14. r
Deliver a great experience to
your customers.
Responsive, fast web applications.
15. SCALE
g DECOUPLED OUT OPTIMIZE FOR COST S
5 patterns for
performance
v
CALIBRATED FOR:
CPU performance
v
CALIBRATED FOR:
IO performan
ce
C
AUTOMATE
60. r
Deploying and scaling a datastore
Follow the same patterns:
horizontal scale, availability, automation.
61. r
One question:
Does your application require a
strict, controlled schema for query flexibility?
62. Does your application require a strict, controlled schema
r for query flexibility? Yes
Amazon Relational Database Service
Management systems: CRM, ERP, finance
63. r
Focus on your app
Handles tedious database admin tasks
Designed for availability
64. r
Multi-engine
MySQL, Oracle, Microsoft SQL Server
Up and running in six clicks
65. r
Point in time snapshots
Automatic. Easy recovery.
66. r
High availability
Deployed across multiple availability zones.
Synchronous writes.
71. Does your application require a strict, controlled schema
r for query flexibility? No
Amazon DynamoDB
Web apps, social apps, mobile apps,
user generated content,
unstructured data integration, lots of data.
72. r
Focus on your app
Managed NoSQL database service.
No schema.
73. r
Unlimited scale
Unlimited storage
Pay as you go
74. r
High performance
Single digit millisecond latencies
75. r
Zero admin
No instances to manage
Tiny API, perfectly formed
80. r
CloudFront for dynamic content
Edge caching for dynamic content
Cache by query string parameters
Multiple origin servers
Persistent connections to origin servers
132. SCALE
g DECOUPLED OUT
5 patterns for
performance
133. SCALE
g DECOUPLED OUT OPTIMIZE FOR COST S
5 patterns for
performance
134. SCALE
g DECOUPLED OUT OPTIMIZE FOR COST S
5 patterns for
performance
CALIBRATED FOR:
v CPU performance
CALIBRATED FOR:
v IO performan
ce
135. SCALE
g DECOUPLED OUT OPTIMIZE FOR COST S
5 patterns for
performance
v
CALIBRATED FOR:
CPU performance
v
CALIBRATED FOR:
IO performan
ce
C
AUTOMATE