DevOps, Databases and The Phoenix Project UGF4042 from OOW14
1. Virtual Data Platform:
or
Revolutionizing Database Cloning
How can the DBA make the biggest
impact on the company
1
http://kylehailey.com
kyle@delphix.com
2. The Goal : Theory of Constraints
Improvement
not made
at the constraint
is an illusion
factory floor optimization
8. Theory of Constraints work for IT ?
• Goals Clarify
• Metrics Define
• Constraints Identify
• Priorities Set
• Iterations Fast
• CI
• Cloud
• Agile
• Kanban
• Kata
“IT is the factory floor of this century”
10. What are the top 5 constraints in IT?
1. Dev environments setup
2. QA setup
3. Code Architecture
4. Development
5. Product management
“One of the most powerful
things that organizations
can do is to enable development
and testing to get
environment they need when
they need it“
- Gene Kim
11. Data is the constraint
CIO Magazine Survey:
60% Projects Over Schedule
85% delayed waiting for data
Data is the Constraint
only getting worse
Gartner: Data Doomsday, by 2017 1/3rd IT in crisis
17. Typical Architecture
Production
Instance
Reporting Backup
Database
File system
Instance
Database
File system
Database
File system
18. Typical Architecture
Production
Instance
Database
File system
Triple Tax
Dev, QA, UAT Reporting Backup
Instance
Instance
Instance
Instance
Database
Database
File system
Database
File system
File system
Database
File system
Database
File system
19. Typical Architecture
Production
Instance
Database
File system
Instance
Instance
Instance
Instance
Database
Database
File system
Database
File system
File system
Database
File system
Database
File system
20. Data floods infrastructure
92% of the cost of business,
in financial services business , is “data”
www.wsta.org/resources/industry-articles
Most companies have
2-9% IT spending , ½ on “data”
http://uclue.com/?xq=1133
21. In this presentation :
• Data Constraint
I. strains IT
II. price is huge
III. companies unaware
• Solution
• Use Cases
22. price is Huge
Four Areas data tax hits
– IT Capital resources $
– IT Operations personnel $
– Application Development $$$
– Business $$$$$$$
25. $ IT Operations
• People
– DBAs
– SYS Admin
– Storage Admin
– Backup Admin
– Network Admin
• Hours : 1000s just for DBAs
• $100s Millions for data center modernizations
26. $ Application Development
• Inefficient QA: Higher costs of QA
• QA Delays : Greater re-work of code
• Sharing DB Environments : Bottlenecks
• Using DB Subsets: More bugs in Prod
• Slow Environment Builds: Delays
27. $ Business
Ability to capture revenue
• Business Applications
– Delays cause lost revenue
• Business Intelligence
– Old data = less intelligence
28. In this presentation :
• Data Constraint
I. strains IT
II. price is huge
III. companies unaware
• Solution
• Use Cases
36. Technology Core : file system snapshots
• EMC
– 16 snapshots on Symmetrix
– Write performance impact
– No snapshots of snapshots
• Netapp
– 255 snapshots
• ZFS
– Compression
– Unlimited snapshots
– Snapshots of Snapshots
• DxFS
– “”
– Storage agnostic
– Shared cache in memory
Also check out new SSD storage such as:
Pure Storage, EMC XtremIO
37. Fuel not equal car
Challenges
1. Technical
2. Bureaucracy
38. Bureaucracy
Developer Asks for DB Get Access
Manager approves
DBA Request
system
Setup DB
System
Admin
Request
storage
Setup
machine
Storage
Admin
Allocate
storage
(take snapshot)
39. 1hour
9 days
1 day
Why are hand offs so expensive?
Bureaucracy
40. Technical Challenge
Production Filer
Database
Luns
Target A
Target B
Target C
snapshot
clones
InsIntsatannccee
InInssttaanncece
InInssttaannccee
InInssttaannccee
Instance
Source
41. Development Filer
Production Filer clones
Database
LUNs
snapshot
Technical Challenge
Instance
Target A
InInssttaannccee
Target B
InInssttaanncece
Target C
InInssttaannccee
Instance
42. Technical Challenge
Production
Copy
Time Flow
Purge
Storage Development
File System Instance
1 2 3
Clone (snapshot)
