This document discusses strategies for optimizing cloud costs using cloud native architectures. It provides examples of how Netflix optimized costs by rapidly experimenting in the cloud without capacity planning. It then outlines several approaches to reduce cloud costs including turning off idle resources, rightsizing instances, using auto-scaling, mixing reserved and on-demand instances, consolidating accounts, and expecting price reductions over time. Combining these approaches could potentially reduce costs by over 90% compared to traditional architectures over three years.

1. Cloud Native Cost Optimization
Adrian Cockcroft @adrianco
Technology Fellow - Battery Ventures
November 2014

2. @adrianco
What does
everyone want?

3. @adrianco
Less Time
Less Cost

4. @adrianco
Faster!
See talks by @adrianco
Speed and Scale - QCon New York
Fast Delivery - GOTO Copenhagen

5. @adrianco
Cheaper!
This brand new talk:
How to use Cloud Native architecture to
reduce cost without slowing down

6. @adrianco
How is Cost
Measured?

7. 1
Bottom Up
2
Product
3
Top Down

8. @adrianco
Bottom Up Costs
Add up the cost to
buy and operate
every component
1

9. @adrianco
Product Cost
Cost of delivering
and maintaining
each product
2

10. @adrianco
Top Down Costs
Divide total budget
by the number of
components
3

11. @adrianco
Top Down vs. Bottom Up
Will never match!
!
Hidden Subsidies vs.
Hidden Costs1
3

12. @adrianco
Agile Team Product Profit
Value minus costs
Time to value
ROI, NPV, MMF
Profit center
2
$

13. @adrianco
What about cloud
costs?

14. @adrianco
Cloud Native Cost Optimization
Optimize for speed first
Turn it off!
Capacity on demand
Consolidate and Reserve
Plan for price cuts
FOSS tooling
$$ $

15. @adrianco
Do The Impossible Immediately
Ne#lix'Examples'
• European'Launch'using'AWS'Ireland'
– No'employees'in'Ireland,'no'provisioning'delay,'everything'
worked'
– No'need'to'do'detailed'capacity'planning'
– OverAprovisioned'on'day'1,'shrunk'to'fit'aDer'a'few'days'
– Capacity'grows'as'needed'for'addiGonal'country'launches'
• Brazilian'Proxy'Experiment'
– No'employees'in'Brazil,'no'“meeGngs'with'IT”'
– Deployed'instances'into'two'zones'in'AWS'Brazil'
– Experimented'with'network'proxy'opGmizaGon'
– Decided'that'gain'wasn’t'enough,'shut'everything'down'

16. @adrianco
The Capacity
Planning Problem

17. @adrianco
Best Case Waste
Product(Launch(Agility(2(Rightsized(
Pre2Launch(
Build2out(
Tes9ng(
Launch(
Grow
th(
Grow
th( Demand(
Cloud(
Datacenter(
$(
Cloud capacity
used is maybe
half average
DC capacity

18. @adrianco
Failure to Launch
Product(Launch(-(Under-es1mated(
Pre-Launch
Build-out
Testing
Launch
G
row
th
G
row
th
Mad scramble
to add more DC
capacity during
launch phase
outages

19. @adrianco
Over the Top Losses
Product(Launch(Agility(–(Over6es8mated(
Pre-Launch
Build-out
Testing
Launch
G
row
th
G
row
th
$
Capacity wasted
on failed launch
magnifies the
losses

20. @adrianco
Turning off Capacity
Off-peak production
Test environments
Dev out of hours
Dormant Data ScienceWhen%you%turn%off%your%cloud%resources,%
you%actually%stop%paying%for%them%

21. @adrianco
Turn off Test Environments
Snapshot or freeze
Fast restart needed
Persistent storage
40 of 168 hrs/wk

22. @adrianco
Seasonal Savings
1 5 9 13 17 21 25 29 33 37 41 45 49
WebServers
Week
Optimize during a year
50% Savings
Weekly&CPU&Load&

23. @adrianco
Autoscale the Costs Away
50%+%Cost%Saving%
Scale%up/down%
by%70%+%
Move%to%Load=Based%Scaling%

24. @adrianco
Daily Duty Cycle
Business'Throughput'Instances'
Reactive Autoscaling
saves around 50%
Predictive Autoscaling saves around 70%
See Scryer on Netflix Tech Blog

