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T11	
  
Test	
  Data	
  Management	
  
5/11/17	
  11:15	
  
	
  
	
  
	
  
	
  
	
  
Test	
  Data	
  Management	
  and	
  Its	
  Role	
  in	
  
DevOps	
  
	
  
Presented	
  by:	
  	
  
	
  
	
   Sunil	
  Sehgal	
  
	
  
TechArcis	
  Solutions,	
  Inc.	
  
	
  
Brought	
  to	
  you	
  by:	
  	
  
	
  	
  
	
  
	
  
	
  
	
  
350	
  Corporate	
  Way,	
  Suite	
  400,	
  Orange	
  Park,	
  FL	
  32073	
  	
  
888-­‐-­‐-­‐268-­‐-­‐-­‐8770	
  ·∙·∙	
  904-­‐-­‐-­‐278-­‐-­‐-­‐0524	
  -­‐	
  info@techwell.com	
  -­‐	
  http://www.starwest.techwell.com/	
  	
  	
  
 
	
  	
  
	
  
Sunil	
  Sehgal	
  
	
  
A	
  regular	
  contributor	
  to	
  StickyMinds.com	
  and	
  other	
  TechWell	
  publications,	
  Sunil	
  
Sehgal	
  is	
  an	
  expert	
  in	
  quality	
  assurance	
  and	
  testing	
  solutions,	
  with	
  a	
  focus	
  on	
  
transformation	
  initiatives	
  that	
  bring	
  year-­‐after-­‐year	
  cost	
  and	
  quality	
  advantages.	
  At	
  
TechArcis,	
  Sunil	
  leads	
  the	
  global	
  strategy,	
  innovation	
  initiatives,	
  and	
  new	
  solutions	
  
for	
  the	
  company.	
  A	
  thought	
  leader	
  in	
  quality	
  engineering	
  and	
  an	
  early	
  adopter	
  of	
  
DevTestOps,	
  Sunil	
  is	
  very	
  active	
  in	
  creating	
  innovative	
  automation	
  solutions	
  for	
  true	
  
implementation	
  of	
  agile	
  and	
  DevOps.	
  His	
  unique	
  business	
  and	
  technology	
  
background	
  -­‐	
  and	
  hands-­‐on	
  experience	
  across	
  a	
  range	
  of	
  business	
  sectors	
  -­‐	
  are	
  
valuable	
  assets	
  for	
  his	
  clients	
  and	
  TechArcis.	
  Reach	
  Sunil	
  at	
  
sunil.sehgal@techarcis.com.	
  
	
  
