Indistinguishable from magic
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1 Indistinguishable from magic Seth Eliot Principal Knowledge Engineer, Engineering Excellence September 11, 2014 How cloud services, big data, and mobile enable software success and customer delight Presentation to
2 About Seth A/B testing of services Big-Data processing platform Quality Cloud Services Data-Driven Engineering
3 Any sufficiently advanced technology is indistinguishable from magic. (umulig å skille fra magi) Arthur C. Clarke
4
5
6 what we take for granted today would seem like magic being able to talk to people over long distances, to transmit images, flying, accessing vast amounts of data like an oracle. These are all things that would have been considered magic a few hundred years ago. Elon Musk
7 Three magics Each with their own powers Cloud services Data Omnipresence Mobile
8 Magic 1 Cloud services
9 Cloud services Software as a Service (SaaS) End-users view of the cloud Consumer or enterprise
10 Omnipresence It is everywhere and growing
11 Many, many consumer services Skype bing Yammer OneDrive Outlook.com
12 SaaS use and growth
13 Like a utility Self-service Reliable Low cost On tap
14 We run the datacenter for you Hardware Power Security Supply Chain Personnel
15 TCO/Workload Economies of Scale Larger datacenters have almost 50% lower Total Cost of Ownership (TCO) per server MAIN DATA CENTER COST BUCKETS ANNUAL TCO/SERVER DECLINES W/SCALE Server hardware costs (~45% of total costs) $5,000 $4,000 Facility & operations (~25%) $3,000 Hardware labor costs (~15%) $2,000 $1,000 Power costs (~15%) $0 1k Server DC 100k Server DC Series1 Series2 Series3 Series4
16 Elasticity Use as much or as little as you need
17 Scalable services Pay for what you need Often a freemium model
18 Total Services Load Provisioned Servers (includes buffer) provided in a scalable manner M Tu W Th F
19 Unlock data Continuous improvement Deliver improvements
20 How services are different Box product is like a Service is like a Power generator Power utility Who runs it? Customer Company How monitored? Sporadic customer contact Continuous data When updated? Infrequent Continuous
21 Services enable continuous improvement using data Deploy This is an iterative cycle. Services can do this. Improve Data Other software can also
22
23 a lot of times the teams are not really aware of the cost run-ups Coburn Watson, Cloud Performance Engineering, Netflix Netflix uses innovative means to surface cloud costs
24 Cloud services Powers Magic Powers Omnipresence On tap Elasticity Continuous improvement
25 Magic 2 Data
26
27 Guinness world record Largest collection of Star Wars Lego Jon Jessesen, Vika, Norway
28 Omnipresence Almost everything emits data and it s growing
29 Connected Devices (Billions) Internet of MANY things (predicted)
30 All the data in the world ZB 1 ZB= 1 trillion GB ZB
31 Social: data plus services June B monthly active users 81% on mobile 350 million photos daily
32 Unlock secrets Gain insights from the past and present
33 Ctrl-t a b 33
34 Newer photos Photo Age Older photos Measure 82% of traffic is focused on 8% of newest photos Improve Designed new datacenters and software to manage new photo storage categories hot, warm, cold Results Reduced cost of cold storage rack to 1/3 rd of traditional rack Reduced cost of new datacenter to 1/5 th of a traditional datacenter 270W of energy saved per sq. ft
35 CTR CTR A/B Testing Controlled experimentation 50% Visitors Randomly Distributed 50% Version A (Control) Version B (Treatment) Page Title Title of Page Signup Here Signup Here It was very humbling to see how bad we were at predicting which features are going to work with users or not. User interactions instrumented, analyzed and compared - Ronny Kohavi, GM, Bing 1.2% of users with a Page View clicked on Signup 2.8% of users with a Page View clicked on Signup Is the observed difference statistically significant? YES Version B is better than Version A
36 A/B Testing What happens to new user retention when you shorten the signup flow? It goes down! Don t ship that feature
37 Predicts future Predictive analytics Machine Learning
38 EXO prioritizes availability Monthly Uptime Percentage Service Credit < 99.9% 25% < 99% 50% < 95% 100% Downtime is defined as any period of time when users are unable to send or receive via all supported mailbox access
39 Availability Exchange Online availability Time Predict dips 24 hours ahead of time
40 Availability Exchange Online availability Time Predict 75% of dips 24 hours ahead of time
41 Predict data center failures SMART data used to predict disk failures (Self-Monitoring, Analysis and Reporting Technology) 60% 5%
42 Big data Any size or little data
43
44 Little data is powerful also User research Relatively small data set Fail Fast or Double-Down
45 How Gilles spent his vacation Kindle First Gen 2007
46
47
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49 Data Powers Magic Powers Omnipresence Unlock secrets Predicts future Any size
50 Magic 3 Mobile
51 Mobile is a force multiplier Services goes with the user Data goes with the user.wherever they go
52 Omnipresence The purpose of mobile
53 Mobile subscriptions worldwide Cellular Broadband
54 It s about the mobile data
55 Sees all Crowd-source data to improve users experiences
56 Data from users Win-win sharing Social Wisdom of crowds
57 Data from sensors Crowd sourced weather Humidity Pressure Temperature GPS Plus user submitted observations
58 Power of crowd-sourced data Waze Outsmarting traffic, together 48MM Users 1B+ Miles Driven per Month
59 Tells all Mobile taps into the world of information
60 Data from the web Via search engines and their APIs bing
61 Apps put that in our pockets Bing indexes the world
62 Mobile Powers Magic Powers Omnipresence Sees all Tells all
63 Three technologies indistinguishable from magic Mobile Each with their own powers Combined to greater power Cloud services Data
64 Thank you! Indistinguishable from magic How cloud services, big data, and mobile enable software success and customer delight
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