25. @adrianco
Underutilized and Unused
AWS$Support$–$Trusted$Advisor$–$
Your$personal$cloud$assistant$

26. @adrianco
Clean Up the Crud
Other&simple&op-miza-on&-ps&
• Don’t&forget&to…&
– Disassociate&unused&EIPs&
– Delete&unassociated&Amazon&
EBS&volumes&
– Delete&older&Amazon&EBS&
snapshots&
– Leverage&Amazon&S3&Object&
Expira-on&
& Janitor&Monkey&cleans&up&unused&resources&

27. @adrianco
Total Cost of Oranges
When%Comparing%TCO…!
Make!sure!that!
you!are!including!
all!the!cost!factors!
into!considera4on!
Place%
Power%
Pipes%
People%
Pa6erns%
How much does Openstack
or ESX datacenter automation
software and support
cost per instance?

28. @adrianco
When Do You Pay?
@adrianco
bill
Now
Next
Month
Ages
Ago
Lease
Building
Install
AC etc
Rack &
Stack
Private
Cloud SW
Run
My Stuff
Datacenter Up Front Costs

29. @adrianco
Reservation Reductions
On Demand Light Use Medium Use Heavy Use
$ No Upfront $172 upfront $286 upfront $337 upfront
$0.070/hr $0.050/hr $0.022/hr $0.015/hr
$1840/36mo $1486/36mo $864/36mo $731/36mo
Savings 22% 53% 60%
Prices on Nov 11th, for m3.medium (1 vCPU, 3.75G RAM, SSD) purely to show typical savings

30. @adrianco
Blended BenefitsMix$and$Match$Reserved$Types$and$On4Demand$
Instances(
Days(of(Month(
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Heavy&Utilization&Reserved Instances
Light&RI Light&RILight&RILight&RI
On8Demand

31. @adrianco
Consolidated Cost CuttingConsolidated+Billing:+Single+payer+for+a+group+of+
accounts+
• One$Bill+for+mul7ple+accounts+
• Easy$Tracking$of+account+
charges+(e.g.,+download+CSV+of+
cost+data)+
• Volume$Discounts+can+be+
reached+faster+with+combined+
usage+
• Reserved$Instances$are+shared+
across+accounts+(including+RDS+
Reserved+DBs)+

32. @adrianco
Production PriorityOver%Reserve(the(Produc0on(Environment(
Produc0on(Env.(
Account(
100#Reserved#
QA/Staging(Env.(
Account(
0#Reserved##
Perf(Tes0ng(Env.(
Account(
0#Reserved##
Development(Env.(
Account(
0#Reserved#
Storage(Account( 0#Reserved#
Total#Capacity#

33. @adrianco
Actual Reservation UsageConsolidated+Billing+Borrows+Unused+Reserva4ons+
Produc4on+Env.+
Account+
68#Used#
QA/Staging+Env.+
Account+
10#Borrowed#
Perf+Tes4ng+Env.+
Account+
6#Borrowed##
Development+Env.+
Account+
12#Borrowed#
Storage+Account+ 4#Borrowed#
Total#Capacity#

34. @adrianco
Consolidated Reservations
Burst capacity guarantee
Higher availability with lower cost
Other accounts soak up any extra
Monthly billing roll-up
Capitalize reservation charges!
But: Fixed location and instance type

35. @adrianco
Re-sell Reservations
Reserved'Instance'Marketplace'
Buy$a$smaller$term$instance$
Buy$instance$with$different$OS$or$type$
Buy$a$Reserved$instance$in$different$region$
Sell$your$unused$Reserved$Instance$
Sell$unwanted$or$over;bought$capacity$
Further$reduce$costs$by$op>mizing$

36. @adrianco
Use EC2 Spot Instances
Cloud native
dynamic autoscaled
spot instances
!
Real world total
savings up to 50%

37. @adrianco
Right Sizing Instances
Fit the instance size to the workload

38. @adrianco
Technology Refresh
Older m1 and m2 families
• Slower CPUs
• Higher response times
• Smaller caches (6MB)
• Oldest m1.xlarge
• 15G/8.5ECU/35c 23ECU/$
• Old m2.xlarge
• 17G/6.5ECU/25c 26ECU/$
New m3 family
• Faster CPUs
• Lower response times
• Larger caches (20MB)
• Java perf ratio > ECU
• New m3.xlarge
• 15G/13ECU/28c 46ECU/$
• 77% better ECU/$
• Deploy fewer instances

