Cloud Economics in Training and Simulation

Nane Kratzke

CLOUD ECONOMICS IN
TRAINING AND SIMULATION

Prof. Dr. rer. nat. Nane Kratzke
1
Computer Science and Business Information Systems

The next 20 to 25 minutes are about ...

•  What is cloud computing?

•  (Economical) characteristics of cloud computing

•  Postulated use cases for cloud computing

•  Some data from real world

•  Decision making is not always obvious => How to
decide?

•  Some findings
2

What is a cloud computing (definition)

„Cloud computing is a model for
enabling ubiquitous, convenient, on-
demand network access to a shared pool
of configurable computing resources
(e.g., networks, servers, storage,
applications, and services) that can be
rapidly provisioned and released with
minimal management effort or service
provider interaction.“

National Institute of Standards and Technology,
NIST: „The NIST definition of cloud computing“;
Peter Mell, Timothy Grance, 2011

http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf
3

Essential Characteristics of Clouds

•  No human •  Remote access via •  Resources are
interaction thin or fat client pooled to serve
necessary platforms multiple consumers
•  Programmable data •  No physical access •  Little control or
center knowledge over
exact location

On-demand Network Resource
self-service access pooling

C enter
Data
•  Rapid provisioning able Pay-per-use cture
amm
• 
gr a s tr u
Pro are d Infr
•  Autoscaling business model
e•  Resource usage
•  Ressources
virtuallyware defin can be monitored,
unlimited
S oft controlled, and
reported

Rapid Measured
elasticity Service

4
Praktische Informatik und betriebliche Informationssysteme

Business Characteristics

Fixed costs become
Pay as you go
variable

Cost are associative Business gains
•  100 servers for one hour flexibility
•  1 server for 100 hours •  no long-term financial
•  (Almost) same price commitment to
resources

5

Economical Cloud Usage Patterns
have to do with peak loads

„In other words, even if cloud
services cost, say, twice as
much, a pure cloud solution
makes sense for those demand
curves where the peak-to-
average ratio is two-to-one or
higher.“

Weinman, Mathematical Proof of
the Inevitability of Cloud
Computing, 2011

http://www.joeweinman.com/Resources/Joe_Weinman_Inevitability_Of_Cloud.pdf

Peak loads are cloud economics best friends
6

Postulated use cases

These use cases (among others) are postulated to be cloud compatible:
data storage,
support software short-term system disaster recovery
hosting websites
development cycles demonstrations and business
continuity

overflow processing
Training and media processing or large-scale
simulation
education and rendering scientific data
processing

•  Research shows that cost advantages of cloud
computing are deeply use case specific
•  Be aware of comparing non comparable use
cases
•  This contribution presents some data of
educational use cases (similar usage
characteristics of simulation use cases)

7

Analyzed use case

•  Web technology lecture/practical course for
computer science students (bachelor) in summer
2011 and summer/winter 2012.
•  Projects: Development of web information
systems (Drupal based)
•  All groups were assigned cloud service accounts
provided by Amazon Web Services (AWS).
•  Analysis of billing as well as usage data provided
by AWS.

8

(A)
Costs per Month (aligned to Weeks)
500
Cost analysis
400
Costs in USD

300
200

Total costs: 846.99 $
100

Total students: 49
Cost per student: 17.28 $
0

CW 13 CW 14 – CW 17 CW 18 – CW 21 CW 22 – CW 25

Calendar Weeks (CW)

(B)
Main Cost Drivers

instancehour (62%)
Main identified cost drivers:
(1)  Server uptime (2/3)
datatransfer (0%)
adressing (3%)
(2)  Data storage (1/3)

datastorage (34%)

9

Usage Analysis

(A)
Maximum and Average Box Usage
Training
50

Average Box Usage
Maximum Box Usage in an hour
40
Used Server Boxes

30

Project 24x7 Migration
20
10
0

13 14 15 16 17 18 19 20 21 22 23 24 25

Calendar Week

10
(B)

0
13 14 15 16 17 18 19 20 21 22 23 24 25
Average to Peak Ratio per Week
Calendar Week

(C)
Average Box to Maximum Box Ratio
according to Weinman
1.0

Cloud computing is
economical not reasonable
Avg to Max Box Usage Ratio

0.8

Cloud computing
0.6

might be reasonable
0.4

Cloud computing is
0.2

economical reasonable
0.0

14 16 18 20 22 24

Calendar Week
11

Economical Decision Analysis
A four step process to decide for or against cloud based solutions

(A)
Determine your atp Maximum and Average Box Usage

50
ratio Average Box Usage

40
Used Server Boxes

30
Determine your

20
dedicated costs

10
0
13 14 15 16 17 18 19 20 21 22 23 24 25

Calendar Week

Determine your
(B)
maximal cloud costs Max instances: 49 2000 Accumulated Processing Hours per Week

