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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