The Post-Cloud. Where Google, DevOps, and Docker Converge

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1 The Post-Cloud Where Google, DevOps, and Docker Converge

2 About me Principal Architect, Intel Corporation DevOps, Telemetry, PaaS, Containers, Puppies Former: VMware EMC Nicholas

3 produce effort consume

4

5

6

7 produce effort Machines consume

8 produce effort Machines consume

9 produce effort Computing Machines consume

10 produce effort Computing consume

11 The Paradox Jevons Paradox: The proposition that as technology progresses, the increase in efficiency with which a resource is used tends to increase (rather than decrease) the rate of consumption of that resource.

12 What does efficiency look like to us?

13 DevOps

14

15 App OS Server

16 App App App App App OS OS OS OS OS Server Server Server Server Server

17 App App App App App OS OS OS OS OS VM VM VM VM VM Hypervisor Server

18 Container Container Container pp Image App Image Container Image Container Image Container Image App Image Ap App App App S O OS M VM VM rvisor Hyper Hypervisor rver Ser Server

19

20

21

22

23 DevOps - Cultural change Automation over manual repetition Decouple deployments from operations Convert change from being from interactive to programmable Make the datacenter declarative

24 DevOps - Cultural change Automation over manual repetition Decouple deployments from operations Convert change from being from interactive to programmable Make the datacenter declarative

25 DevOps - Cultural change Automation over manual repetition Decouple deployments from operations Convert change from being from interactive to programmable Make the datacenter declarative

26 DevOps - Cultural change Automation over manual repetition Decouple deployments from operations Convert change from being from interactive to programmable Make the datacenter declarative

27 DevOps = Efficiency in controlling change

28

29 PaaS

30 App

31 IaaS

32 App? VM IaaS

33

34 App Code Libs Runtime OS VM IaaS

35

36 App DB Code Libs Runtime MQ OS OS OS VM VM VM IaaS

37 App PaaS

38 App PaaS IaaS

39 App What an App wants. What an App needs.

40 App PaaS, like IaaS but closer to the point.

41 Packaging Configuration Dependencies App Services Databases Runtimes

42 PaaS is a great starting point for: Container integration (Docker) Microservices implementation Continuous Deployment (DevOps)

43 PaaS = Efficiency through frictionless application fulfillment

44 Docker + Containers

45 System (Ubuntu* 14.04)

46 Container A Container B System

47 Resource Limiting Container Memory 1GB Container Memory 2GB Container A Container B System Memory

48 Resource Limiting Container Memory 1GB Container Memory 2GB Block Device 10 MB/s Container A Block Device 10 MB/s Block Device 20 MB/s Container B System Storage

49 Resource Limiting Container Memory 1GB CPU 25% Share Container Memory 2GB CPU 75% Share Block Device 10 MB/s Block Device 10 MB/s Block Device 20 MB/s Container A Container B System CPU

50 Namespace Isolation Processes Container Memory 1GB CPU 25% Share Container Memory 2GB CPU 75% Share Block Device 10 MB/s Block Device 10 MB/s Block Device 20 MB/s Container A Container B PID PID Container A s view of PIDs Container B s view of PIDs

51 Namespace Isolation - Networking Container Memory 1GB CPU 25% Share Container Memory 2GB CPU 75% Share Block Device 10 MB/s Block Device 10 MB/s Block Device 20 MB/s Container A Container B Interfaces veth0 veth1 Container A s view of interfaces Interfaces veth3 Container B s view of interfaces

52 Namespace Isolation Mounts Container Memory 1GB CPU 25% Share Container Memory 2GB CPU 75% Share Block Device 10 MB/s Block Device 10 MB/s Block Device 20 MB/s Container A Container B Mounts /dev/sda1 Container A s view of mounts Mounts /dev/sda2 /dev/sda3 Container B s view of mounts

53 Namespace Isolation Mounts Container Memory 1GB CPU 25% Share Container Memory 2GB CPU 75% Share Block Device 10 MB/s Block Device 10 MB/s Block Device 20 MB/s Container A Container B Mounts /dev/sda1 Container A s view of mounts Mounts /dev/sda2 /dev/sda3 Container B s view of mounts

54 Namespace Isolation Users Container Memory 1GB CPU 25% Share Container Memory 2GB CPU 75% Share Block Device 10 MB/s Block Device 10 MB/s Block Device 20 MB/s Container A Container B Users neo morpheus trinity Users harry hermione ron Container A s view of users Container B s view of users

