agile development with data virtualization to support devops and continuous deployment

1. Agile Data: Revolutionizing database cloning
1
http://kylehailey.com
kyle@delphix.com
Tim Gorman
tim@delphix.com

2. Are you too busy to Innovate?
Inertia
A new way : Welcome Agile & DevOps!

3. Waterfall, Agile, Devops
• Waterfall
Design Code test Deploy
• Agile
Design Code test Code test Code test Code test Deploy
• Agile with Continuous Deploy
Design
Continuous Deploy requires DevOps

4. What is DevOps = tools + culture
• Culture :
– Bridging silos between Dev & Ops
– Empathy avoid blame
– Collaboration
• Tools :
– Automation VMs, Puppet, Jenkins
– Self-service
– Measurement
4

5. Note: DevOps > Tools + Culture
DevOps Goal= optimizing flow from Dev to Ops to Pro
5
Don’t copy steps. Copy the goal
Goal = company’s bottom line

6. Missed !
Goal
Agile & CI vsWaterfall
Agile & CI Achieved !

7. bugs
time
Missed !
Goal
Agile & CI Achieved !
Bugs

8. profit
time
Missed !
Goal
Agile & CI Achieved !
Profit

9. Missed !
Goal
Cost per Deployment
Agile & CI Achieved !
Cost
Per
Deployment time

10. DevOps and Data : Impossible?
Waterfall
Agile & DevOps
Big Software Release
Small Continuous Releases
DevOps Goal= optimizing flow from Dev to Ops to Pro

11. The Goal : Theory of Constraints
Improvement
not made
at the constraint
is an illusion
factory floor optimization

12. Factory floor

13. Factory floor
constraint
Not a relay race

14. Tune before constraint
constraint
Tuning here
Stock piling

15. Tune after constraint
constraint
Tuning here
Starvation

16. Factory floor : straight forward
constraint
Goal: find constraint
optimize it

17. 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”

18. The Phoenix Project
What is the
constraint
in IT ?

19. 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

20. 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

21. In this presentation :
• Data Constraint
• Solution
• Use Cases

22. • Data Constraint
• Solution
• Use Cases

23. Typical Architecture
Production
Instance
Database
File system

24. Typical Architecture
Production
Instance
Backup
Database
File system
Database
File system

25. Typical Architecture
Production
Instance
Reporting Backup
Database
File system
Instance
Database
File system
Database
File system

26. 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

27. 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

28. moving data is hard
– Storage & Systems
– Personnel
– Time

29. copies take up space
–Servers
–Storage
–Network
–Data center floor space, power, cooling

30. Never enough environments

31. Your Project
Available
Resources

32. Copies require People & Time
• People 1000s hours per year just for DBAs
– DBAs
– SYS Admin
– Storage Admin
– Backup Admin
– Network Admin
• $100s Millions for data center modernizations

33. Data floods infrastructure
92% of the cost of business,
in financial services business , is “data”
www.wsta.org/resources/industry-articles
Most companies average
5% IT spending , ½ on “data”
http://uclue.com/?xq=1133

34. companies unaware

35. companies unaware
Boss, Storage Admin, DBA Developer or Analyst

36. companies unaware
Metrics
– Time
– Old Data
– Storage
Other
– Analysts
–Audits

37. What Problems does Data Constraint Cause
1. Bottlenecks
2. Waiting for environments
3. Waiting to check in code
4. Production Bugs
5. Expensive Slow QA

38. Development : waiting

39. Development : bottlenecks
Frustration Waiting

40. Development : Bugs
Old Unrepresentative Data

41. Development : subsets
False Negatives
False Positives
Bugs in Production

42. Production Wall
42

43. Development : silos

44. QA : Long Build times
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)

45. DevOps : Impossible with databaes?
• Need lots of copies
Design
• Each copy is like

46. In this presentation :
• Data Constraint
• Solution
• Use Cases

47. 99% of blocks are identical
Development QA UAT

48. Solution

49. Thin Clone
Development QA UAT

50. 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

51. Fuel not equal car
Challenges
1. Technical
2. Bureaucracy

52. 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)

53. 1hour
9 days
1 day
Why are hand offs so expensive?
Bureaucracy

54. Technical Challenge
Production Filer
Database
Luns
Target A
Target B
Target C
snapshot
clones
InsIntsatannccee
InInssttaannccee
InInssttaanncece
InInssttaanncece
Instance
Source

55. Development Filer
Production Filer clones
Database
LUNs
snapshot
Technical Challenge
Instance
Target A
InInssttaannccee
Target B
InInssttaannccee
Target C
InInssttaanncece
Instance

56. Technical Challenge
1 2 3
Production
Copy
Time Flow
Purge
Storage Development
File System Instance
Clone (snapshot)
Compress
Share Cache
Provision
Mount, recover, rename
Self Service, Roles & Security
Instance

57. Technical Challenge
Production Storage Development
1 2 3

58. How to get a Data Virtualization?
– ZFS
–EMC 2 + SRDF
1
– Netapp 2 + SMO
1
– Oracle EM 12c + data guard + Netapp /ZFS
– Actifio - hardware
– Delphix - software
3 1 2
Source
sync
Deploy
automation
Storage
snapshots
1 2 3
2
1 2 3
1 2 3

59. Goal : virtualize, govern, deliver
59
• Masking: Masking
• Security: Chain of custody
• Self Service: Logins
• Developer: Versioning , branching
• Audit: Live Archive
Data Supply Chain
Data Virtualization
Thin Cloning
Snap Shots
1 2 3
2 3
2

60. Intel hardware
DB2
Data
File Systems
Binaries
Install Delphix on x86 hardware

61. Allocate Any Storage to Delphix
Allocate Storage
Any type
Pure Storage + Delphix
Better Performance for
1/10 the cost

62. One time backup of source database
Production
InsIIntnsasttanannccceee
Database
File system

63. DxFS (Delphix) Compress Data
Production
InsIIntnsasttanannccceee
Database
Data is
compressed
typically 1/3
size
File system

64. Incremental forever change collection
Production
Database
File system
Changes
• Collected incrementally forever
• Old data purged
InsIIntnsasttanannccceee
Time Flow

65. Snapshot 1 – full backup once only at link time
Jonathan Lewis © 2013
Virtual DB
65 / 30
a b c d e f g h i
We start with a full backup - analogous to a level 0 rman backup. Includes
the archived redo log files needed for recovery. Run in archivelog mode.

