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Optimizing Total Cost of Ownership
for AWS
Rohit Rahi, Amazon Web Services
Valentino Volonghi, AdRoll
Agenda
• Total Cost of Ownership
• AdRoll
• Cost Optimization on AWS
Lower costs with AWS
1
“Average of 400 servers
replaced per customer”
Replace up-front
capital expense with
low variable cost
2
42 Price
Reductions
Economies of scale
allow AWS to continually
lower costs
3
Pricing model choice
to support variable &
stable workloads
4
Save more money as
you grow bigger
Tiered Pricing
Volume Discounts
Custom Pricing
On-Demand
Reserved
Spot
Dedicated
Source: IDC Whitepaper, sponsored by
Amazon, “The Business Value of Amazon
Web Services Accelerates Over Time.”
December 2013
Lower costs than on-premises
On-Premises
Traditional
Data Center
On-Premises
Virtualized
Data Center
CAPEX
OPEX
OPEX
AWS
CAPEX
OPEX*
Cost savings from running
internal IT more efficiently AWS Scale
• Multiple new data centers built each year
• Volume purchasing, highly automated, supply
chain optimization
Utilization fundamentally higher in
AWS cloud
• Aggregating non-correlated workloads, scale,
spot market
Amazon specific hardware designs
• OEM acquisition of custom servers & net gear
• Direct purchasing of disk, memory, & CPU
• AWS controlled hypervisor & net protocol
layers
Diagram is not to scale
*For AWS, OPEX costs includes Reserved Instances one-time low, upfront payment, if Reserved Instances are used.
Cost savings from moving
to a public cloud provider
AWS Pricing Philosophy
More AWS
Usage
More
Infrastructure
Economies
of Scale
Lower
Infrastructure
Costs
Reduced
Prices
More
Customers Ecosystem
Global Footprint
New Features
New Services
Infrastructure
Innovation
We pass the savings along to our
customers in the form of low
prices and continuous reductions
42
Analysts have shown AWS reduces costs
In early 2012, AWS commissioned IDC to interview 11 organizations that deployed applications on AWS. Since this study was conducted in early
2012, AWS has introduced price reductions nearly 20 times across Amazon EC2 and Amazon S3. IDC estimated what the impact of AWS's fee
restructuring would be on the organizations that participated in the 2012 study and determined that the overall fees would drop by 21% lowering the
five year TCO from $909,000 to $846,000. Source: IDC Business Value of AWS Accelerates over time
IT
PRODUCTIVITY
INCREASE:
52%
5 YEAR TCO
SAVINGS:
72%
AWS TCO benefits increase over time…
$3.50 in benefits
$1 Investment in AWS $1 Investment in AWS
$8.40 in benefits
At 36 Months of using AWS… At 60 Months of using AWS…
~3X ~8X
Source: IDC Business Value of AWS Accelerates over time
According to IDC, this relationship between length of time using AWS and return is due to customers leveraging the more optimized
environment to generate more applications along a learning curve.
Comparing TCO is not easy
(But We’re Going to Try)
≠
Typical cost drivers for on-premises deployments,
including overhead costs
Network
Costs
Storage
Costs
Server
Costs
Hardware – Server, Rack
Chassis PDUs, ToR
Switches
(+Maintenance)
Software - OS,
Virtualization Licenses
(+Maintenance)
Overhead Cost
Space Power Cooling
Hardware – Storage
Disks, SAN/FC Switches
Overhead Cost
Storage Admin costs
Network Hardware – LAN
Switches, Load Balancer
Bandwidth costs
Network Admin costs
Overhead Cost
IT Labor
Costs
Server Admin
Virtualization Admin
1
2
3
4
Space Power Cooling
Space Power Cooling
illustrative
Diagram doesn’t include every cost item. E.g. software costs can include database, management, middle tier software costs.
Facilities cost can include costs associated with upgrades, maintenance, building security, taxes etc. IT labor costs can include
security admin and application admin costs.