39. @adrianco
Data Science for Free
Follow%the%Customer%(Run%web%servers)%during%the%day%
Follow%the%Money%(Run%Hadoop%clusters)%at%night%
0
2
4
6
8
10
12
14
16
Mon Tue Wed Thur Fri Sat Sun
No#of#Instances#Running#
Week
Auto7Scaling7Servers
Hadoop7Servers
No.%of%Reserved%
Instances%

40. @adrianco
Real Reservation ReductionsSoaking(up(unused(reserva0ons(
Unused(reserved(instances(is(published(as(a(metric(
(
Ne9lix(Data(Science(ETL(Workload(
• Daily(business(metrics(rollAup(
• Starts(aBer(midnight(
• EMR(clusters(started(using(hundreds(of(instances(
Ne9lix(Movie(Encoding(Workload(
• Long(queue(of(high(and(low(priority(encoding(jobs(
• Can(soak(up(1000’s(of(addi0onal(unused(instances(

41. @adrianco
Six Ways to Cut Costs
#1#Business#Agility#by#Rapid#Experimenta8on#=#Profit#
#2#Business>driven#Auto#Scaling#Architectures#=#Savings##
#3#Mix#and#Match#Reserved#Instances#with#On>Demand#=#Savings#
#4#Consolidated#Billing#and#Shared#Reserva8ons#=#Savings#
#5#Always>on#Instance#Type#Op8miza8on#=#Recurring#Savings#
Building#Cost>Aware#Cloud#Architectures#
#6#Follow#the#Customer#(Run#web#servers)#during#the#day#
Follow#the#Money#(Run#Hadoop#clusters)#at#night#

42. @adrianco
Expect Prices to Drop
Three Years Halving Every 18mo = maybe 40% over-all savings
0
25
50
75
100
1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
Data shown is purely illustrative

43. @adrianco
Combinations

44. @adrianco
Lift and Shift Compounding
0
25
50
75
100
Base Price Rightsized Seasonal Daily Scaling Reserved Tech Refresh Price Cuts
25
3030
707070
100 Traditional
application
using AWS
heavy use
reservations
Base price is for capacity bought up-front

45. @adrianco
Conservative Compounding
0
25
50
75
100
Base Price Rightsized Seasonal Daily Scaling Reserved Tech Refresh Price Cuts
15
20
25
35
50
70
100 Cloud native
application
partially optimized
light use reservations

46. @adrianco
Agressive Compounding
0
25
50
75
100
Base Price Rightsized Seasonal Daily Scaling Reserved Tech Refresh Price Cuts
46812
25
50
100 Cloud native application
fully optimized autoscaling
mixed reservation use
costs 4% of base price
over three years!

47. @adrianco
Cloud Native Patterns
● Business logic isolation in stateless micro-services
● Immutable code with instant rollback
● Auto-scaled capacity and deployment updates
● Distributed across availability zones and regions
● De-normalized single function NoSQL data stores
● See over 40 NetflixOSS projects at netflix.github.com
● Get “Technical Indigestion” trying to keep up with techblog.netflix.com

48. @adrianco
Cost Monitoring and Optimization

49. @adrianco
Final Thoughts
Turn off idle instances
Clean up unused stuff
Optimize for pricing model
Assume prices will go down
Go cloud native to save

50. @adrianco
Further Reading
See www.battery.com for a list of portfolio investments
● Battery Ventures Blog http://www.battery.com/powered
● Adrian’s Blog http://perfcap.blogspot.com and Twitter @adrianco
● Slideshare http://slideshare.com/adriancockcroft
!
● Monitorama Opening Keynote Portland OR - May 7
th
, 2014 - Video available
● GOTO Chicago Opening Keynote May 20
th
, 2014 - Video available
● Qcon New York – Speed and Scale - June 11
th
, 2014 - Video available
● Structure - Cloud Trends - San Francisco - June 19th, 2014 - Video available
● GOTO Copenhagen/Aarhus – Denmark – Sept 25
th
, 2014
● DevOps Enterprise Summit - San Francisco - Oct 21-23rd, 2014 - Videos available
● GOTO Berlin - Germany - Nov 6th, 2014
● AWS Re:Invent - Las Vegas - Cloud Native Cost Optimization - November 14th, 2014
● Dockercon Europe - Amsterdam - Microservices - December 4th, 2014