Cloud compting101

Fabien Hermenierimage credit http://eyepluscamera.files.wordpress.com/

1

was cloud computing needed ?

2

Mainframes

3

Then came with affordable PCs

Then we spread out the load for security, performance, manageability

Then we bought tons of servers to support load spikes

4

5

Amazon X-mas 2013 426 items sold each second6

Where is energy spent ?

7

episode 0 rise of the cloud8

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction.

2011

“”9

1 self-provisioning, no human intervention

On-demand self-services

10

11

2availability over the network

standard mechanisms

broad network access

12

3multi-tenant

virtual or physical resources on-demand allocation

location independance

resource pooling

13

reserved instances (yearly based) on-demand instances (hourly based)

hotspot instances (market based) 14

Amazon EC2 HotSpot instances

bid over the market price to get the instance15

4fast (de-)allocation of resources scale to infinity

rapid elasticity

16

verti

cal e

lastic

ity

Tiers 1

Tiers 2

Tiers 3

17

verti

cal e

lastic

ity

Tiers 1

Tiers 2

Tiers 3

17

horizontal elasticity

Tiers 1

Tiers 2

Tiers 3

18

horizontal elasticity

Tiers 1

Tiers 2

Tiers 3

18

5 metering capabilities transparent reporting

measured service

19

20

and I will call it cloud computing

21

Cloud Computingorigins

22

If computers of the kind I have advocated become the computers of the future, then computing may someday be organized as a public utility just as the telephone system is a public utility... The computer utility could become the basis of a new and important industry.

John McCarthy, 1961

“”

23

cluster computingloosely coupled co-located servers

single tenant non-interactive workload

rigid jobs80s

24

Clo

ud o

r no

t ?

on demand self-services

broad network access

resource pooling

rapid elasticity

measured service

25

Clo

ud o

r no

t ?

on demand self-services

broad network access

resource pooling

rapid elasticity

measured service

26

grid computingIan Foster et al. 2001

27

Pow

er G

rid

Ana

logy

28

virtual organisation heterogeneous hw. multiple applications abstract resources

doing * at

Power grid Computing grid

multiple providers heterogeneous sources

multiple clients abstract source

large scaleindependencelocation

live consumption batch jobs

29

Throughput(MB/s)

TransferThroughput2014-10-2212:40to2014-10-2312:40UTC

alice atlas cms lhcb

13:00

14:00

15:00

16:00

17:00

18:00

19:00

20:00

21:00

22:00

23:00

00:00

01:00

02:00

03:00

04:00

05:00

06:00

07:00

08:00

09:00

10:00

11:00

12:00

0k

5k

10k

15k

20k

25k

Worldwide LHC Computing grid

170 centres to analyse 30 PB / year30

Clo

ud o

r no

t ?

on demand self-services

broad network access

resource pooling

rapid elasticity

measured service

31

Clo

ud o

r no

t ?

on demand self-services

broad network access

resource pooling

rapid elasticity

measured service

32

Application Service Provider

service oriented

pay as you go

95+

1Client

2Client

3Client

remote access to dedicated applications

33

Clo

ud o

r no

t ?

on demand self-services

broad network access

resource pooling

rapid elasticity

measured service

34

Clo

ud o

r no

t ?

on demand self-services

broad network access

resource pooling (not real hw resources)

rapid elasticity

measured service

35

computers on demand.2002Deploy full custom stacks (OS to applications)

36

to (re)deploy reproducible network experiments

multi-tenant, (limited on purpose) resource pooling,

37

to (re)deploy reproducible network experiments

100Mb/s10ms

10ms50ms,

5% loss

38

to (re)deploy reproducible network experiments

10ms

10ms

50ms, 5% loss

39

Clo

ud o

r no

t ?

on demand self-services

broad network access

resource pooling

rapid elasticity

measured service

40

Clo

ud o

r no

t ?

on demand self-services

broad network access

resource pooling

rapid elasticity

measured service

41

S O Aervice

orientedrchitecture

2001+

composable unassociated, loosely coupled units

42

exponential grows since 2001 private and public services to support its growth

43

Two pizza rule

If a team can’t be fed by two pizzas then it is to big

- Jeff Bezos (founder/ CEO of amazon.com)

44

800 x

tons of API, mini-services devoted to automation, flexibility, on-demand services for public and private use

45

2006

scalable web services for other websites or client-side applications

46

SOAP & REST over HTTP pay as you go elastic *-oriented services

*data, network or computation47

Clo

ud !

on demand self-services

broad network access

resource pooling

rapid elasticity

measured service

48

RECAP49

I have a dream, it was about Utility Computing “ ”John McCarthy - 1961

50

web + grid computing + resources on demand + service oriented architectures

cloud computing (2006)

51

can we talk about cloud computing now ?