AWS services pricing includes overhead costs
Hardware
Vendor
Offering
✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔
✔
Server
Network
Hardware
Software
OS +
VMs
DC/Co-lo
Floor
Space
Powering
Cooling
Software
Defined
Networking
Data Center
Personnel
Storage
Redundancy
Resource
Mgmt. /SW
Automation
× × × ××× ×
TCO Example : 100 VMs On-Premises vs. AWS
# of VMs Avg.
vCPU
Avg.
vRAM
Optimize by? Usage
25 1 2 RAM 5%
35 4 14 RAM 80%
30 8 32 RAM 60%
5 8 68 RAM 40%
5 16 128 Disk I/O 8%
# of
Instances
Instance vCPU RAM Instance Type
25 m1.small 1 1.7 On Demand
35 m3.xlarge 4 15 3 Yr. Heavy RI
30 m3.2xlarge 8 30 3 Yr. Med. RI
5 m2.4xlarge 8 68.4 3 Yr. Light RI
5 i2.4xlarge 16 122 3 Yr. Light RI
Avg.
vCPU
Avg.
vRAM
Optimize by?
1 2 CPU
4 14 CPU
8 32 CPU
8 68 CPU
16 128 Disk I/O
Instance vCPU RAM
m1.small 1 1.7
c3.xlarge 4 7
c3.2xlarge 8 15
c3.2xlarge 8 15
i2.4xlarge 16 122
1, 1.7, $0.060
1, 3.75, $0.113
2, 3.75, $0.145
2, 7.5, $0.225
2, 17.1, $0.410
4, 7, $0.300
4, 15, $0.450
4, 34.2, $0.820
8, 15, $0.600
8, 30, $0.900
8, 68.4, $1.640
4, 30.5, $0.853
8, 61, 1.705
16, 30, $1.200
32, 60, $2.400
32, 244, $3.500
16, 122, $3.410
16, 117, $4.600
32, 244, $6.820
0
50
100
150
200
250
300
0 5 10 15 20 25 30
TCO Example : Choosing EC2 instances
On Demand Prices shown (N.Virginia region), only latest generation instances (M3,C3) shown
where applicable, GPU and Micro instances not shown above
Memory-Optimized Instances
Compute-Optimized Instances
General Purpose Instances
Storage-Optimized Instances
vCPU
RAM
TCO Example : 100 VMs On-Premises vs. AWS
• From over 40 data centers down to 6
• Planning to migrate 3000 apps by Jan
2015
• Saving $100M over 3 Years
VS
1. Evaluate infrastructure
costs & architecture
2. Make business case 3. Enable decision to move to the
cloud
Customer Spotlight: Dow Jones Intl.
In Your TCO Analysis
Power/Cooling (compute, storage, shared network)
Data Center Administration (procurement, design, build, operate, network,
security personnel)
Rent/Real Estate (co-lo charges, building deprecation, taxes)
Software Licensing/Maintenance (OS, Virtualization, DCIM, Automation..)
RAW vs. USABLE storage capacity (Usable = ~50% Raw)
Storage Redundancy (RAID penalty, OS penalty)
Storage Backup costs (Tape, backup software)
Bandwidth, Network Gear & Redundancy (Routers, VPN, WAN..)
DON’T
FORGET
THINK
BENEFITS
Additional investment into new initiatives
Reduced Procurement Time, Resource sitting on shelf
Cost of lost customers
Lower down time, increased productivity
50B req/day without breaking the bank
Pixel “fires”
Pixel “fires”
Serve ad?
Pixel “fires”
Serve ad?
Ad served
Data must be available all over the world!
7/2011 - ~50GB/day
4/2013 - ~5TB/day
10/2013 - ~20TB/day
03/2014 - ~40TB/day
What do we do then?
• Store 1.5+ PB of compressed data in S3
• Be available worldwide, and replicate all our data in every major
area
• ~50B requests/day with 100ms latency caps
• As close as possible to 100% uptime
• 35 engineers
AdRoll S3 Usage by the numbers
• 1.5+ PB of compressed data stored
• 5-10TB of compressed new data each day
• ~5B monthly requests in February
• 500+ TB of transfer
• No engineers spend time on storage
AdRoll S3 buckets would be one of the most
visited properties on the web, we don’t even
think about it.
