Amazon EC2 provides a broad selection of instance types to deliver high performance for a diverse mix of applications. In this session, we overview the drivers of system performance and discuss in depth how Amazon EC2 instances deliver system performance while also providing elasticity and complete control over your infrastructure. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Adam Boeglin, HPC Solutions Architect
July 13, 2016
Deep Dive on Delivering Amazon
EC2 Instance Performance

2.  Understanding the factors that go into choosing an EC2 instance
 Defining system performance and how it is characterized for
different workloads
 How Amazon EC2 instances deliver performance while providing
flexibility and agility
 How to make the most of your EC2 instance experience through the
lens of several instance types
What to Expect from the Session

3. InstancesAPI
Networking
EC2
EC2
Purchase options
Amazon Elastic Compute Cloud is Big

4. Host Server
Hypervisor
Guest 1 Guest 2 Guest n
Amazon EC2 Instances

5. In the Past
 First launched in August 2006
 M1 instance
 “One size fits all”
M1

6. 2006 2008 2010 2012 2014 2016
m1.small
m1.large
m1.xlarge
c1.medium
c1.xlarge
m2.xlarge
m2.4xlarge
m2.2xlarge
cc1.4xlarge
t1.micro
cg1.4xlarge
cc2.8xlarge
m1.medium
hi1.4xlarge
m3.xlarge
m3.2xlarge
hs1.8xlarge
cr1.8xlarge
c3.large
c3.xlarge
c3.2xlarge
c3.4xlarge
c3.8xlarge
g2.2xlarge
i2.xlarge
i2.2xlarge
i2.4xlarge
i2.4xlarge
m3.medium
m3.large
r3.large
r3.xlarge
r3.2xlarge
r3.4xlarge
r3.8xlarge
t2.micro
t2.small
t2.med
c4.large
c4.xlarge
c4.2xlarge
c4.4xlarge
c4.8xlarge
d2.xlarge
d2.2xlarge
d2.4xlarge
d2.8xlarge
g2.8xlarge
t2.large
m4.large
m4.xlarge
m4.2xlarge
m4.4xlarge
m4.10xlarge
Amazon EC2 Instances History
x1.32xlarge
t2.nano

7. Instance generation
c4.large
Instance family Instance size

8. Choices and Flexibility
 Choice of Processor
 Memory
 Storage Options
 Accelerated Graphics
 Burstable Performance

9.  Servers are hired to do jobs
 Performance is measured differently depending on the job
Hiring a Server
?

10. Performance Factors
Resource Performance factors Key indicators
CPU Sockets, number of cores, clock
frequency, bursting capability
CPU utilization, run queue length
Memory Memory capacity Free memory, anonymous paging,
thread swapping
Network
interface
Max. bandwidth, packet rate Receive throughput, transmit throughput
over max. bandwidth
Disks Input/output operations per second,
throughput
Wait queue length, device utilization,
device errors

11. Resource Utilization
 For given performance, how efficiently are
resources being used?
 Something at 100% utilization can’t
accept any more work
 Low utilization can indicate more resource
is being purchased than needed

12. Example: Web Application
 MediaWiki installed on Apache with 140 pages of content
 Load increased in intervals over time

13. Example: Web Application
 Memory stats

14. Example: Web Application
 Disk stats

15. Example: Web Application
 Network stats

16. Example: Web Application
 CPU stats

17. “Launching new instances and running tests
in parallel is easy…[when choosing an
instance] there is no substitute for measuring
the performance of your full application.”
- EC2 documentation

18. How Not to Choose an EC2 Instance
 Brute force testing
 Ignoring metrics
 Favoring old generation instances
 Guessing based on what you already have

19. EC2 Instance Families
General
purpose
Compute-
optimized
C3
Storage and IO-
optimized
I2 G2
GPU-
enabled
Memory-
optimized
R3C4
M4
D2
X1

20.  Give back instances as easily as you can acquire new ones
 Find an ideal instance type and workload combination
 EC2 Instance Pages provide “Use Case” Guidance
 With Amazon Elastic Block Store, storage and instance size don’t
need to be coupled
Instance Selection = Performance Tuning

21. Instance Sizing
c4.8xlarge 2 - c4.4xlarge
≈
4 - c4.2xlarge
≈
8 - c4.xlarge
≈

22. Choosing the Right Size
Understand your unit of work
 Web request
 Database/table
 Batch process
What is that unit’s requirements?
 CPU threads
 Memory constraints
 Disk and network
What are it’s availability requirements?