52

?aaS53

web access to commercial sw. “one to many” model

customers don’t handle upgrades API for integration

Software as a Service

Saa

S

54

55

56

jailed runtime available to host applications generic or provider-specific APIs no control over the environment

Platform as a Service

Paa

S

57

58

$ heroku login…

$ git clone https://github.com/heroku/java-getting-started.git$ cd java-getting-started

$ heroku createCreating warm-eyrie-9006... done, stack is cedar-14http://warm-eyrie-9006.herokuapp.com/ | git@heroku.com:warm-eyrie-9006.gitGit remote heroku added

$ git push heroku master… http://warm-eyrie-9006.herokuapp.com/ deployed to Heroku

$ heroku ps:scale web=1

59

Infrastructure as a Service

low-level resources to deploy arbitrary software stacks complete control over its network, storage and OS

IaaS

60

61

62

63

Things will crash. Deal with it!

Assume you could start with super reliable servers (MTBF of 30 years) Build computing system with 10 thousand of those Watch one fail per day

Dean Keynote, LADIS 2009

“

”

64

~0.5 overheating (power down most machines in <5 mins, ~1-2 days to recover) ~1 PDU failure (~500-1000 machines suddenly disappear, ~6 hours to come back) ~1 rack-move (plenty of warning, ~500-1000 machines powered down, ~6 hours) ~1 network rewiring (rolling ~5% of machines down over 2-day span) ~20 rack failures (40-80 machines instantly disappear, 1-6 hours to get back) ~5 racks go wonky (40-80 machines see 50% packetloss) ~8 network maintenances (4 might cause ~30-minute random connectivity losses) ~12 router reloads (takes out DNS and external vips for a couple minutes) ~3 router failures (have to immediately pull traffic for an hour) ~dozens of minor 30-second blips for dns ~1000 individual machine failures ~thousands of hard drive failures slow disks, bad memory, misconfigured machines, flaky machines, etc. Long distance links: wild dogs, sharks, dead horses, drunken hunters, etc.

Typical first year for a new google cluster

Leslie Lamport

A distributed system is one in which the failure of a computer you didn't even know existed can render your own computer unusable

65

“”

66

Building fault tolerant services

deal with failures deal with inconsistency

be pessimistic

at every level

67

October, 21th 2016: dynDNS targeted by a DDoS

Affected services:

1.2 Tb/s of DNS lookups

68

applications

runtimes

integration/security

database

servers

virtualisation

server HW

storage

network

you

man

age ol’

school IT

69

SaaS

applications

runtimes

integration/security

database

servers

virtualisation

server HW

storage

network

man

aged

by ve

ndor

70

PaaS

applications

runtimes

integration/security

database

servers

virtualisation

server HW

storage

network

you manage

man

aged

by ve

ndor

71

Open-source PaaS stacks

IaaS

applications

runtimes

integration/security

database

servers

virtualisation

server HW

storage

network

you

man

age

man

aged

by ve

ndor

73

Open-source IaaS stacks

(2008+)

cloudstack

(2008+)

(2010+) (2012+)

74

75

vendor lock-in

IaaS PaaS SaaS

Deployment models

76

public cloudgeneral availability to everyone

the “real” cloud reduced costs trust issues ?

77

78

cloud computing vs.

fog of war

79

Trust in megive me your code & data

80

I’m aware read my mails

what is my is hacked ?

private cloudself hosted cloudworldcompany SA

might reduce TCO stronger trust

better manageability

81

worldcompany SA hybrid cloud

82

multi-cloudsyou spread your application

avoid Single Point of Failures* take the benefits of each cloud

LB

83

inter-cloudsthey outsource your components

agreements between the providers“cloud of clouds”

84

fog computing

85

community cloudprivate cloud by and for

multiple organizations

86

RECAP87

CLOUD IS ABOUT REDUCING COSTS

88

CLOUD IS ABOUT SCALABILITY

89

90

CLOUD IS ABOUT RESILIENCY

CLOUD IS ABOUT TRUST