BackBlaze Storage Pod 4.0
• 180TB cost $9,305 to build, only 1 PSU per box.
• X 3 for local redundancy
• X 3 for geographic redundancy
• X 2 because we need to have room for growth
• +50% because we need to have quickly available spare parts in
each area
• TOTAL: $251,235 <- this is the real cost of 180TB
And it’s not even all of it…
• Now let’s develop the software that manages about 5B monthly
requests and transparently fails over…
• Let’s add bandwidth cost, electricity and data center costs…
• Our AWS total cost is equivalent to about 6 engineers.
We’re not a storage company!
We happen to have a similar amount of
data that a storage company has. But
we don’t have engineering dedicated
to storage.
Our RTB infrastructure
• ~500 c3.4xlarge in 4 regions
• Close to 100% uptime since launch
• <100ms max latency, 0.15% timeouts YTD at 50B requests/day
• 500K+ requests/second globally on DynamoDB
• Fully replace the global infrastructure in less than 1 hour
2 engineers
We have more people installing,
configuring and managing our office
network and windows laptops
Alternative?
• Setup 4 data centers locations
• 2 on-call staff in each location
• Provision ~1000 machines for growth and deployment flexibility.
• Implement Auto Scaling and a common API
• Provision 10-20% cold capacity in each location
• What if a big customer signs up for AdRoll?
• What if we improve our algorithms and we can do with half the
machines? What if we want to upgrade our hardware?
We’ve been trading money… For Time
Time is a far more scarce resource and
you can’t save it.
What does it mean in numbers?
• Minimum team size is about 20:
– 8 on-call
– 1 product manager for Auto Scaling and API
– 5 engineers to develop and maintain Auto Scaling
– 5 engineers to maintain Cassandra installation instead of DDB
– 1 engineering manager
• 20 people at an average $130K/year…
$2.6M/year
We spent less than that to run our entire
infrastructure in EC2 last year.
All of these very skilled engineers would
not be adding value to our product.
If we didn’t use EC2 a competitor
would…
And then we’d be in trouble
Cost Optimization on AWS
1. Choose the right instance types
Start
Choose an instance
that best meets your
basic requirements
Start with memory & then
choose closest virtual
cores
Look for peak IOPS
storage requirements
Tune
Change instance size up
or down based upon
monitoring
Use CloudWatch &
Trusted Advisor to assess
Roll-Out
Run multiple instances
in multiple Availability
Zones
2. Use Auto Scaling
Describes what Auto Scaling will
create when adding Instances
Only one active launch configuration
at a time
Launch
Configuration
as-create-launch-config
--image-id ami-54cf5c3d
--instance-type m1.small
--key mykey
--group webservers
--launch-config 101-launch-config
Auto Scaling managed grouping of EC2
instances
Automatically scale the number of
instances by policy – Min, Max, Desired
Auto Scaling
Group
as-create-auto-scaling-group 101-as-group
--availability-zones us-east-1a us-east-1b
--launch-configuration 101-launch-config
--load-balancers myELB
--max-size 5
--min-size 1
Parameters for performing an Auto
Scaling action
Scale Up/Down and by how much
Auto Scaling
Policy
as-put-scaling-policy 101ScaleUpPolicy
--auto-scaling-group 101-as-group
--adjustment=1
--type ChangeInCapacity
--cooldown 300
Utilization and Auto Scaling: Granularity
more small instances vs. less large instances
29 m1.large @ $0.240/hr.
= $6.96
59 m1.small @ $0.06/hr.
= $3.54
3. Turn off un-used instances
• Dev./test instances
• Simple instance start/stop
• Tear down/build up altogether
• Instances are disposable
0
2
4
6
8
10
12
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
On Demand
Light Utilization RI
Medium Utilization RI
Heavy utilization RI
/Spot Instances
4. Use Reserved Instances
Reserved Instances enable you to maximize savings by paying a low, one-time fee for a
capacity reservation of 1-3 years in exchange for a significant discount on the hourly rate.