© TechArcis Confidential and Proprietary
Quality Assurance I Testing Transformation I Outsourcing
11th May’ 2017
Sunil Sehgal
Managing Partner – Global Testing Practice
O: 770-415-4815 x 101
M: 678-361-4357
sunil.sehgal@techarcis.com
Test Data Management and Its Role in DevOps, Continuous
Integration and Delivery
Quality Engineering driven by Innovations and Automation
© TechArcis Confidential and Proprietary
2
Agenda
© TechArcis Confidential and Proprietary
DevOps Movement
Introduction to Continuous Delivery
TDM becomes a pre-requisite to the success of DevOps, CI / CD
Today’s Test Data Challenges
Top considerations for a TDM Approach
Practical Tips to Get Started
The Data Gap
Key Takeaways
References: DevOps Guide, TechWell, Delphix, CA, K2View, Other Industry materials
© TechArcis Confidential and Proprietary
3
Applications & API Economy - Three Factors in Play
© TechArcis Confidential and Proprietary
Testing has to change as well
Dev-test -opsDev-ops
And Dev-test-ops is not possible without Test Automation
“CONTINUOUS”
deployment of Code
and Quality Solutions
“DISRUPTION”
(Technology & Business Models)
DEMAND FOR “AUTOMATION”
• Test Automation
• TDM Automation
© TechArcis Confidential and Proprietary
4
Thriving in “Disruption”
© TechArcis Confidential and Proprietary
Quality and Convenience Drives “Customer Success”
Product Innovation and Development
is Changing
Software Development is also changing and
embracing Automation
Agile and DevOps is the new norm
But, how to drive “Continuous” Quality at
Speed in this Disruption?
© TechArcis Confidential and Proprietary
5
DevOps Movement
© TechArcis Confidential and Proprietary
One of the hallmarks of high performers in any field is that they always “accelerate
from the rest of the herd.” In other words, the best always get better.
© TechArcis Confidential and Proprietary
6
DevTestOps - Understanding “Continuous” terminology
© TechArcis Confidential and Proprietary
Process of delivering software updates to users on a nearly constant basis.
Code can be rapidly and safely deployed to production by delivering every
change to a production-like environment
Continuous deployment is the next step of continuous delivery
Continuous Integration Continuous Integration means the constant integration of changes to an
application at all stages of the delivery chain.
© TechArcis Confidential and Proprietary
7
Understanding “Continuous” paradigm
© TechArcis Confidential and Proprietary
Post
Prod
Tests
Local Dev
Environment
Developer
Branch
CI
Server
QA/
Staging
Environment
Mainline
App Store
and Play
store
CI
Server
Local Dev
Environment
Developer
Branch
QA/
Staging
Environment
Code
Revision
QA
Code
Revision QA
Immediate
Deploy
Detects
Branch
Change
Delivery to
QA/Staging
Detects
PASS
QA
PASS
Merge
to Main
Bad
ReleaseCI Build
FailedQA
FailedCI Build
FailedCode
Review
Failed
Code
Commit
Delivery to
QA/Staging
Code
Commit
© TechArcis Confidential and Proprietary
8
“Test Automation” at speed of Dev
© TechArcis Confidential and Proprietary
User creates
story
Defines
acceptance
criteria
Dev
Test
Dev team codes the
User Story
Apply action and validation
steps in automation
components
Story available for
test
Mapping script with code
Run test
FAIL
Report to dev. team
Code Check-in
PASS
Add to sprint suite
Trigger CI
Update result in
JIRA
Discuss Requirements,
Application flow, Test
Points
Example In-Sprint Workflow
1
Day-Zero Test automation for
in-Sprint User stories is the
only way Agile Testing can be
scaled 2
3Always tie test automation
to source code branch that
is being developed.
Test automation consistency
and maintenance is hard to
achieve in real world
© TechArcis Confidential and Proprietary
9
Even organizations with cutting-edge DevOps practices
are finding that standup and reproducibility constraints
still apply to data.
The Data Gap
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
10
1. Industry best practices for TDM
2. What others are doing / challenges faced?
3. TDM Solutions building / Key points to focus on.
We will focus on three important points…..
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
11
Rise of “TDM (automated)”
© TechArcis Confidential and Proprietary
Once viewed as a
back-office function,
Test Data
Management
(TDM) has emerged as
a critical business
enabler for enterprise
agility, security, and
cost efficiency.
Adoption of DevOps
and other
agile methodologies is
giving rise
to New TDM
approaches, tools,
and strategies that
solve data
delivery challenges.
© TechArcis Confidential and Proprietary
12
The Current State of Test Data Management
Who’s responsible for TDM in an organization?
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
13
How long does it take to deliver a test dataset?
Today’s Test Data Challenges
© TechArcis Confidential and Proprietary
It takes 3.5 days and 3.8 people,
on average, to fulfill a request
for a new environment.
At 1 out of every 5 organizations,
it takes over a week.
© TechArcis Confidential and Proprietary
14
What percentage of defects are data-related?
Development teams lack high-fidelity data