23. CPU Instructions and Protection Levels
 CPU has at least two protection levels.
 Privileged instructions can’t be executed in user mode to protect
system. Applications leverage system calls to the kernel.
Kernel
Application

24. VMM
Application
Kernel
PV
X86 CPU Virtualization: Prior to Intel VT-x
 Binary translation for privileged instructions
 Paravirtualization (PV)
 PV requires going through the VMM, adding latency
 Applications that are system call bound are most affected

25. Kernel
Application
VMM
PV-HVM
X86 CPU Virtualization: After Intel VT-x
 Hardware-assisted virtualization (HVM)
 PV-HVM uses PV drivers opportunistically for operations that
are slow emulated:
 E.g., network and block I/O

26. Tip: Use HVM AMIs with Amazon EBS

27. Time Keeping Explained
 Time keeping in an instance is deceptively hard
 gettimeofday(), clock_gettime(), QueryPerformanceCounter()
 The TSC
 CPU counter, accessible from userspace
 Requires calibration, vDSO
 Invariant on Sandy Bridge+ processors
 Xen pvclock; does not support vDSO
 On current generation instances, use TSC as clocksource

28. Tip: Use TSC as Clocksource

29. Review: C4 Instances
 Custom Intel E5-2666 v3 at 2.9 GHz
 P-state and C-state controls
Model vCPU Memory (GiB) EBS (Mbps)
c4.large 2 3.75 500
c4.xlarge 4 7.5 750
c4.2xlarge 8 15 1,000
c4.4xlarge 16 30 2,000
c4.8xlarge 36 60 4,000
Batch and HPC Workloads, Game Servers, Ad Serving, and High Traffic Web Servers

30. What’s New in C4: P-State and C-State Control
 Intel Turbo Boost up to 3.5 Ghz
 By entering deeper idle states, non-idle cores can achieve up to 300 MHz
higher clock frequencies
 But…deeper idle states require more time to exit, may not be appropriate
for latency-sensitive workloads

31. Tip: P-State Control for AVX2
 If an application makes heavy use of AVX2 on all cores, the processor
may attempt to draw more power than it should
 Processor will transparently reduce frequency
 Frequent changes of CPU frequency can slow an application

32. Review: T2 Instances
 Lowest-cost EC2 instance at $0.0065 per hour
 Burstable performance
 Fixed allocation enforced with CPU credits
Model vCPU Baseline CPU Credits
/Hour
Memory
(GiB)
Storage
t2.nano 1 5% 3 .5 EBS Only
t2.micro 1 10% 6 1 EBS Only
t2.small 1 20% 12 2 EBS Only
t2.medium 2 40%** 24 4 EBS Only
t2.large 2 60%** 36 8 EBS Only
General Purpose, Web Serving, Developer Environments, Small Databases

33. How Credits Work
 A CPU credit provides the performance of a
full CPU core for one minute
 An instance earns CPU credits at a steady rate
 An instance consumes credits when active
 Credits expire (leak) after 24 hours
Baseline rate
Credit
balance
Burst
rate

34. Tip: Monitor CPU Credit Balance

35. Tip: How to Interpret Steal Time
 Fixed CPU allocations of CPU can be offered through CPU caps
 Steal time happens when CPU cap is enforced
 Leverage Amazon CloudWatch metrics

36. Announced: X1 Instances
 Largest memory instance with 2 TB of DRAM
 Quad socket, Intel E7 processors with 128 vCPUs
Model vCPU Memory (GiB) Local
Storage
x1.32xlarge 128 1952 2x 1920 GB
In-Memory Databases, Big Data Processing, HPC Workloads

37. NUMA
 Non-uniform memory access
 Each processor in a multi-CPU system has local memory that is
accessible through a fast interconnect
 Each processor can also access memory from other CPUs, but local
memory access is a lot faster than remote memory
 Performance is related to the number of CPU sockets and how they
are connected - Intel QuickPath Interconnect (QPI)

