Amazon EC2 offers a broad array of instance types that provide customers with a varying set of resources for their applications. From the diminutive Micro instance to the powerful Cluster Compute Eight Extra Large instance, AKA "The Beast", customers are presented with a number of options for deploying their applications. This talk dives into the various Amazon EC2 instance families and walks through a variety of use cases that demonstrate the capabilities and ideal use cases for different instance types. You should leave with enough information to understand how to choose the instance type most appropriate to meet the requirements of your applications.

1. Revving Up Your Applications
Deepak Singh, Principal Product Manager - Amazon EC2
#reinvent

2. Via butteryflysha under a CC-BY
license

5. ec2-run-instances

6. instances

8. Unit of compute
Image: St. Stev

9. CPU

10. Disk

11. Memory

12. Network

13. Instance families

16. 1

18. Things change

27. Standard
High-CPU
High-Memory
Micro
Cluster Compute
Cluster GPU
High I/O
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28. Most
Standard
apps
Scale-out
compute
High-CPU Memory-intensive
apps
High-Memory
Compute + network throughput Micro Inexpensive
Cluster Compute
Cluster GPU
Parallel GPGPU computing
Lots of low-latency
IOPS
High I/O
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29. Standard instances

31. Sweet spot

32. Common applications

33. Databases

34. Caches

35. Data processing

36. The next generation

37. Need more CPU?

38. M3 Standard Instances

40. 50% more CPU/core
8-core option

41. Batch Processing
Encoding

42. Web servers
CMS

43. Lower cost
M1
Low entry point

44. Fast
M3
More cores

45. The Micro instance

46. Low cost instance

47. Free tier

48. Low, consistent, baseline
Burst of CPU capacity

49. So what can you run?

51. Request-based applications

52. Profiles to avoid

54. High CPU instances

55. Low $/core
Low $/ECU

57. Scale out

58. Tasks
Queue
Instances
Results
Store

60. Even more performance

61. Scale out

62. Tightly coupled

63. Network bound

64. Cluster Compute instances

65. Intel Xeon E5-2670

66. 2 processors
16 cores
32 threads
88 ECU

68. Placement
Group

70. Cores 17024
Rmax 240.09
Rpeak 354.12

71. November 2011

72. “The Beast”

73. 330 instances
76.9 TeraFlops
< $800/hr

74. ... or less on the Spot Market

75. < $90/hr*
*Spot Price of $0.27/hr on 11/17/2012

77. AVX

78. 2x Flops/cycle

79. Druid: 26 billion rows/second

80. ...new features

81. Intel Turbo

82. NUMA

83. Cluster GPU instances

85. 2*Intel Xeon 5570
22 GiB RAM
1.7 TB instance storage
2*NVidia Tesla M2050

86. CUDA

87. AMBER

89. High Memory instances

90. Higher memory/core

91. $/GB of RAM

93. Databases

94. Memcached

95. In-memory computing

96. ...what else could we do?

97. Cluster High Memory

98. 2 * Intel Xeon E5-2670
240 GiB RAM
2 * 120 GB SSD
10 Gigabit Ethernet
NUMA
Intel Turbo

99. In-memory databases

100. HPC

101. $3.50/hr (On Demand)
$0.90/hr (3-yr Heavy Utilization RI)

102. What about disk I/O?

103. Lots of IOPS

104. Low-latency IOPS

105. High I/O Instances

106. SSD-backed

107. Lots of CPU

108. Lots of networking

109. 120,000 4K random read IOPS
85,000 4K random write IOPS*
*Depends on active LBA SPAN

110. Replicated databases

111. NoSQL

113. Testing on EC2 hi1.4xlarge for mongoDB 2.2 rc0 via mongoperf
Settings:
nThreads:64,w:true,mmf:true,syncDelay:60,fileSizeMB:100000
All file systems ext4, mdadm raid0 on the hi1 ephemeral disks

114. EBS-optimized instances

115. Optimized for
EBS Provisioned IOPS

116. Dedicated network
throughput

117. 1000 Mbps
500 Mbps

118. Provision IOPS 20K IOPS
+ Manageability
EBS-optimized
Flexibility

119. > 20K IOPS
High I/O
instances Low latency
High bandwidth

120. ...one more thing

122. High Storage instances

123. 16 virtual cores
35 ECU
117 GiB memory
10 Gigabit ethernet
hs1.8xlarge

124. 24 HDD

125. 48 TB

126. 2.6 GB/s

127. Hadoop

128. Data Warehousing

129. Petabytes

130. $4.60/hr (On Demand)
$1.40/hr (3-yr Heavy Utilization RI)

133. 1

134. 17

135. In summary

136. Amazon EC2 instances

137. Unit of compute
Image: St. Stev

138. Most Apps
Low Cost
M1 Standard
M3 Standard Most Apps
Fast
High CPU
Scale-out
Compute
Memory-intensive
High Memory Apps
Compute + Network Througput
Micro Inexpensive
Cluster Compute Memory-intensive
Cluster Computing
Cluster High Memory
Lots of low-latency Cluster GPU Parallel GPGPU Computing
IOPS
High I/O Petabyte Scale
Lots of Throughput
High Storage

139. Choose wisely

141. Tell us your requirements
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142. We are sincerely eager to
hear your feedback on this
presentation and on re:Invent.
Please fill out an evaluation
form when you have a
chance.
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