Unlocked Workshop OSCON 2013 - Part I

OSCON
23 july 2013
Portland, OR
Butter Up your application
Tuesday, July 23, 13

welcome &
introductions

your unlocked team
3
Wayne A. Walls
@waynewalls
Alex Brandt
@alunduil
Hart Hoover
@hhoover

get social!
4
@rackspace #unlockedPDX#oscon

6
Business Strategy

7
Cloud Savvy

8
Cloud Freedom

9
Application Fit

cost of cloud
apps
Wayne walls
cloud evangelist

40%PRIVATE CLOUD
11

40%PRIVATE CLOUD
11
50%HOSTED ON-SITE

90% of Workloads Remain In-House...
40%PRIVATE CLOUD
11
50%HOSTED ON-SITE

Cost Considerations
Infrastructure
12

13
How many customers can you serve?

14
How easy would it be to scale?

Innovation
15

In-house?
16

Cost Considerations
17
Developers

18
Developer time translates into $

19
Apply effort where it matters

20
Be realistic about engineering time

21
Choose tools that scale

everything
as code
Wayne walls
cloud evangelist
hart hoover
cloud evangelist

24
Self-service

25
On-demand

26
Metered

27
Resource pooling

28
Broad network access

NIST SAys...
29

NIST says...
30

NIST says...
31

multi-cloud
32

ENTER devops
33

34
Culture & Work Methodology

35
Tooling

36
Deployment Strategies

37
Measure All the Things

38
Automate All the Things

41
Gerrit

42
Gerrit

Infrastructure as code
45

46
Same Problems

47
What version is in production?

48
Issues are found, fixed & redeployed quickly

49
Test as you develop

50
Same Best Practices

51
Tag, branch & release code that defines infra

52
Coverage lifecycle over various stages

53
Continuously Test

Chef
Server
Chef
Workstation
Chef Client
knife
node
Chef Client
node
environment
55

•Nodes: Servers
•Environments: Groups of nodes (Dev/QA/Prod)
•Recipes: Describes the desired state of a node
•Cookbooks: Group of Recipes
•Roles: Group of Cookbooks (Web)
•Attribute: information about the current state of a node
56

Thinking like a developer
57

Product
Backlog
Sprint
Backlog
Sprint
Working increment
of the software
58
1. Design
5. QA 2. Build
4. Release 3. Configure

59
1. Design
5. QA 2. Build
4. Release 3. Configure

Test Driven Development

Behavior Driven Development

Behavior Driven Development Domain Driven Development

Behavior Driven Development
Application Bliss
Domain Driven Development

POLYGLOT
PERSISTENCE
alex brandt
sr developer

65
RDBMS may not be the best fit

68
5 Characteristics

69
Non-relational

70
Distributed

71
Open-source

72
Horizontally Scalable

73
Schema-less

orders
customers
order lines
credit cards
ID: 1001
line items:
customer: Ann
0321293533
0321601912
0131495054
2
1
1
$48 $48
$39
$51
$39
$51
payment details:
Card: Amex
CC #: 12345
expires: 04/2001
74

75
There are several different types of
data stores that are considered to
be NoSQL

76
Key/Value Databases

77
Document Databases

78
Column-Family Stores

79
Graph Databases

80
Types in Detail

Key/Value DatabaseS
81

Key/Value DatabaseS
• Good Use Cases:
• Storing Session Information
• User Profiles & Preferences
• Shopping Cart Data
• Bad Use Cases:
• Data Relationships
•Multi-operation Transactions
•Query by Data
82

Key/Value DatabaseS
• Good Use Cases:
• Storing Session Information
• User Profiles & Preferences
• Shopping Cart Data
• Bad Use Cases:
• Data Relationships
•Multi-operation Transactions
•Query by Data
83

document Database
84

document Databases
•Good Use Cases:
• Event Logging
• Blogging Platforms
• Real-time Analytics
• Article storage
• Bad Use Cases:
• Complex Transactions
•Queries against Varying
Aggregate Structures
85

document Databases
•Good Use Cases:
• Event Logging
• Real-time Analytics
• Article storage
• Bad Use Cases:
• Complex Transactions
•Queries against Varying
Aggregate Structures
86

COLUMN FAMILY
87

COLUMN-FAMILY
datastores
•Good Use Cases:
• Event Logging
• Counters (page visits)
• Expiring Usage
• Bad Use Cases:
• ACID transactions
required
• Early prototype
applications
89

graph database
90

Amanda
KNOWS
KNOWS
KNOWS
Robert
Gerry
Lamar
KNOWS
App 1
BUILT
BUILT
KNOWS
App 2
USES
BUILT
Christie
KNOWS
Destiny
Jessica
KNOWS
App 3
BUILT
USES
USES
USES
KNOWS
graph database
91

graph databases
•Good Use Cases:
• Connected Data
• Location-based services
• Recommendation engines
• Bad Use Cases:
• Ability to update
specific aggregates
92

Companies using
nosql
93
DATABASE COMPANIES

THE FUTURE IS POLYGLOT
94
Neo4J
database
Cassandra
database
Couch
database
MongoDB
database
RELATIONAL
DATABASE
Graph-structured
domain rules
Columnar data
access with
decentralization
Document
structures
Document structures
with offline
processing
(Actors) (Actors)
(Actors)(Actors)
Asynchronous message passing
MODULE 1
MODULE 2
MODULE 3
MODULE 4
IEEE Software Sept/October 2010 - Debasish Ghosh / Twitter @debasishg

95
POLYGLOT PATTERN: cache
ORDER
TAKING
RESTAURANT
MANAGEMENT
REDIS
CACHE
MYSQL
DATABASE
SECONDFIRST
CONSUMER
RESTAURANT
OWNER
Credit: @crichardson

96
POLYGLOT PATTERN:
write to sql and NOSQL
NEW
TWEET
INSERT
LPUSHX
LTRIM
MySQL
TWEETS
FOLLOWS
FOLLOWERS
Redis: Timeline
FOLLOWER 1
FOLLOWER 2
FOLLOWER 3
Avoid
expensive
MySQL joins

97
POLYGLOT PATTERN:
REPLICATE FROM
MYsql to NOSQL
QUERY
SERVICE
UPDATE
SERVICE
REDIS
MYSQL
DATABASE
SYSTEM
OF
RECORD
MATERIALIZED
VIEW
READER WRITER
replicate and
denormalize
query() update()

98
Atomic
Consistent
Isolated
Durable
ACID to base
Basically Available
Soft state
Eventually consistent

Unlocked Workshop OSCON 2013 - Part I

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Unlocked Workshop OSCON 2013 - Part I