Amazon EC2
up to 65% savings
Amazon RDS
up to 76% savings
Amazon DynamoDB
up to 76% savings
Amazon Redshift
up to 73% savings
Amazon ElastiCache
up to 70% savings
AWS services offering reservations
Customer Spotlight: Pinterest
AWS
Set-up
• 8 billion objects and 400 terabytes of data (May 2012), 10x growth from August 2011; EC2 instances
have grown by 3x in the same time period
• 150 EC2 instances ( web tier), 90 instances (in-memory caching), 70 master databases
• Reserved instances used for standard traffic; On-demand and spot instances used to handle daily elastic
load. Most services targeted to run at about 50% on-demand and 50% spot
Source: Pinterest AWS Case study, Pinterest Architecture update, 410TB of data, 10X Growth, 12 employees
Source: Return on Agility, Werner Vogels
“Imagine we were running our data center, and we had to go through a process of capacity
planning and ordering and racking hardware. It wouldn't have been possible to scale fast
enough,"– Ryan Park, Pinterest Operations Engineer
Costs have gone from $54 per hour to $20
per hour
Only 2 weeks of engineering effort was
required to achieve this cost savings
5. Use Spot Instances
• Pricing
• Up to 92% discount
• Elastic
• Capacity not otherwise
available
• Tradeoff
• Potential for interruption
Picking the right Bid Price - Tolerance for interruptions, % likelihood of
termination
1.21 PFLOPS
264 years of compute in < 18 hours
16,788 instances in 8 regions
Customer Spotlight: Cycle Computing
On-Premises Spot
$68 Million
$33K
6. Leverage Storage Classes
AWS Cloud
Amazon
Glacier
Gateway Appliance/
AWS Storage Gateway
Amazon
S3
Block File
On-premises Data Center
Archive Backup Disaster
Recovery
Amazon
EBS
Amazon S3 Reduced Redundancy
• 99.99% durability vs.
99.999999999%
• Up to 20% savings
• Great for everything that is easy to
reproduce
Amazon Glacier
• Same durability as S3
• 3 to 5 hours restore time
• Up to 89% savings
• Great for archiving, long-term
backups and old data
7. Offload your architecture
The more you can offload, the less infrastructure you need to maintain, scale, and pay for
• Offload popular traffic to Amazon CloudFront and S3
• Introduce Caching
ResponseTime
ServerLoad
ResponseTime
Server
Load
ResponseTime
Server
Load
No CDN CDN for
Static
Content
CDN for
Static &
Dynamic
Content
8. Use Application Services
Elastic
Load
Balancing
Amazon
Relational
Database
Service (RDS)
Amazon Simple
Queue Service
(SQS)
Amazon Simple
Email Service
(SES)
Amazon
Elastic
MapReduce
Amazon
ElastiCache
Amazon Simple
Notification
Service (SNS)
Web Servers
Availability Zone
$0.025 per Elastic Load Balancer-
hour (or partial hour)
$0.008 per GB of data processed
by an Elastic Load Balancer
100 GB Data processed, 1 ELB
$18 (.025*24*30) + $.008*100
$18.80
Web Servers
Availability Zone
EC2 instance
+ software LB
Elastic Load
Balancer
DNS
DNS
VS
Leverage Application Services
$0.060 per hour, m1.small
Separate for Software Load
Balancer
$.060*24*30 = $43.2 (m1.small)
+ Software LB Cost
On Demand Prices shown (N.Virginia region)
9. Use Consolidated Billing
• Receive a single bill for all charges incurred across all linked accounts
• Share RI discounts
• Combine tiering benefits
• View & manage linked accounts
• Add additional accounts
10. Leverage AWS tools
AWS Trusted Advisor
AWS EC2 Usage Reports
Recap
Choose the right Instance type
Use Auto Scaling
Turn off un-used Instances
Use Reserved Instances
Use Spot Instances
Leverage Storage Classes
Offload your architecture
Use Application Services
Use Consolidated Billing
Leverage AWS Tools – Trusted Advisor, EC2 Usage Reports
Others…
Summary
TCO
• Make reasonable assumptions and leverage industry benchmarks
• Know the on-premises hidden costs
Cost Optimization
• Create cost-aware architectures and leverage best practices
• Re-evaluate and revisit your architecture often
• Leverage Application Services, CloudWatch
• Stay up to date – RI modifications, Trusted Advisor
© 2014 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.