55 VM VM VM Widget Painter Service Widget Scraper Service Widget Cleaner Service Widget Lib Widget Lib Widget Lib Linux * OS Linux OS Linux OS

56 Container A Container B Container C Widget Painter Service Widget Scraper Service Widget Cleaner Service Widget Lib Linux * OS

57 VM Container A Container B Container C Widget Painter Service Widget Scraper Service Widget Cleaner Service Widget Lib Linux * OS

58 Container Benefits: Faster lifecycle vs. virtual machines Contains what is running within the OS Ideal for homogenous application stacks on Linux* Almost non-existent overhead Very efficient way to control resources on a Linux host

59

60

61 Docker * Images Ordered results of actions to build a container Add file Open port Run a command DevOps like source code for a deployment image Uses a copy-on-write file system (like others)

62 Images are layers cmd =../apache2 set env var run apt-get from ubuntu:14.04 rootfs bootfs

63 Images are layers my_app cmd =../apache2 set env var run apt-get from ubuntu:14.04 rootfs bootfs

64 Images are layers my_app2 cmd =../apache2 mount dir run git-clone from my_app rootfs bootfs

65 Image Registry Public Docker registry: Docker * Hub Option to deploy your own private Docker Registry

66

67

68

69 Docker: Reducing the cost of using containers in both operational overhead (time) and needing the expertise of the few

70 Docker enabled: Creating immutable and versioned application units Portability of these units Extremely fast deployment and standup of these units

71 Docker = Efficiency in a well-designed interface for controlling containers

72 Big Data

73

74 First problem Efficient access to data

75 Second problem Extracting useful information that is useful for a domain

76 Big Data = Efficiency through access to store, retrieve, and extract information

77 Big Data = Efficiency through access to store, retrieve, and extract information Domain-relevant information is critical to making efficient decisions

78 Google

79

80 Server

81 Server

82 Server

83

84

85 The efficiencies

86 frictionless control of complex things

87 taking data access for granted

88 broad decision making abilities

89 The Road to Awe

90 I want to deploy my Web Service x86 servers

91 I want to deploy my Web Service to a virtual server x86 Virtualization

92 I want to migrate my virtual machines containing my Web Service around Live Migration (vmotion)

93 I want Web Service virtual machine deployed as a service IaaS (OpenStack, EC2)

94 I want my Web Service(s) automagically configured DevOps (Puppet, Chef, Ansible)

95 I want my Web Services(s) built, packaged, and released as a service PaaS (Cloud Foundry)

96 I want my Web Services(s) captured as immutable and versioned images Docker

97 I want my Web Services(s) as immutable images I can turn up in a second for a developer to work on Docker

98 I want my Web Services(s) as immutable images I can turn up in a second for testing cycles Docker

99 I want my Web Services(s) as immutable images I can turn up in a second in production Docker

100 I want my Web Service(s) to be spun up on demand Scheduling (Mesos, Kubernetes, CF Diego)

101 I want my Web Service(s) to be quickly replaced on error Scheduling (Mesos, Kubernetes, CF Diego)

102 I want my Web Service(s) to be spun down on lack of demand Scheduling (Mesos, Kubernetes, CF Diego)

103 I want my Web Service(s) to be placed intelligently to maximize use of my computing power Scheduling (Mesos, Kubernetes, CF Diego)

104 I want my Web Service(s) to be managed intelligently based on advanced data from any level The Post-Cloud

105 Actually, I just want to work on the Web Service and have the datacenter do all the rest The Post-Cloud

106 Pushing for the paradox.

107 Watcher

108 WATCH COLLECT

109 Decider

110 COLLECT WATCH DECIDE

111 Actor

112 COLLECT WATCH DECIDE ACT

113 COLLECT WATCH DECIDE ACT APP

114 COLLECT WATCH DECIDE ACT APP SERVER / STORAGE / NETWORK

115 Pushing for the paradox. What has to come next?

116 Greater exposure of telemetry

117 Google Omega-style decision making for the masses* *fed by knowledge built on telemetry

118 Brand new disciplines around extracting efficiency

119 Massive cooperation of cloud domains

120 In conclusion

121 In conclusion

122 The Post-Cloud is what emerges from the next evolution of efficiency in computing.

123 The Post-Cloud is just a label for the computing that our grandchildren will take for granted as they provide their own value.

124 Nicholas Thank You

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