66. Snapshot 2 (from SCN)
a b c d e f g h i
b' c'
The "backup from SCN" is analogous to a level 1
incremental backup (which includes the relevant
archived redo logs). Sensible to enable BCT.
Jonathan Lewis © 2013
Delphix executes
standard rman scripts

67. Apply Snapshot 2
a b b' c c' d e f g h i
The Delphix appliance unpacks the rman backup and "overwrites" the
initial backup with the changed blocks - but DxFS makes new copies of
the blocks
Jonathan Lewis © 2013

68. Drop Snapshot 1
a b' c' d e f g h i
The call to rman leaves us with a new level 0 backup, waiting for recovery.
But we can pick the snapshot root block. We have EVERY level 0 backup
Jonathan Lewis © 2013

69. Creating a vDB
a b' c' d e f g h i
The first step in creating a vDB is to take a snapshot of the filesystem as at
the backup you want (then roll it forward)
Jonathan Lewis © 2013
My vDB
(filesystem)
Your vDB
(filesystem)

70. Creating a vDB
a b' c' d e f g h i
The first step in creating a vDB is to take a snapshot of the filesystem as at
the backup you want (then roll it forward)
Jonathan Lewis
© 2013
My vDB
(filesystem)
Your vDB
(filesystem)
aa bb'' cc'' dd ee ff gg hh ii i’

71. Database Virtualization

72. Three Physical Copies
Three Virtual Copies
Data
Virtualization
Appliance

73. 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”

74. 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

75. • Problem in the Industry
• Solution
• Use Cases

76. Use Cases
1. Development and QA
2. Production Support
3. Business

77. Use Cases
1. Development and QA
2. Production Support
3. Business

78. Development: Virtual Data
• Unlimited
• Full size
• Self Service
Development

79. Virtual Data: Easy
Instance
Instance
Instance
Instance
Source
DVA

80. Development Virtual Data: Parallelize
gif by Steve Karam

81. Development Virtual Data: Full size

82. Development Virtual Data: Self Service

83. QA : Virtual Data
• Fast
• Parallel
• Rollback
• A/B testing

84. Dev
QA
QA Virtual Data : Fast
Prod
Instance
DVA
• Low Resource
• Find bugs Fast
Production Time Flow

85. QA with Virtual Data: Rewind
Instance
QA
Prod
Production Time Flow

86. QA with Virtual Data: A/B
Instance
Instance
Instance
Index 1
Index 2
Production Time Flow

87. Data Version Control
Dev
QA
2.1
Dev
QA
2.2
DVA Production Time Flow
2.1 2.2
Prod
Instance
12/3/2014 87

88. Use Cases
1. Development and QA
2. Production Support
3. Business

89. • Backups
• Recovery
• Forensics
• Migration
• Consolidation
Recovery

90. 9TB database 1TB change day
30 day backups storage requirements
90
70
60
50
40
30
20
10
0
week 1
week 2
week 3
week 4
original
Oracle
Delphix

91. Recovery
Source
Instance
Recover VDB
Instance
Drop
DVA Production Time Flow

92. Forensics
Instance
Development
DVA
Source
Production Time Flow

93. Development (the new production)
Instance
Development
DVA
Source
Development
Prod & VDB Time Flow
X

94. Migration

95. Consolidation

96. Use Cases
1. Development and QA
2. Production Support
3. Business Intelligence

97. Business Intelligence
• ETL
• Temporal
• Confidence Testing
• Federated Databases
• Audits

98. Business Intelligence: ETL and DW Refreshes
Prod
Instance
DW & BI
Instance

99. Virtual Data: Fast Refreshes
• Collect only Changes
• Refresh in minutes
Prod
Instance
BI and DW
ETL
24x7
DVA
Production Time Flow

100. Temporal Data

101. Confidence testing

102. Modernization: Federated
Source1
Instance
Source2
Instance
DVA
Production Time Flow 1
Production Time Flow 2

103. Modernization: Federated

104. Modernization: Federated
“I looked like a hero”
Tony Young, CIO Informatica

105. Live Archive
Production Time Flow
Audit
Prod
Instance
DVA
12/3/2014 105

106. Use Case Summary
1. Development & QA
2. Production Support
3. Business

107. How expensive is the Data Constraint?
DVA at Fortune 500 :
Dev throughput increase by 2x

108. How expensive is the Data Constraint?
Faster
• Financial Close
• BI refreshes
• Surgical recovery
• Projects

109. 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

111. Summary
• Problem: Data is the constraint
• Solution: Virtualize Data
• Results:
• Half the time for projects
• Higher quality
• Increase revenue

112. Thank you!
• Kyle Hailey| Oracle ACE and Technical
Evangelist, Delphix
– Kyle@delphix.com
– kylehailey.com
– slideshare.net/khailey