Optimizing Total Cost of Ownership
for AWS
Rohit Rahi, Amazon Web Services
Valentino Volonghi, AdRoll
Thank you!

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Optimizing Total Cost of Ownership for the AWS Cloud

  • 1. © 2014 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. Optimizing Total Cost of Ownership for AWS Rohit Rahi, Amazon Web Services Valentino Volonghi, AdRoll
  • 2. Agenda • Total Cost of Ownership • AdRoll • Cost Optimization on AWS
  • 3. Lower costs with AWS 1 “Average of 400 servers replaced per customer” Replace up-front capital expense with low variable cost 2 42 Price Reductions Economies of scale allow AWS to continually lower costs 3 Pricing model choice to support variable & stable workloads 4 Save more money as you grow bigger Tiered Pricing Volume Discounts Custom Pricing On-Demand Reserved Spot Dedicated Source: IDC Whitepaper, sponsored by Amazon, “The Business Value of Amazon Web Services Accelerates Over Time.” December 2013
  • 4. Lower costs than on-premises On-Premises Traditional Data Center On-Premises Virtualized Data Center CAPEX OPEX OPEX AWS CAPEX OPEX* Cost savings from running internal IT more efficiently AWS Scale • Multiple new data centers built each year • Volume purchasing, highly automated, supply chain optimization Utilization fundamentally higher in AWS cloud • Aggregating non-correlated workloads, scale, spot market Amazon specific hardware designs • OEM acquisition of custom servers & net gear • Direct purchasing of disk, memory, & CPU • AWS controlled hypervisor & net protocol layers Diagram is not to scale *For AWS, OPEX costs includes Reserved Instances one-time low, upfront payment, if Reserved Instances are used. Cost savings from moving to a public cloud provider
  • 5. AWS Pricing Philosophy More AWS Usage More Infrastructure Economies of Scale Lower Infrastructure Costs Reduced Prices More Customers Ecosystem Global Footprint New Features New Services Infrastructure Innovation We pass the savings along to our customers in the form of low prices and continuous reductions 42
  • 6. Analysts have shown AWS reduces costs In early 2012, AWS commissioned IDC to interview 11 organizations that deployed applications on AWS. Since this study was conducted in early 2012, AWS has introduced price reductions nearly 20 times across Amazon EC2 and Amazon S3. IDC estimated what the impact of AWS's fee restructuring would be on the organizations that participated in the 2012 study and determined that the overall fees would drop by 21% lowering the five year TCO from $909,000 to $846,000. Source: IDC Business Value of AWS Accelerates over time IT PRODUCTIVITY INCREASE: 52% 5 YEAR TCO SAVINGS: 72%
  • 7. AWS TCO benefits increase over time… $3.50 in benefits $1 Investment in AWS $1 Investment in AWS $8.40 in benefits At 36 Months of using AWS… At 60 Months of using AWS… ~3X ~8X Source: IDC Business Value of AWS Accelerates over time According to IDC, this relationship between length of time using AWS and return is due to customers leveraging the more optimized environment to generate more applications along a learning curve.
  • 8. Comparing TCO is not easy (But We’re Going to Try) ≠
  • 9. Typical cost drivers for on-premises deployments, including overhead costs Network Costs Storage Costs Server Costs Hardware – Server, Rack Chassis PDUs, ToR Switches (+Maintenance) Software - OS, Virtualization Licenses (+Maintenance) Overhead Cost Space Power Cooling Hardware – Storage Disks, SAN/FC Switches Overhead Cost Storage Admin costs Network Hardware – LAN Switches, Load Balancer Bandwidth costs Network Admin costs Overhead Cost IT Labor Costs Server Admin Virtualization Admin 1 2 3 4 Space Power Cooling Space Power Cooling illustrative Diagram doesn’t include every cost item. E.g. software costs can include database, management, middle tier software costs. Facilities cost can include costs associated with upgrades, maintenance, building security, taxes etc. IT labor costs can include security admin and application admin costs.