Processing hours: 7612
1500
Processing Hours

Determine appropriate
Average: 7612 / (26 * 7 * 24) = 1.74
1000

cloud ressources Overall atp ratio: 1.74 / 49 = 0.035
500

12
0

13 14 15 16 17 18 19 20 21 22 23 24 25


Determine your atp „In other words, even if cloud services cost,
ratio say, twice as much, a pure cloud solution
makes sense for those demand curves where
the peak-to-average ratio is two-to-one or
higher.“
Determine your
dedicated costs Weinman, Mathematical Proof of the Inevitability
of Cloud Computing, 2011

Determine your Example Server: 500 US Dollar
maximal cloud costs
Amortization: 3 years

500$
Determine appropriate d3years (500$) = = 0.019 $ h
cloud ressources 3 • 365 • 24h

13


According to Weinman the peak-to-average
Determine your atp
ratio ratio should be greater than the ratio between
the variable costs c and your (assumed)
dedicated costs d:

Determine your
dedicated costs

Determine your
maximal cloud costs

Determine appropriate 0.019 $ h $
cloud ressources c Max = = 0.54
0.035 h
14


Determine your atp 0.019 $ h $
ratio c Max = ≈ 0.54
0.035 h

Pricings for EU region, 19th March, 2012
Determine your €

Example: Amazon Web Services EC2-
dedicated costs

Determine your
maximal cloud costs

Determine appropriate
cloud ressources

15

A four step process to decide for or against cloud based virtual labs

The measured ATP ratio of 0.035 means in fact a 1/0.035 ==
28.57 times cost advantage.
This means for the presented use case:

A cloud based solution provides a more
than 25 times cost advantage.

Compared to necessary investment efforts for a classical
dedicated system implementation.

16

Why this big cost advantage?

(A)
How to dimensionize the data center?
peak load
50

Average Box Usage
And the delta?
40
Used Server Boxes

30

Measures the overdimension of a data center
20

average
10

load
0

13 14 15 16 17 18 19 20 21 22 23 24 25

Calendar Week
What is the need?
17
(B)

In other words ...

(A)
You have to finance a really big house ...
50

Average Box Usage
40

... knowing
Used Server Boxes

that you
will inhabit
30

only some
rooms of it.
20
10
0

13 14 15 16 17 18 19 20 21 22 23 24 25

Calendar Week

18
(B)

Findings

•  Cloud computing loves peak load scenarios (be happy)
•  25 times cost advantage (analyzed use case)
•  Cloud generated costs are use case specific (be carefull)
•  Decision making must not be obvious
•  Four step decision making model (to determine your ATP ratio)
•  Main cost drivers are (try to minimize)
•  Server uptime
•  Data storage (server volumes)
•  Data transfer (in communication intensive use cases)
•  Uneconomical use cases (try to avoid)
•  24x7 and
•  constant loads

•  So if you have to deal with peak load scenerios it is
likely that cloud based solutions might be an
economical option ...

19

Thank you for listening

Find this presentation here:
http://www.slideshare.net/i21aneka/itis-ws-2013

Slideshare:
i21aneka
XING:
Nane_Kratzke
LinkedIn:
nanekratzke
Prof. Dr. Nane Kratzke
Computer Science and WEB:
Business Information Systems http://praktische-informatik.fh-luebeck.de
Lübeck University of Applied Sciences
Mönkhofer Weg 239
Mail: Twitter:
23562 Lübeck
nane.kratzke@fh-luebeck.de @nanekratzke
Germany

20

Qualitative IT-Management Impact of Clouds

Governance Enterprise system design Operation
(COBIT) (TOGAF) (ITIL)

12 x Positive 3 x Positive 6 x Positive
8 x Negative 0 x Negative 3 x Negative

21

Advantages and short comings of cloud computing

Advantages Short comings

l
cture and low leve
Physical infrastru mer perspective)
o
service free (cust
mpliancy
More complex co t
ted functional managemen
Pro vision of automa
services

t
cu rity managemen
More complex se
(ex post)
Cost transparency

d
rvice, process an
More complex se anagement
ntinuousity and configuration m
Inhe rent scalability, co
availability

22

So – everthing is beautifull?
No substantial show stoppers?

•  Higher order showstoppers for cloud approaches
Hard to handle
•  Security and Compliance Management
•  Incompatible SLAs
•  Especially national laws, privacy, data ownership,
confidentiality, data location, forensic evidence, auditing, etc.

•  Decision making showstoppers for cloud approaches
Could be solved
•  Ex post but no ex ante cost transparency
•  Relevant costs of cloud approaches must be known before a
system enters operation
•  Otherwise IT investment decisions pro or contra cloud based
approaches can not been made

23

Typical Cost Structure

Infrastructure ... Platform ... Software ...

... as a Service

Service Level Cost category

•  IaaS + Scalability •  datatransfer
•  PaaS •  dataprocessing
•  SaaS •  datastorage
•  network
•  monitoring
•  per request
•  per user/account

24

Assignment of cost categories to Cloud Service Levels

Per
Data Data Data Net- Moni-
Request/
storage processing transfer work toring
User

Scalability X X X

X
IaaS X X X X X (per micro
request)

X
PaaS X X X (per
request)

X
SaaS X X
(per user)

25

Cloud Economics in Training and Simulation

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