Compress
Share Cache
Provision
Mount, recover, rename
Self Service, Roles & Security
Instance
43. How to get a Data Virtualization?
2 1
– EMC + SRDF
– Netapp 2 + SMO
1
– Oracle EM 12c + data guard + Netapp /ZFS
– Delphix
3 1 2
Source
sync
Deploy
automation
Storage
snapshots
1 2 3
44. Goal : virtualize, govern, deliver
• Security
• Masking
• Chain of custody
• Self Service
• Roles
• Restrictions
• Developer
• Data Versioning
• Refresh, Rollback
• Audit:
Data Supply Chain
Data Virtualization
Thin Cloning
• Live Archive Snap Shots
10/3/2014 44
46. Allocate Any Storage to Delphix
Allocate Storage
Any type
Pure Storage + Delphix
Better Performance for
1/10 the cost
47. One time backup of source database
Production
InsIIntnsasttanannccceee
Database
File system
48. DxFS (Delphix) Compress Data
Production
InsIIntnsasttanannccceee
Database
Data is
compressed
typically 1/3
size
File system
49. Incremental forever change collection
Production
Database
File system
Changes
Time Window
• Collected incrementally forever
• Old data purged
InsIIntnsasttanannccceee
58. Before Virtual Data
Production Dev, QA, UAT
Instance
Reporting Backup
Database
File system
Instance
Instance
Instance
Instance
Database
Database
File system
Database
File system
File system
Database
File system
Database
File system
“triple data
tax”
59. With Virtual Data
Production
Instance
Dev & QA
Instance
InInssttaannccee
InInssttaannccee
Database
Reporting
Instance
Database
Backup
Database
Instance Instance Instance
Database
Database
Database
File system
Data
Virtualization
Appliance
72. QA : Virtual Data
• Fast
• Parallel
• Rollback
• A/B testing
73. QA : Long Build times
QA Build QA
96% of QA time was building environment
$.04/$1.00 actual testing vs. setup
QA Build QA
X Bug
70
60
50
40
30
20
10
0
1 2 3 4 5 6 7
Delay in Fixing the bug
Cost
To
Correct
Software Engineering Economics – Barry Boehm (1981)
74. Dev
QA
QA Virtual Data : Fast
Prod
Instance
DVA
Time Flow
• Low Resource
• Find bugs Fast
75. QA with Virtual Data: Rewind
Instance
Development
Instance
Prod
76. QA with Virtual Data: A/B
Instance
Instance
Instance
Index 1
Index 2
77. Data Version Control
Dev
QA
2.1
Dev
QA
2.2
2.1 2.2
Prod
Instance
DVA
10/3/2014 77
99. Use Case Summary
1. Development & QA
2. Production Support
3. Business
100. How expensive is the Data Constraint?
DVA at Fortune 500 :
Dev throughput increase by 2x
101. How expensive is the Data Constraint?
• Faster Financial Close
• Faster BI refreshes
• Faster surgical recovery
• More Project tracks
• Faster Projects
102. Virtual Data Quotes
• Projects “12 months to 6 months.”
– New York Life
• Insurance product “about 50 days ... to about 23 days”
– Presbyterian Health
• “Can't imagine working without it”
– State of California
103.
104. Summary
• Problem: Data is the constraint
• Solution: Virtualize Data
• Results:
• Half the time for projects
• Higher quality
• Increase revenue
105. Oaktable World & hands on labs
105
We are
here
Oaktable
World
Moscone
South
120. 1 Netapp
NetApp Filer - Production NetApp Filer - Development
Database
Luns
Snap
mirror
Snapshot Manager
for Oracle
Flexclone
Repository
Database
Snap
Drive
Protection
Manage
Production
Development
Target A
InInssttaannccee
Target B
InInssttaanncece
Target C
InInssttaannccee
Instance
121. Where we want to be
Production
Instance
Instance Instance Instance Instance
Database
File system
Development
Instance
Database
QA
Instance
Database
UAT
Instance
Database
Snapshots
122. EM 12c: Snap Clone
Production Development
Flexclone Flexclone
Netapp
Snap Manager for Oracle
127. III. Data Constraint companies unaware
Don’t we already do that ?
Why do I need an iPhone ?
SQL scripts
Alter database begin backup
Back up datafiles
Redo
Archive
Alter database end backup
RMAN
128.
129. Merge to dev1 Dev1
Dev2
Trunk
DB
VC
Fork
Fork
Fork
Fork
DBmaestro