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
15
How Organizations manage their Data today – Lets
understand the Four S’s of Test Data Management
© TechArcis Confidential and Proprietary
Sub setting
Strategies
Synthetic Data
Shared Test Data
Environments
Standalone Masking
Solutions
• This emerged to
overcome
limitations in
copying and
moving full,
production-sized
datasets.
• Smaller, more
portable datasets
can serve as
substitutes for
complete ones
but in practice,
Subsets fail to
adequately
embody the
breadth of real
world conditions
• This is an alternative
approach in which
algorithmically
generated test data
substitutes for data
derived from production
sources
• Synthetic data
circumvents the security
issues involved in
distributing “real data”
which contains
potentially sensitive
information but
sometimes fail to cover
all the data
permutations attendant
in production sources
• The inability to
provision dedicated QA
environments to
individual testers leads
to share test datasets
among –projects and
teams.
• Sharing provides
efficiency benefits by
giving multiple teams
immediate, concurrent
access to a common
data environment but
in practice, conflicts
occur when more than
one stakeholder
contends for the same
resources at the same
time
• Need to ensure that
sensitive information
is protected when
delivered to non-
production
environments,
including those used
for testing
• Given the
shortcomings of
synthetic data, as
well as those of
measures including
access control and
encryption, data
masking has become
a de facto standard
for securing test data
© TechArcis Confidential and Proprietary
16
The Issue ? No single technology exists that fulfills
all TDM requirements.
© TechArcis Confidential and Proprietary
• Four solutions typify test data management today: Subsetting, Synthetic Data, Shared
Environments, and Standalone Masking.
• These approaches have reached widespread adoption and are often used in combination
with one another.
© TechArcis Confidential and Proprietary
17
What traditional TDM methods are you using?
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
18
What percentage of testing requirements are met
using subsets?
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
19
Why does your organization use subsets?
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
20
Building a Comprehensive TDM Toolset
© TechArcis Confidential and Proprietary
Teams must……
Build an
Integrated TDM
Solution
That provides
all the Data
Types
Required to
meet a diverse
set of Testing
needs
Successful TDM approach should aim to provide the appropriate types of test data,
weighing the pros and cons of each.
© TechArcis Confidential and Proprietary
21
Various Data Types : Pros and Cons
© TechArcis Confidential and Proprietary
Production Data
provides the most
complete test
coverage
comes at the
expense of agility
and storage costs
For some
applications, it can
also mean
exposing sensitive
data.
ProsCons
Subsets of
Production data
significantly more
agile than full copies
provide some
savings on hardware,
CPU, and licensing
costs
difficult to achieve
sufficient test
coverage
Masked Production
data
makes it possible for
development teams to
use real data without
introducing unsafe levels
of risk
masking processes can
elongate environment
provisioning
masking requires
staging environments
with additional storage
and staff to ensure
referential integrity after
data is transformed
Synthetic data
circumvents security
issues
the space savings are
limited
creating test data is
also prone to human
error and requires an in-
depth understanding of
data relationships
© TechArcis Confidential and Proprietary
22
Top Considerations for a Test Data Management Approach
© TechArcis Confidential and Proprietary
• Automation
• Toolset Integration
• Self Service
Data Delivery:
reducing the time to deliver test
data to a developer or tester
• Data Age
• Data Accuracy
• Data Size
Data Quality :
meeting requirements for high-
fidelity test data
• Complete Solution
• No need for development expertise
• Integrated masking and distribution
Data Security:
minimizing security risks without
compromising speed
• Data consolidation
• Data archiving
• Environment utilization
Infrastructure Costs:
lowering the costs of storing and
archiving test data
© TechArcis Confidential and Proprietary
23
Testing in a traditional scenario vs. with an optimized TDM approach
Taking an Optimized Approach
© TechArcis Confidential and Proprietary
As companies adopt more iterative release methodologies to become more agile, data is
the fastest, easiest way to accelerate test cycles.
A well-orchestrated approach to TDM has the potential to transform the overall
application development process by slashing wait-times for data.
© TechArcis Confidential and Proprietary
24
Incorporating Data Virtualization in TDM
© TechArcis Confidential and Proprietary
• One technology that transforms how
companies manage data for their critical
application projects is data virtualization.
o With data virtualization, teams can mask and
