d u c e w r i t e
l a t e n c y
r e i n v e n t i n g w h a t
g e t s w r i t i n g
H i g h l y r e l i a b l e a n d
r e s i l i e n t t o
c o m p l e x f a i l u r e
s c e n a r i o s
V e r y f a s t t i m e t o
r e p a i r i n e x t r e m e
f a i l u r e c a s e s
D e c o u p l e i n t o a
h i g h l y s c a l a b l e a n d
r e l i a b l e s t o r a g e
s e r v i c e

30. TodayD y n a m o
w h i t e p a p e r
2 0 0 7 DynamoDB Launch
CloudFormation
Support
Batch GetItem,
Writeitem, update
table
Binary data types
GSI query
Fine grained access control
Cross-region copy in data pipeline
DDB local
Geospatial library
Low cost reads
LSI launch
JSON documents +
expanded free-tier
mobile console support
cross-region
import/export
Cloudformation GSI/LSI
Titan graph DB integration
1 minute CloudWatch metrics
ElasticSearch integration
Consistent scans
CRR library
CloudTrail integration
Streams, Lambda triggers
Focus on scalability,
availability, and
performance
improvements
Point-in-time recovery
Service level agreement
On-Demand
Transactions
Time to live (TTL)
VPC Endpoints
DynamoDB Accelerator (DAX)
Auto scaling
Global Tables
On-demand backups
Encryption at rest2 0 1 2 2 0 1 8
2 0 1 3
2 0 1 4 2 0 1 6
2 0 1 5 2 0 1 7

31. The four pillars of DynamoDB
Fully-managed
Performance at scale
Comprehensive
security
Built for modern
applications

32. DynamoDB
Advancements over the last 12 months
VPC
endpoints
April 2017
Auto
scaling
June 2017
DynamoDB
Accelerator (DAX)
April 2017
Time To
Live (TTL)
February 2017
Global tables
On-demand
backup
Encryption at rest
November 2017 November 2017 November 2017
Point-in-time
recovery
March 2018
SLA
June 2018
99.999% SLA
August 2018
Adaptive
capacity ACID
November 2018
Transactions
November 2018
On-demand

33. DynamoDB transactions
Simplify your code by executing multiple, all-or-nothing
actions within and across tables with a single API call.
Single
API
Call

34. DynamoDB on-demand
Start at Zero
No Limit
Features
• No capacity planning, provisioning, or
reservations– simply make API calls
• Pay only for the reads and writes you perform
Key Benefits
• Eliminates tradeoffs of over- or under-
provisioning
• Instantly accommodates your workload as traffic
ramps up or down

35. Item and Offers Service
https://www.amazon.co
m
Item
Offer
Relationships

36. Item Master Service (IMS)
Blob Stores 4
Index Tables 7
Databases 24
Partitioning Hash
Logical Partitions 256
Record Count ~600 Billion
Update Rate ~5 Billion/Day
24 ORACLE DATABASES
UPDAT
ES
PUBLI
SH
PARTITION MAP
Oracle DB
instance
Oracle DB
instance
Oracle DB
instance
Oracle DB
instance
Websit
e
Sellers

38. Amazon Redshift is
now 3.5x faster than
6 months ago
Normalized Queries Per Hour (QPH)
Assuming Amazon Redshift’s QPH 6 months ago=100%
JUL 2018 AUG 2018 SEP 2018 OCT 2018
181%
237%
284%
350%
100%
JUN 2018

39. 87% of Amazon Redshift
customers don’t have
significant wait times
Daily
cluster
queue time
per day
Remaining 13% have
bursts of activity averaging
10 minutes at a time

40. Consistently fast performance
even with thousands of concurrent queries
Amazon Redshift
concurrency scaling
A V A I L A B L E I N P R E V I E W T O D A Y
NEW!

42. Machine learning / training data
Surveillance video/closed circuit
data lakesAutonomous
vehicle data
IoTeventlogs
Logfiles High definition video
Mapping
data
Documents
Scanned
forms
Smar
t
Hom
e
data
DNA sequences
Oil & gas topography
Backup
s
Video
assets
Compliance records
Archives
Genomic
s data
Origin content for CDNs
Device sync
and backup
Customer
callrecords
Medical imagery
and records
Device
backups
Master
media
files
WORM/compliance data
Columnar-storage files
(Parquet, etc.)
Machine Learning training sets
Historical record
preservation data
Telemetry data
Pharmaceutical trial data
HPC application data
Transcode
d content
Seismic surveys
CCTV
data
Thumbnai
l Images
Analytics results

43. Amazon
S3

44. More than 235
distributed
microservices

45. Designed
for 11 9’s
TIME TO FAIL TIME TO REPAIR

46. The right tool (DB)
for the right job (workload)

47. AWS databases services
Purpose-built for all your app needs
NeptuneRDS
Aurora CommercialCommunity
Timestream QLDBElastiCache
Relational Key-value Document In-memory Graph Time series Ledger
DynamoDB
DocumentDB
NEW!
Redis Memcached
NEW!

48. Everyone wants to just focus on
business logic

50. Lambda Innovation

51. Serverless allows you to
build increasingly powerful
applications, faster

52. Systems of systems

53. IDEs Languages
AWS Cloud9
AWS Toolkit
for PyCharm
AWS Toolkit
for IntelliJ
AWS Toolkit
for VS Code
WebSocket support
for API Gateway
ALB support
for Lambda
Step Functions
service integrations
Managed Streaming
for Kafka
Custom Runtimes
Workflows
Programming
Models
AWS Lambda
Layers
AWS Nested Apps
using Serverless
Application Repository

54. Are you well architected?

55. | Benefits
SECURITY
2
O P E R AT I O N A
L
E X C E L L E N C E
1
R E L I A B I L I T Y
3
C O S T
O P T I M I Z AT I O
N
5
P E R F O R M A N C E
E F F I C I E N C Y
4

56. AWS Well-
Architected Tool
NEW!
Measure and improve your architecture using
AWS Well-Architected best practices
G E N E R A L L Y A V A I L A B L E T O D A Y
Implement workplans to
improve your architecture
Stay up to date as your
architecture evolves
Review workloads
against best practices

59. Security
Events
Videos
Resources
Best Practices
Improvement Plans

60. 95% of AWS features and services are
built based on direct customer feedback

61. GO BUILD