38. QPI
122 GB 122 GB
16 vCPU’s 16 vCPU’s
r3.8xlarge

39. QPI
QPI
QPIQPI
QPI
488 GB
488 GB
488 GB
488 GB
32 vCPU’s 32 vCPU’s
32 vCPU’s 32 vCPU’s
x1.32xlarge

40. Tip: Kernel Support for NUMA Balancing
 An application will perform best when the threads of its processes are
accessing memory on the same NUMA node.
 NUMA balancing moves tasks closer to the memory they are accessing.
 This is all done automatically by the Linux kernel when automatic NUMA
balancing is active: version 3.8+ of the Linux kernel.
 Windows support for NUMA first appeared in the Enterprise and Data
Center SKUs of Windows Server 2003.

41. Review: I2 Instances
 16 vCPU: 3.2 TB SSD; 32 vCPU: 6.4 TB SSD
 365 K random read IOPS for 32 vCPU instance
Model vCPU Memory
(GiB)
Storage Read IOPS Write IOPS
i2.xlarge 4 30.5 1 x 800 SSD 35,000 35,000
i2.2xlarge 8 61 2 x 800 SSD 75,000 75,000
i2.4xlarge 16 122 4 x 800 SSD 175,000 155,000
i2.8xlarge 32 244 8 x 800 SSD 365,000 315,000
NoSQL Databases, Clustered Databases, Online Transaction Processing (OLTP)

42. Hardware
Split-Driver Model
Driver Domain Guest Domain Guest Domain
VMM
Front-end
driver
Front-
end
driver
Back-
end
driver
Device
Driver
Physical
CPU
Physical
Memory
Network
Device
Virtual CPU
Virtual
Memory
CPU
Scheduling
Sockets
Application
1
23
4
5

43. Granting in Pre-3.8.0 Kernels
 Requires “grant mapping” prior to 3.8.0
 Grant mappings are expensive operations due to TLB flushes
read(fd, buffer,…)
I/O domain Instance

44. Granting in 3.8.0+ Kernels, Persistent and Indirect
 Grant mappings are set up in a pool once
 Data is copied in and out of the grant pool
read(fd, buffer…)
Copy to
and from
grant pool

45. 2009–Longer Ago Than You Think
 Avatar was the top movie in the theaters
 Facebook overtook MySpace in active users
 President Obama was sworn into office
 The 2.6.32 Linux kernel was released

46. Tip: Use 3.8+ Kernel
 Amazon Linux 13.09 or later
 Ubuntu 14.04 or later
 RHEL/Centos 7 or later
 Etc.

47. Device Passthrough: Enhanced Networking
 SR-IOV eliminates need for driver domain
 Physical network device exposes virtual function to instance
 Requires a specialized driver, which means:
 Your instance OS needs to know about it
 EC2 needs to be told your instance can use it

48. Hardware
After Enhanced Networking
Driver Domain Guest Domain Guest Domain
VMM
NIC
Driver
Physical
CPU
Physical
Memory
SR-IOV Network
Device
Virtual CPU
Virtual
Memory
CPU
Scheduling
Sockets
Application
1
2
3
NIC
Driver

49. Elastic Network Adapter
 Next Generation of Enhanced Networking
 Hardware checksums
 Multi-Queue support
 Receive-side steering
 20 Gbps in a placement group
 New Open Source Amazon Network Driver

50. EBS Performance
 Instance size matters
 Match your volume size and
type to your instance
 Use EBS optimization if EBS
performance is important

51.  Choose HVM AMI’s
 Time keeping: use TSC
 C state and P state controls
 Monitor T2 CPU credits
 Use a modern Linux kernel
 NUMA balancing
 Persistent grants for I/O performance
 Enhanced networking
Summary: Getting the Most Out of EC2 Instances

53.  Bare metal performance goal, and in many scenarios already there
 History of eliminating hypervisor intermediation and driver domains
 Hardware-assisted virtualization
 Scheduling and granting efficiencies
 Device passthrough
Virtualization Themes

54. Next Steps
 Visit the Amazon EC2 documentation
 Launch an instance and try your app!

55. Remember to complete
your evaluations!

56. Thank you!