This session is a deep dive into techniques used by successful customers who optimized their use of AWS. Learn tricks and hear tips you can implement right away to reduce waste, choose the most efficient instance, and fine-tune your spending; often with improved performance and a better end-customer experience. We showcase innovative approaches and demonstrate easily applicable methods to save you time and money with Amazon EC2, Amazon S3, and a host of other services.

1. Chicago
©2015, Amazon Web Services, Inc. or its affiliates. All rights reserved
Enterprise Pre-Day

2. Do you
• Wear green eye-shades?
• Work from the console?

3. You’re using AWS.
You like it.

4. But maybe you are spending
more than you planned

5. Or you’d just like to spend less

6. What should you do?

7. How about
some
frameworks

8. Some
tools

9. Some best practices

10. And some examples
from other customers
like you

11. How are you
controlling the
provisioning of
resources?

12. Control who can
provision resources

13. Require
tagging

14. “No tags? No instance”
– Large financial services
customer in Boston

15. Best practices:
• Control who can provision
resources via IAM
• Require tagging
– Inspect
– Stop instances without tags

16. Savings potential
100% if you don’t start
instances you don’t need!

17. Are you identifying
and terminating idle
resources?

18. How do I identify idle resources?

19. AWS Trusted Advisor
runs 100+ configuration
checks and recommends
savings

20. Trusted Advisor Demo

21. We are using AWS Trusted Advisor to
improve cost efficiency and to audit
the configurations of service
platforms

22. Trusted Advisor

23. How do I handle demand spikes?

24. Design for
elasticity rather
than deploy for
peak

25. Use Auto Scaling or
queue-based approaches
to add resources when
needed, and turn them
off when not
Amazon SQS
Queue
Auto Scaling

26. Problem: Workloads
arrive asynchronously
and require isolation
Solution: Amazon
Simple Queue Service
and launch/
termination of
instances
Amazon SQS

27. Problem: How to scale up to
accommodate sudden traffic
spikes?
Solution: Auto ScalingAuto Scaling

28. Auto Scaling real world example
• Baseline traffic: 300+ thousand pages / hour
130 TB/month outbound traffic
• Peak: 2.0+ million pages / hour (~7x baseline)
• Architectural changes: e.g., move from local
SSDs to provisioned IOPS needed due to this
scale
• Auto Scaling provides 23% savings over three
years

29. Best practices
• Identify idle resources using Trusted
Advisor
• Turn them off
• Design to scale up and scale down using
Auto Scaling or a queue-based approach
• Match your usage and capacity—don’t pay
for idle resources!

30. Are you using the
most cost-effective
instances or
resources?

31. Match
resources to
workload

32. How can I tell if there’s a
match or mismatch?

33. Use Amazon
CloudWatch to
collect and track
metrics
CloudWatch

34. Amazon CloudWatch monitoring
Basic
• 7 metrics for Amazon EC2
including:
– CPU utilization
– Data transfer
– Disk usage and more
• 5-minute frequency
• Metrics for Amazon EBS,
Amazon DynamoDB, Amazon
RDS, etc.
Detailed
• 1-minute frequency
• Aggregation by instance type and
AMI

35. Why does this matter?

36. Different instances cost
different amounts

37. Instance families: Example
Instance vCPU Mem
(GiB)
Monthly price
(3-yr AURI )
Ideal use case
c4.2xlarge 8 15 $125.44 Best price-compute performance
m4.2xlarge 8 32 $137.25 Balanced
r3.2xlarge 8 61 $179.25 Lowest cost per GiB RAM
r3.xlarge 4 30.5 $89.61 Lowest cost per GiB RAM

38. Do you need
continuous compute
or does bursting work
for you?

39. t2.medium
• 4 GiB RAM
• Baseline performance: 40%
• Bursts beyond this based on CPU
credits
• Less than $17 per month
• Details: http://amzn.to/1sl2bKa
• Web servers, dev, small databases
t2

40. m3.medium

41. t2.medium (bursting)

42. Cloudwatch: CPU Utilization

43. t2 vs m3.medium or c4.large
Instance vCPU Mem
(GiB)
Monthly price
(3-yr AURI )
Ideal use case
m3.medium 1 3.75 $19.08 Always available, balanced
c4.large 2 3.75 $31.36 Always available, compute
t2.medium 2 4 $16.86 Bursty workloads

44. Consider switching to a t2?

45. Guidance
• Inspect your workloads (use CloudWatch!)
• Can your workload run on a t2?
• If not, is it memory intensive? àr3
• Is it compute intensive? à c4
• Others to consider:
– i2 for storage-optimized
– g2 for GPU

48. Savings potential
If t2 works for you
• 11%: Switch from m3.medium to t2.medium
• 46%: Switch from c3.large to t2.medium
Instance optimization
• 9%: Switch to c4 for compute-intensive apps
(m4.2xl -> c4.2xl)
• 35%: Switch to r3 for memory-intensive apps
(m4.2xl -> r3.xlarge)

49. Best practices:
1. Monitor instances with CloudWatch
2. Switch to t2 as possible
3. Use compute- and memory-focused
instances as needed

50. Do you need long-
term storage?

51. Amazon Glacier
Extremely low-cost cloud
storage service
Amazon Glacier

52. Are you purchasing
in the most cost-
effective way?

53. Commitment
and spot save $

54. Use Reserved
Instances if possible:
Up to 60% savings +
capacity reservation

55. AWS Trusted Advisor
identifies savings
attainable via
Reserved Instancess

56. Reserved Instance Marketplace

57. Use Spot Instances for
non-stateful workloads
Pricing starts
at 90% off

58. Novartis, Cycle Computing &
AWS Spot Instances

59. Goal:
Screen 10 million compounds
against a common cancer target
in < 1 week

60. 10,600 AWS instances

61. 39 drug design years in 11 hours

62. 3 promising compounds
identified

63. Cost of $4,232

64. Savings potential
• ~40%: 1-Year Reserved
Instances
• ~60%: 3-Year Reserved
Instances
• Up to 90%: Spot Instances

65. Could you save by
letting AWS do more
work for you?

66. Focus on what
you do best

67. Let AWS solve other
problems for you

68. AWS’s higher-
level services
automate your
work and save
you money
CloudFront
DynamoDB
Amazon RDS
ElastiCache
Amazon Redshift
Amazon EMR
Amazon
Kinesis
Amazon
WorkSpaces

69. Are you modeling
and monitoring your
spend?

70. https://
calculator.s3.amazonaws.com/
index.html

71. Detailed billing
reports and
cost insights

72. Detailed Billing Reports
http://amzn.to/1swNwLV

73. Cost Explorer
http://amzn.to/1zHE2Fj

74. Cost Explorer Demo

75. Forecasting Demo

76. Budgeting Demo

77. Demo
CloudWatch

81. • Control and verify
• Design for elasticity
• Match resources and
workload
• Purchase for savings
• Use application
services
• Model and track
Frameworks to remember

82. Tools to use
• IAM, AWS console
• Auto Scaling,
Amazon SQS
• Amazon CloudWatch
• AWS Trusted Advisor
• Detailed billing reports
and Cost Explorer
• Partners

83. • Turn off untagged resources
• Stop idle instances
• Use instances matched to task
and less expensive ones
• Baseload with RIs
• Use Spot Instances for non-
stateful workloads
• Model and track spending
Best practices

84. Chicago
©2015, Amazon Web Services, Inc. or its affiliates. All rights reserved
Enterprise Pre-Day