deliver data 100 times faster while using 10
times less space.
• In addition, data virtualization integrates
with existing TDM and DevOps tools to
provide...
o Automated, self-service access to data, enabling
development teams to roll out projects at twice
the speed.
© TechArcis Confidential and Proprietary
25
In order to deliver on the promise of DevOps, CI / CD and hit
continuous release targets for even the largest, most complex and
integrated applications, organizations need solutions…
1. That provide the same flexibility for data as for code bases.
2. The same automation and repeatability for data as for
configurations.
TDM becomes a pre-requisite to the success of
DevOps and CI / CD
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
26
Practical Tips to Get Started
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
27
Better TDM with Data as a Service (Daas):
Bring Quality, Speed, and Security to Test Data
© TechArcis Confidential and Proprietary
• Capturing data—including ongoing changes— in production systems
• Versioning and managing data across the full application lifecycle
• Delivering data to non-production systems, including test environments
DaaS platforms bring the benefits of virtualization to application data by:
• Bookmark and share test data with teammates
• Refresh test data from the latest version production
• Reset test data back to prior point in time
• Branch data for performance and A/B testing
Since DaaS systems capture and version production data over a window of time, testers can:
© TechArcis Confidential and Proprietary
28
DevOps isn’t just about self-sufficiency. It’s also about sophisticated collaboration. Without a
DaaS solution, often data can be the bottleneck to efficient collaboration.
Bookmark and Share
© TechArcis Confidential and Proprietary
With legacy solutions, data is locked with the user instead of traveling with code
With DaaS, free data movement accelerates test-fix cycles.
© TechArcis Confidential and Proprietary
29
With DaaS, test environment setup takes minutes instead of hours, and is the
minority of test cycle time.
Refresh and Reset
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
30
Data branching from production and non-production keeps data and code in sync.
Provision and Branch
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
31
Key Takeaways
© TechArcis Confidential and Proprietary
© TechArcis Confidential and Proprietary
32
Continuous Delivery needs all systems to be fast
© TechArcis Confidential and Proprietary
Developer 1
Developer 2
Developer 3
A System is developed
• Instant
Configuration
• Up-to-date
snapshots of
complex
environments
• Share and use
environments in
parallel
• Powerful cloud,
infrastructure, on
demand
Applications are deployed
in production
• Continuous Deployment
• Environment Management
• Software is fully tested first
time round and defects are
detected.
Testing – Starts immediately,
in parallel
• Gold Copy data covers every test
that needs to be run, including
future and negative scenarios
• It is available instantly, and is
delivered into unlimited, isolated
environments
• It is available across versions and
releases in parallel, and is fully
versioned
• It is absolutely no sensitive
information.
100% 100% 100%
Test Environment Test Data Continuous Code
Deployment
© TechArcis Confidential and Proprietary
33
Continuous Testing with “Automated Test Data”
mirroring the production data
© TechArcis Confidential and Proprietary
Metric
Watch
Local Dev
Environment
Developer
Branch
CI
Server
QA/
Staging
Environment
Mainline
App Store
and Play
store
CI
Server
Local Dev
Environment
Developer
Branch
QA/
Staging
Environment
Code
Revision
QA
Code
Revision QA
Immediate
Deploy
Detects
Branch
Change
Delivery
to Staging
Detects
PASS QA
PASS
Merge
to Main
Bad
ReleaseCI Build
FailedQA Failed
CI Build
FailedCode
Review
Failed
Code
Commit
Delivery
to Staging
Code
Commit
Automated Test Data for
debugging and Unit tests
Automated Test Data for Integration,
Regression and E2E Tests (Production Data)
Automated Test as per
End user conditions
(Production Data)
© TechArcis Confidential and Proprietary
34
Key takeaways
© TechArcis Confidential and Proprietary
2
Automated TDM is key to deliver on the promise of DevOps, CI / CD
and hit continuous release targets
Global teams requires access of TDM infrastructure anytime, anywhere
Agile and DevOps is the new norm
Drive “Continuous” Quality at Speed in this disruption1
3
Teams must build an integrated solution that provides all the data
types required to meet a diverse set of testing needs.
DevOps success depends on effective use of Automated TDM solution
Prod
Better TDM with Data as a Service: Bring Quality, Speed, and Security to Test Data
With DaaS, we can leverage the same capabilities for managing the data that the
code talks to.
4
© TechArcis Confidential and Proprietary
Thank You
Your Trusted Quality Assurance Partner
Quality Assurance I Testing Transformation I Outsourcing
www.techarcis.com
We are a Technology Company with 100%
specialization in QA and Testing