  • 10. AWS services pricing includes overhead costs Hardware Vendor Offering ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ Server Network Hardware Software OS + VMs DC/Co-lo Floor Space Powering Cooling Software Defined Networking Data Center Personnel Storage Redundancy Resource Mgmt. /SW Automation × × × ××× ×
  • 11. TCO Example : 100 VMs On-Premises vs. AWS # of VMs Avg. vCPU Avg. vRAM Optimize by? Usage 25 1 2 RAM 5% 35 4 14 RAM 80% 30 8 32 RAM 60% 5 8 68 RAM 40% 5 16 128 Disk I/O 8% # of Instances Instance vCPU RAM Instance Type 25 m1.small 1 1.7 On Demand 35 m3.xlarge 4 15 3 Yr. Heavy RI 30 m3.2xlarge 8 30 3 Yr. Med. RI 5 m2.4xlarge 8 68.4 3 Yr. Light RI 5 i2.4xlarge 16 122 3 Yr. Light RI Avg. vCPU Avg. vRAM Optimize by? 1 2 CPU 4 14 CPU 8 32 CPU 8 68 CPU 16 128 Disk I/O Instance vCPU RAM m1.small 1 1.7 c3.xlarge 4 7 c3.2xlarge 8 15 c3.2xlarge 8 15 i2.4xlarge 16 122
  • 12. 1, 1.7, $0.060 1, 3.75, $0.113 2, 3.75, $0.145 2, 7.5, $0.225 2, 17.1, $0.410 4, 7, $0.300 4, 15, $0.450 4, 34.2, $0.820 8, 15, $0.600 8, 30, $0.900 8, 68.4, $1.640 4, 30.5, $0.853 8, 61, 1.705 16, 30, $1.200 32, 60, $2.400 32, 244, $3.500 16, 122, $3.410 16, 117, $4.600 32, 244, $6.820 0 50 100 150 200 250 300 0 5 10 15 20 25 30 TCO Example : Choosing EC2 instances On Demand Prices shown (N.Virginia region), only latest generation instances (M3,C3) shown where applicable, GPU and Micro instances not shown above Memory-Optimized Instances Compute-Optimized Instances General Purpose Instances Storage-Optimized Instances vCPU RAM
  • 13. TCO Example : 100 VMs On-Premises vs. AWS
  • 14. • From over 40 data centers down to 6 • Planning to migrate 3000 apps by Jan 2015 • Saving $100M over 3 Years VS 1. Evaluate infrastructure costs & architecture 2. Make business case 3. Enable decision to move to the cloud Customer Spotlight: Dow Jones Intl.
  • 15. In Your TCO Analysis Power/Cooling (compute, storage, shared network) Data Center Administration (procurement, design, build, operate, network, security personnel) Rent/Real Estate (co-lo charges, building deprecation, taxes) Software Licensing/Maintenance (OS, Virtualization, DCIM, Automation..) RAW vs. USABLE storage capacity (Usable = ~50% Raw) Storage Redundancy (RAID penalty, OS penalty) Storage Backup costs (Tape, backup software) Bandwidth, Network Gear & Redundancy (Routers, VPN, WAN..) DON’T FORGET THINK BENEFITS Additional investment into new initiatives Reduced Procurement Time, Resource sitting on shelf Cost of lost customers Lower down time, increased productivity
  • 16. 50B req/day without breaking the bank
  • 20. Data must be available all over the world!
  • 21. 7/2011 - ~50GB/day 4/2013 - ~5TB/day 10/2013 - ~20TB/day 03/2014 - ~40TB/day
  • 22. What do we do then? • Store 1.5+ PB of compressed data in S3 • Be available worldwide, and replicate all our data in every major area • ~50B requests/day with 100ms latency caps • As close as possible to 100% uptime • 35 engineers
  • 23. AdRoll S3 Usage by the numbers • 1.5+ PB of compressed data stored • 5-10TB of compressed new data each day • ~5B monthly requests in February • 500+ TB of transfer • No engineers spend time on storage
  • 24. AdRoll S3 buckets would be one of the most visited properties on the web, we don’t even think about it.
