Learn how to take advantage of Amazon RDS to run highly-available and performance-intensive production applications on AWS. We show you what you can do to achieve the highest levels of availability and performance for your relational databases. You learn how easy it is to architect for these requirements using several Amazon RDS features, such as Multi-AZ deployments, read replicas, and Provisioned IOPS storage. In addition, you learn how to quickly architect for the level of disaster recovery required by your business. Finally, some of our customers share how they built very high performing web and enterprise applications on Amazon RDS.

1. DAT301 - Running Highly-Available and
Performance-Intensive Production Applications on
Amazon RDS
Grant McAlister – AWS Database Services
Brennan Saeta – Coursera
November 14, 2013
© 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.

2. Why High Availability and Scalability
DB1a
DB1
DB1b
DB1c

3. High Availability and Disaster Recovery

4. Availability – Read and Write – Multi-AZ
cname update
DNS
Primary Update
AZ1
Physical
Synchronous
Replication
AZ2

5. Read Availability – Read Replicas
Sync
Replication
Async Replication

6. Logical Failover – Replicas of Replicas
Sync
Replication
Async Replication

7. Backup and Restore
Amazon S3
Log
1 Log
2
AZ1
Log
5
AZ2

8. Cross Region – Snapshot Copy
Amazon
S3
Amazon
S3
AZ1
AZ3
Region 1
Region 2

9. Cross Region – Read Replicas
AZ1
Region 1
AZ3
Region 2

10. Performance and Scale

11. Provisioned IOPS - Scale
db.m2.4xlarge - 130GB Data - Partial Random Read Workload
20,000
17,500
15,000
333GB - Regular
12,500
T
P 10,000
S
7,500
5,000
2,500
0
333GB - 1000 PIOPS
300GB - 3000 PIOPS

12. Provisioned IOPS - Latency
db.m2.4xlarge - 130GB Data - Partial Random Read Workload - Max Rate
9%
Percentage in Latency Bucket
8%
7.69% 7.89%
7%
6%
333GB - Regular
333GB - 1000 PIOPS
300GB - 3000 PIOPS
5%
4%
3.83%
3%
2%
1.38%
1%
0.42%
0.00%
0.01% 0.00% 0.00%
0%
3-20 ms
20-500ms
>500ms

13. Provisioned IOPS - Scale
db.m2.4xlarge - 130GB Data - Partial Random Read Workload
20,000
17,500
15,000
333GB - Regular
333GB - 1000 PIOPS
12,500
T
P 10,000
S
7,500
5,000
Target = 5000
2,500
0
300GB - 3000 PIOPS

14. Provisioned IOPS– Latency @ 5000 TPS
db.m2.4xlarge - 130GB Data - Partial Random Read Workload - 5000 TPS
9%
Percentage in Latency Bucket
8%
7.89%
7%
6%
5%
333GB - Regular
333GB - 1000 PIOPS
300GB - 3000 PIOPS
4%
3%
2%
1.17%
1%
0.35% 0.27%
0.00% 0.00%
0.04% 0.00% 0.00%
0%
3-20 ms
20-500ms
>500ms

15. Provisioned IOPS– 10,000 IOPS
db.m2.4xlarge - 130GB Data - Partial Random Read Workload
40,000
35,000
30,000
25,000
T
P 20,000
S
15,000
10,000
5,000
0
333GB - Regular
300GB - 3000 PIOPS
333GB - 1000 PIOPS
1000GB-10000 PIOPS

16. What Limit? – Amazon CloudWatch Metrics

17. Bottlenecks and Scaling
Throughput
•
•
•
•
EBS Optimized (0.5 -1Gbit)
db.m1.large,db.m1.xlarge,m2.2xlarge,m2.4xlarge
db.cr1.8xlarge – 10Gbit
Regular + non optimized – shared
DB Instance Class
IOPS
•
•
•
•
db.t1.micro – db.cr1.8xlarge
1-88 ECU
0.6 – 244 GB RAM
Memory to ECU Ratio
•
1.7 to 2.8 (exclude micro)
Regular or 1,000-30,000
Storage
•
Ratio 3:1 to 10:1
5GB - 100GB - 3TB
DB Engine
•
•
Block Size 8 – 16K
Ability to utilize resources

18. Read/Write Benchmark
130GB Data - Partial Random 90R/10W Workload 10K IOPS
80,000
70,000
cpu
95%
r/s
6800
w/s
2600
rMB/s 104
60,000
TPS
50,000
40,000
30,000
20,000
10,000
cpu
85%
r/s
3450
w/s
600
rMB/s
52
cpu
100%
r/s
6800
w/s
950
rMB/s 104
42,000
cpu
40%
r/s
0
w/s
3200
rMB/s
0
47,000
13,200
5,850
-
db.m1.large
db.m1.xlarge
db.m2.4xlarge
db.cr1.8xlarge

19. Bottlenecks and Scaling – Read Replicas

20. Read/Write Benchmark – Using RR
130GB Data - Partial Random 90R/10W Workload – 10K IOPS
120,000
100,000
TPS
80,000
126,000
60,000
40,000
42,000
20,000
5,850
47,000
db.m2.4xlarge
db.cr1.8xlarge
13,200
-
db.m1.large
db.m1.xlarge
cr1 + 3 x 4xlarge

21. Our Amazon RDS Journey
Tips, tricks, and war stories from our pervasive use of
Amazon RDS

22. re:Coursera

23. re:Brennan Saeta
Infrastructure Engineer
saeta@coursera.org
@bsaeta
http://betacs.pro

24. Coursera’s
Architecture Journey

25. Baby coursera.org
Webserver
Webserver
Webserver
Frontend
Webserver
Frontend
Frontend
nginx
ELB
nginx
nginx
nginx
php
class.coursera
php
class.coursera
php
class.coursera
php
class.coursera
memcache
memcache
memcache
memcache
Database

26. Simplified, modern
coursera.org
Legacy
Frontend
nginx
notifications
python www.
Cloud
Front
courservice
pdf
Cloud
Search
other
services
SES
SES
other
services
REST/HTTP
coursera
S3
S3
SQS
AWS IaaS
launcher
REST/HTTP
ELB
kangxi
subtitle
php
class.coursera
online services
maestro
maestrorr
memcache
Zoo
Keeper
class
class-nrr
Kafka
ELB
ELB
Edge
arrrrgh
api.coursera
DBs:
MySQL on RDS
Auth
accounts.coursera
Cascade
workbench
REST/HTTP
ELB
Eventing
eventing.coursera
arrrrgh
ELB
Wiki
share.coursera
ELB
other
ELB
services
near-line services

27. Every website [almost]

28. It’s always the database!

29. Scaling – Every app is different!

30. Why Amazon RDS? – The Beginning
• MySQL
– Familiar tool, quick to work with
• Amazon RDS
– Automatic backups, point-in-time restore
– Click to scale, click to read-replica
– Multi-AZ

31. Why Amazon RDS? – Now
• MySQL
 Single node reliability and proven persistence engine
• Amazon RDS
 Automatic backups, point-in-time restore
 Click to scale, click to read-replica
? Multi-AZ

32. Lessons Learned Along the Way
It was the worst of times
It was the best of times

33. If I could do one thing over…
Provisioned
IOPS

35. Hostile Networks

36. War Stories
• Opaque ORMs
• UTF-8
• Snapshots vs Perf
• Practice failover

37. Please give us your feedback on this
presentation
DAT301
As a thank you, we will select prize
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