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Test Data Management and Its Role in DevOps

  • 1.                 T11   Test  Data  Management   5/11/17  11:15             Test  Data  Management  and  Its  Role  in   DevOps     Presented  by:         Sunil  Sehgal     TechArcis  Solutions,  Inc.     Brought  to  you  by:                 350  Corporate  Way,  Suite  400,  Orange  Park,  FL  32073     888-­‐-­‐-­‐268-­‐-­‐-­‐8770  ·∙·∙  904-­‐-­‐-­‐278-­‐-­‐-­‐0524  -­‐  info@techwell.com  -­‐  http://www.starwest.techwell.com/      
  • 2.         Sunil  Sehgal     A  regular  contributor  to  StickyMinds.com  and  other  TechWell  publications,  Sunil   Sehgal  is  an  expert  in  quality  assurance  and  testing  solutions,  with  a  focus  on   transformation  initiatives  that  bring  year-­‐after-­‐year  cost  and  quality  advantages.  At   TechArcis,  Sunil  leads  the  global  strategy,  innovation  initiatives,  and  new  solutions   for  the  company.  A  thought  leader  in  quality  engineering  and  an  early  adopter  of   DevTestOps,  Sunil  is  very  active  in  creating  innovative  automation  solutions  for  true   implementation  of  agile  and  DevOps.  His  unique  business  and  technology   background  -­‐  and  hands-­‐on  experience  across  a  range  of  business  sectors  -­‐  are   valuable  assets  for  his  clients  and  TechArcis.  Reach  Sunil  at   sunil.sehgal@techarcis.com.    
  • 3. © TechArcis Confidential and Proprietary Quality Assurance I Testing Transformation I Outsourcing 11th May’ 2017 Sunil Sehgal Managing Partner – Global Testing Practice O: 770-415-4815 x 101 M: 678-361-4357 sunil.sehgal@techarcis.com Test Data Management and Its Role in DevOps, Continuous Integration and Delivery Quality Engineering driven by Innovations and Automation
  • 4. © TechArcis Confidential and Proprietary 2 Agenda © TechArcis Confidential and Proprietary DevOps Movement Introduction to Continuous Delivery TDM becomes a pre-requisite to the success of DevOps, CI / CD Today’s Test Data Challenges Top considerations for a TDM Approach Practical Tips to Get Started The Data Gap Key Takeaways References: DevOps Guide, TechWell, Delphix, CA, K2View, Other Industry materials
  • 5. © TechArcis Confidential and Proprietary 3 Applications & API Economy - Three Factors in Play © TechArcis Confidential and Proprietary Testing has to change as well Dev-test -opsDev-ops And Dev-test-ops is not possible without Test Automation “CONTINUOUS” deployment of Code and Quality Solutions “DISRUPTION” (Technology & Business Models) DEMAND FOR “AUTOMATION” • Test Automation • TDM Automation
  • 6. © TechArcis Confidential and Proprietary 4 Thriving in “Disruption” © TechArcis Confidential and Proprietary Quality and Convenience Drives “Customer Success” Product Innovation and Development is Changing Software Development is also changing and embracing Automation Agile and DevOps is the new norm But, how to drive “Continuous” Quality at Speed in this Disruption?
  • 7. © TechArcis Confidential and Proprietary 5 DevOps Movement © TechArcis Confidential and Proprietary One of the hallmarks of high performers in any field is that they always “accelerate from the rest of the herd.” In other words, the best always get better.
  • 8. © TechArcis Confidential and Proprietary 6 DevTestOps - Understanding “Continuous” terminology © TechArcis Confidential and Proprietary Process of delivering software updates to users on a nearly constant basis. Code can be rapidly and safely deployed to production by delivering every change to a production-like environment Continuous deployment is the next step of continuous delivery Continuous Integration Continuous Integration means the constant integration of changes to an application at all stages of the delivery chain.
  • 9. © TechArcis Confidential and Proprietary 7 Understanding “Continuous” paradigm © TechArcis Confidential and Proprietary Post Prod Tests Local Dev Environment Developer Branch CI Server QA/ Staging Environment Mainline App Store and Play store CI Server Local Dev Environment Developer Branch QA/ Staging Environment Code Revision QA Code Revision QA Immediate Deploy Detects Branch Change Delivery to QA/Staging Detects PASS QA PASS Merge to Main Bad ReleaseCI Build FailedQA FailedCI Build FailedCode Review Failed Code Commit Delivery to QA/Staging Code Commit
  • 10. © TechArcis Confidential and Proprietary 8 “Test Automation” at speed of Dev © TechArcis Confidential and Proprietary User creates story Defines acceptance criteria Dev Test Dev team codes the User Story Apply action and validation steps in automation components Story available for test Mapping script with code Run test FAIL Report to dev. team Code Check-in PASS Add to sprint suite Trigger CI Update result in JIRA Discuss Requirements, Application flow, Test Points Example In-Sprint Workflow 1 Day-Zero Test automation for in-Sprint User stories is the only way Agile Testing can be scaled 2 3Always tie test automation to source code branch that is being developed. Test automation consistency and maintenance is hard to achieve in real world
