image credit Fabien Hermenier Cloud compting 101

Transcription

1 image credit Fabien Hermenier Cloud compting 101 1

2 was cloud computing needed? 2

3 3 Mainframes

4 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 5

6 Amazon X-mas items sold each second

7 Where is energy spent? 7

8 episode 0 rise of the cloud 8

9 2011 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. 9

10 1 self-provisioning, On-demand self-services no human intervention 10

11 11

12 2 broad network access availability over the network standard mechanisms 12

13 3 multi-tenant resource pooling virtual or physical resources on-demand allocation location independance 13

14 reserved instances (yearly based) on-demand instances (hourly based) hotspot instances (market based) 14

15 Amazon EC2 HotSpot instances bid over the market price to get the instance 15

16 rapid elasticity fast (de-)allocation of resources scale to infinity 16 4

17 vertical elasticity Tiers 1 Tiers 2 Tiers 3 17

18 Tiers 1 Tiers 2 Tiers 3 horizontal elasticity 18

19 5 metering measured service 19 capabilities transparent reporting

20 20

21 and I will call it cloud computing 21

22 Cloud Computing origins 22

23 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, 23

24 cluster computing loosely coupled co-located servers 80s single tenant non-interactive workload rigid jobs 24

25 Cloud or not? on demand self-services broad network access resource pooling rapid elasticity measured service 25

26 Cloud or not? on demand self-services broad network access resource pooling rapid elasticity measured service 26

27 grid computing Ian Foster et al

28 Power Grid Analogy 28

29 Power grid Computing grid multiple providers heterogeneous sources multiple clients abstract source live consumption location doing * at virtual organisation heterogeneous hw. multiple applications abstract resources batch jobs independence large scale 29

30 Worldwide LHC Computing grid 25k T ransfer T hroughput :40 t o :40 UTC 20k T hroughput (MB/s) 15k 10k 5k 0k 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 alice atlas cms lhcb 30 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: centres to analyse 30 PB / year

31 Cloud or not? on demand self-services broad network access resource pooling rapid elasticity measured service 31

32 Cloud or not? on demand self-services broad network access resource pooling rapid elasticity measured service 32

33 Client 1 Client 2 Client 3 Application Service Provider 95+ remote access to dedicated applications service oriented pay as you go 33

34 Cloud or not? on demand self-services broad network access resource pooling rapid elasticity measured service 34

35 Cloud or not? on demand self-services broad network access resource pooling (not real hw resources) rapid elasticity measured service 35

36 2002 computers on demand. Deploy full custom stacks (OS to applications) 36

37 to (re)deploy reproducible network experiments multi-tenant, (limited on purpose) resource pooling, 37

38 to (re)deploy reproducible network experiments 50ms, 5% loss 10ms 100Mb/s 10ms 38

39 to (re)deploy reproducible network experiments 50ms, 5% loss 10ms 10ms 39

40 Cloud or not? on demand self-services broad network access resource pooling rapid elasticity measured service 40

41 Cloud or not? on demand self-services broad network access resource pooling rapid elasticity measured service 41

42 2001+ S ervice O oriented A rchitecture composable unassociated, loosely coupled units 42

43 exponential grows since 2001 private and public services to support its growth 43

44 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

45 800 x tons of API, mini-services devoted to automation, flexibility, on-demand services for public and private use 45

46 2006 scalable web services for other websites or client-side applications 46

47 SOAP & REST over HTTP pay as you go elastic *-oriented services *data, network or computation 47

48 on demand self-services Cloud! broad network access resource pooling rapid elasticity measured service 48

49 RECAP 49

50 I have a dream, it was about Utility Computing John McCarthy

51 web + grid computing + resources on demand + service oriented architectures cloud computing (2006) 51

52 can we talk about cloud computing now? 52

53 ?aas 53

54 SaaS Service as a Service web access to commercial sw. one to many model customers don t handle upgrades API for integration 54

55 55

56 56

57 PaaS Platform as a Service jailed runtime available to host applications generic or provider-specific APIs no control over the environment 57

58 $ heroku login $ git clone $ cd java-getting-started $ heroku create Creating warm-eyrie done, stack is cedar-14 git@heroku.com:warm-eyrie-9006.git Git remote heroku added $ git push heroku master deployed to Heroku $ heroku ps:scale web=1 58

59 59

60 IaaS Infrastructure as a Service low-level resources to deploy arbitrary software stacks complete control over its network, storage and OS 60

61 61

62 62

63 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 Things will crash. Deal with it! 63 Dean Keynote, LADIS 2009

64 Typical first year for a new google cluster ~0.5 overheating (power down most machines in <5 mins, ~1-2 days to recover) ~1 PDU failure (~ machines suddenly disappear, ~6 hours to come back) ~1 rack-move (plenty of warning, ~ 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. 64

65 A distributed system is one in which the failure of a computer you didn't even know existed can render your own computer unusable Leslie Lamport 65

66 Building fault tolerant services at every level be pessimistic deal with failures deal with inconsistency 66

67 applications runtimes ol school IT you manage integration/security database servers virtualisation server HW storage network 67

68 applications runtimes SaaS integration/security database servers virtualisation server HW managed by vendor storage network 68

69 you manage applications runtimes PaaS integration/security database servers virtualisation server HW managed by vendor storage network 69

70 Open-source PaaS stacks

71 applications you manage runtimes integration/security IaaS database servers virtualisation server HW storage network managed by vendor 71

72 Open-source IaaS stacks (2008+) (2008+) cloudstack (2010+) (2012+) 72

73 vendor lock-in IaaS PaaS SaaS 73

74 Deployment models 74

75 public cloud general availability to everyone the real cloud reduced costs trust issues? 75

76 cloud computing vs. fog of war 76

77 give me your code & data Trust in me 77

78 I m aware read my mails what is my is hacked? 78

79 private cloud worldcompany SA self hosted cloud might reduce TCO stronger trust better manageability 79

80 worldcompany SA hybrid cloud 80

81 LB multi-clouds you spread your application avoid Single Point of Failures* take the benefits of each cloud 81

82 inter-clouds they outsource your components agreements between the providers cloud of clouds 82

83 distributed clouds back to volunteer computing (Boinc, ) 83

84 community cloud private cloud by and for multiple organizations 84

85 RECAP 85

86 CLOUD IS ABOUT REDUCING COSTS 86

87 CLOUD IS ABOUT SCALABILITY 87

88 CLOUD IS ABOUT RESILIENCY 88

89 CLOUD IS ABOUT TRUST 89