  • 25. BackBlaze Storage Pod 4.0 • 180TB cost $9,305 to build, only 1 PSU per box. • X 3 for local redundancy • X 3 for geographic redundancy • X 2 because we need to have room for growth • +50% because we need to have quickly available spare parts in each area • TOTAL: $251,235 <- this is the real cost of 180TB
  • 26. And it’s not even all of it… • Now let’s develop the software that manages about 5B monthly requests and transparently fails over… • Let’s add bandwidth cost, electricity and data center costs… • Our AWS total cost is equivalent to about 6 engineers.
  • 27. We’re not a storage company!
  • 28. We happen to have a similar amount of data that a storage company has. But we don’t have engineering dedicated to storage.
  • 29. Our RTB infrastructure • ~500 c3.4xlarge in 4 regions • Close to 100% uptime since launch • <100ms max latency, 0.15% timeouts YTD at 50B requests/day • 500K+ requests/second globally on DynamoDB • Fully replace the global infrastructure in less than 1 hour
  • 31. We have more people installing, configuring and managing our office network and windows laptops
  • 32. Alternative? • Setup 4 data centers locations • 2 on-call staff in each location • Provision ~1000 machines for growth and deployment flexibility. • Implement Auto Scaling and a common API • Provision 10-20% cold capacity in each location • What if a big customer signs up for AdRoll? • What if we improve our algorithms and we can do with half the machines? What if we want to upgrade our hardware?
  • 33. We’ve been trading money… For Time
  • 34. Time is a far more scarce resource and you can’t save it.
  • 35. What does it mean in numbers? • Minimum team size is about 20: – 8 on-call – 1 product manager for Auto Scaling and API – 5 engineers to develop and maintain Auto Scaling – 5 engineers to maintain Cassandra installation instead of DDB – 1 engineering manager • 20 people at an average $130K/year… $2.6M/year
  • 36. We spent less than that to run our entire infrastructure in EC2 last year. All of these very skilled engineers would not be adding value to our product.
  • 37.
  • 38. If we didn’t use EC2 a competitor would… And then we’d be in trouble
  • 40. 1. Choose the right instance types Start Choose an instance that best meets your basic requirements Start with memory & then choose closest virtual cores Look for peak IOPS storage requirements Tune Change instance size up or down based upon monitoring Use CloudWatch & Trusted Advisor to assess Roll-Out Run multiple instances in multiple Availability Zones
  • 41. 2. Use Auto Scaling Describes what Auto Scaling will create when adding Instances Only one active launch configuration at a time Launch Configuration as-create-launch-config --image-id ami-54cf5c3d --instance-type m1.small --key mykey --group webservers --launch-config 101-launch-config Auto Scaling managed grouping of EC2 instances Automatically scale the number of instances by policy – Min, Max, Desired Auto Scaling Group as-create-auto-scaling-group 101-as-group --availability-zones us-east-1a us-east-1b --launch-configuration 101-launch-config --load-balancers myELB --max-size 5 --min-size 1 Parameters for performing an Auto Scaling action Scale Up/Down and by how much Auto Scaling Policy as-put-scaling-policy 101ScaleUpPolicy --auto-scaling-group 101-as-group --adjustment=1 --type ChangeInCapacity --cooldown 300
  • 42. Utilization and Auto Scaling: Granularity more small instances vs. less large instances 29 m1.large @ $0.240/hr. = $6.96 59 m1.small @ $0.06/hr. = $3.54
  • 43. 3. Turn off un-used instances • Dev./test instances • Simple instance start/stop • Tear down/build up altogether • Instances are disposable
  • 44. 0 2 4 6 8 10 12 14 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 On Demand Light Utilization RI Medium Utilization RI Heavy utilization RI /Spot Instances 4. Use Reserved Instances Reserved Instances enable you to maximize savings by paying a low, one-time fee for a capacity reservation of 1-3 years in exchange for a significant discount on the hourly rate. Amazon EC2 up to 65% savings Amazon RDS up to 76% savings Amazon DynamoDB up to 76% savings Amazon Redshift up to 73% savings Amazon ElastiCache up to 70% savings AWS services offering reservations