  • 11. © TechArcis Confidential and Proprietary 9 Even organizations with cutting-edge DevOps practices are finding that standup and reproducibility constraints still apply to data. The Data Gap © TechArcis Confidential and Proprietary
  • 12. © TechArcis Confidential and Proprietary 10 1. Industry best practices for TDM 2. What others are doing / challenges faced? 3. TDM Solutions building / Key points to focus on. We will focus on three important points….. © TechArcis Confidential and Proprietary
  • 13. © TechArcis Confidential and Proprietary 11 Rise of “TDM (automated)” © TechArcis Confidential and Proprietary Once viewed as a back-office function, Test Data Management (TDM) has emerged as a critical business enabler for enterprise agility, security, and cost efficiency. Adoption of DevOps and other agile methodologies is giving rise to New TDM approaches, tools, and strategies that solve data delivery challenges.
  • 14. © TechArcis Confidential and Proprietary 12 The Current State of Test Data Management Who’s responsible for TDM in an organization? © TechArcis Confidential and Proprietary
  • 15. © TechArcis Confidential and Proprietary 13 How long does it take to deliver a test dataset? Today’s Test Data Challenges © TechArcis Confidential and Proprietary It takes 3.5 days and 3.8 people, on average, to fulfill a request for a new environment. At 1 out of every 5 organizations, it takes over a week.
  • 16. © TechArcis Confidential and Proprietary 14 What percentage of defects are data-related? Development teams lack high-fidelity data © TechArcis Confidential and Proprietary
  • 17. © TechArcis Confidential and Proprietary 15 How Organizations manage their Data today – Lets understand the Four S’s of Test Data Management © TechArcis Confidential and Proprietary Sub setting Strategies Synthetic Data Shared Test Data Environments Standalone Masking Solutions • This emerged to overcome limitations in copying and moving full, production-sized datasets. • Smaller, more portable datasets can serve as substitutes for complete ones but in practice, Subsets fail to adequately embody the breadth of real world conditions • This is an alternative approach in which algorithmically generated test data substitutes for data derived from production sources • Synthetic data circumvents the security issues involved in distributing “real data” which contains potentially sensitive information but sometimes fail to cover all the data permutations attendant in production sources • The inability to provision dedicated QA environments to individual testers leads to share test datasets among –projects and teams. • Sharing provides efficiency benefits by giving multiple teams immediate, concurrent access to a common data environment but in practice, conflicts occur when more than one stakeholder contends for the same resources at the same time • Need to ensure that sensitive information is protected when delivered to non- production environments, including those used for testing • Given the shortcomings of synthetic data, as well as those of measures including access control and encryption, data masking has become a de facto standard for securing test data
  • 18. © TechArcis Confidential and Proprietary 16 The Issue ? No single technology exists that fulfills all TDM requirements. © TechArcis Confidential and Proprietary • Four solutions typify test data management today: Subsetting, Synthetic Data, Shared Environments, and Standalone Masking. • These approaches have reached widespread adoption and are often used in combination with one another.
  • 19. © TechArcis Confidential and Proprietary 17 What traditional TDM methods are you using? © TechArcis Confidential and Proprietary
  • 20. © TechArcis Confidential and Proprietary 18 What percentage of testing requirements are met using subsets? © TechArcis Confidential and Proprietary
  • 21. © TechArcis Confidential and Proprietary 19 Why does your organization use subsets? © TechArcis Confidential and Proprietary
  • 22. © TechArcis Confidential and Proprietary 20 Building a Comprehensive TDM Toolset © TechArcis Confidential and Proprietary Teams must…… Build an Integrated TDM Solution That provides all the Data Types Required to meet a diverse set of Testing needs Successful TDM approach should aim to provide the appropriate types of test data, weighing the pros and cons of each.
  • 23. © TechArcis Confidential and Proprietary 21 Various Data Types : Pros and Cons © TechArcis Confidential and Proprietary Production Data provides the most complete test coverage comes at the expense of agility and storage costs For some applications, it can also mean exposing sensitive data. ProsCons Subsets of Production data significantly more agile than full copies provide some savings on hardware, CPU, and licensing costs difficult to achieve sufficient test coverage Masked Production data makes it possible for development teams to use real data without introducing unsafe levels of risk masking processes can elongate environment provisioning masking requires staging environments with additional storage and staff to ensure referential integrity after data is transformed Synthetic data circumvents security issues the space savings are limited creating test data is also prone to human error and requires an in- depth understanding of data relationships