  • 45. Customer Spotlight: Pinterest AWS Set-up • 8 billion objects and 400 terabytes of data (May 2012), 10x growth from August 2011; EC2 instances have grown by 3x in the same time period • 150 EC2 instances ( web tier), 90 instances (in-memory caching), 70 master databases • Reserved instances used for standard traffic; On-demand and spot instances used to handle daily elastic load. Most services targeted to run at about 50% on-demand and 50% spot Source: Pinterest AWS Case study, Pinterest Architecture update, 410TB of data, 10X Growth, 12 employees Source: Return on Agility, Werner Vogels “Imagine we were running our data center, and we had to go through a process of capacity planning and ordering and racking hardware. It wouldn't have been possible to scale fast enough,"– Ryan Park, Pinterest Operations Engineer Costs have gone from $54 per hour to $20 per hour Only 2 weeks of engineering effort was required to achieve this cost savings
  • 46. 5. Use Spot Instances • Pricing • Up to 92% discount • Elastic • Capacity not otherwise available • Tradeoff • Potential for interruption Picking the right Bid Price - Tolerance for interruptions, % likelihood of termination
  • 47. 1.21 PFLOPS 264 years of compute in < 18 hours 16,788 instances in 8 regions Customer Spotlight: Cycle Computing On-Premises Spot $68 Million $33K
  • 48. 6. Leverage Storage Classes AWS Cloud Amazon Glacier Gateway Appliance/ AWS Storage Gateway Amazon S3 Block File On-premises Data Center Archive Backup Disaster Recovery Amazon EBS Amazon S3 Reduced Redundancy • 99.99% durability vs. 99.999999999% • Up to 20% savings • Great for everything that is easy to reproduce Amazon Glacier • Same durability as S3 • 3 to 5 hours restore time • Up to 89% savings • Great for archiving, long-term backups and old data
  • 49. 7. Offload your architecture The more you can offload, the less infrastructure you need to maintain, scale, and pay for • Offload popular traffic to Amazon CloudFront and S3 • Introduce Caching ResponseTime ServerLoad ResponseTime Server Load ResponseTime Server Load No CDN CDN for Static Content CDN for Static & Dynamic Content
  • 50. 8. Use Application Services Elastic Load Balancing Amazon Relational Database Service (RDS) Amazon Simple Queue Service (SQS) Amazon Simple Email Service (SES) Amazon Elastic MapReduce Amazon ElastiCache Amazon Simple Notification Service (SNS)
  • 51. Web Servers Availability Zone $0.025 per Elastic Load Balancer- hour (or partial hour) $0.008 per GB of data processed by an Elastic Load Balancer 100 GB Data processed, 1 ELB $18 (.025*24*30) + $.008*100 $18.80 Web Servers Availability Zone EC2 instance + software LB Elastic Load Balancer DNS DNS VS Leverage Application Services $0.060 per hour, m1.small Separate for Software Load Balancer $.060*24*30 = $43.2 (m1.small) + Software LB Cost On Demand Prices shown (N.Virginia region)
  • 52. 9. Use Consolidated Billing • Receive a single bill for all charges incurred across all linked accounts • Share RI discounts • Combine tiering benefits • View & manage linked accounts • Add additional accounts
  • 53. 10. Leverage AWS tools AWS Trusted Advisor AWS EC2 Usage Reports
  • 54. Recap Choose the right Instance type Use Auto Scaling Turn off un-used Instances Use Reserved Instances Use Spot Instances Leverage Storage Classes Offload your architecture Use Application Services Use Consolidated Billing Leverage AWS Tools – Trusted Advisor, EC2 Usage Reports Others…
  • 55. Summary TCO • Make reasonable assumptions and leverage industry benchmarks • Know the on-premises hidden costs Cost Optimization • Create cost-aware architectures and leverage best practices • Re-evaluate and revisit your architecture often • Leverage Application Services, CloudWatch • Stay up to date – RI modifications, Trusted Advisor
  • 56. © 2014 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. Optimizing Total Cost of Ownership for AWS Rohit Rahi, Amazon Web Services Valentino Volonghi, AdRoll Thank you!