  • 24. © TechArcis Confidential and Proprietary 22 Top Considerations for a Test Data Management Approach © TechArcis Confidential and Proprietary • Automation • Toolset Integration • Self Service Data Delivery: reducing the time to deliver test data to a developer or tester • Data Age • Data Accuracy • Data Size Data Quality : meeting requirements for high- fidelity test data • Complete Solution • No need for development expertise • Integrated masking and distribution Data Security: minimizing security risks without compromising speed • Data consolidation • Data archiving • Environment utilization Infrastructure Costs: lowering the costs of storing and archiving test data
  • 25. © TechArcis Confidential and Proprietary 23 Testing in a traditional scenario vs. with an optimized TDM approach Taking an Optimized Approach © TechArcis Confidential and Proprietary As companies adopt more iterative release methodologies to become more agile, data is the fastest, easiest way to accelerate test cycles. A well-orchestrated approach to TDM has the potential to transform the overall application development process by slashing wait-times for data.
  • 26. © TechArcis Confidential and Proprietary 24 Incorporating Data Virtualization in TDM © TechArcis Confidential and Proprietary • One technology that transforms how companies manage data for their critical application projects is data virtualization. o With data virtualization, teams can mask and deliver data 100 times faster while using 10 times less space. • In addition, data virtualization integrates with existing TDM and DevOps tools to provide... o Automated, self-service access to data, enabling development teams to roll out projects at twice the speed.
  • 27. © TechArcis Confidential and Proprietary 25 In order to deliver on the promise of DevOps, CI / CD and hit continuous release targets for even the largest, most complex and integrated applications, organizations need solutions… 1. That provide the same flexibility for data as for code bases. 2. The same automation and repeatability for data as for configurations. TDM becomes a pre-requisite to the success of DevOps and CI / CD © TechArcis Confidential and Proprietary
  • 28. © TechArcis Confidential and Proprietary 26 Practical Tips to Get Started © TechArcis Confidential and Proprietary
  • 29. © TechArcis Confidential and Proprietary 27 Better TDM with Data as a Service (Daas): Bring Quality, Speed, and Security to Test Data © TechArcis Confidential and Proprietary • Capturing data—including ongoing changes— in production systems • Versioning and managing data across the full application lifecycle • Delivering data to non-production systems, including test environments DaaS platforms bring the benefits of virtualization to application data by: • Bookmark and share test data with teammates • Refresh test data from the latest version production • Reset test data back to prior point in time • Branch data for performance and A/B testing Since DaaS systems capture and version production data over a window of time, testers can:
  • 30. © TechArcis Confidential and Proprietary 28 DevOps isn’t just about self-sufficiency. It’s also about sophisticated collaboration. Without a DaaS solution, often data can be the bottleneck to efficient collaboration. Bookmark and Share © TechArcis Confidential and Proprietary With legacy solutions, data is locked with the user instead of traveling with code With DaaS, free data movement accelerates test-fix cycles.
  • 31. © TechArcis Confidential and Proprietary 29 With DaaS, test environment setup takes minutes instead of hours, and is the minority of test cycle time. Refresh and Reset © TechArcis Confidential and Proprietary
  • 32. © TechArcis Confidential and Proprietary 30 Data branching from production and non-production keeps data and code in sync. Provision and Branch © TechArcis Confidential and Proprietary
  • 33. © TechArcis Confidential and Proprietary 31 Key Takeaways © TechArcis Confidential and Proprietary
  • 34. © TechArcis Confidential and Proprietary 32 Continuous Delivery needs all systems to be fast © TechArcis Confidential and Proprietary Developer 1 Developer 2 Developer 3 A System is developed • Instant Configuration • Up-to-date snapshots of complex environments • Share and use environments in parallel • Powerful cloud, infrastructure, on demand Applications are deployed in production • Continuous Deployment • Environment Management • Software is fully tested first time round and defects are detected. Testing – Starts immediately, in parallel • Gold Copy data covers every test that needs to be run, including future and negative scenarios • It is available instantly, and is delivered into unlimited, isolated environments • It is available across versions and releases in parallel, and is fully versioned • It is absolutely no sensitive information. 100% 100% 100% Test Environment Test Data Continuous Code Deployment
  • 35. © TechArcis Confidential and Proprietary 33 Continuous Testing with “Automated Test Data” mirroring the production data © TechArcis Confidential and Proprietary Metric Watch Local Dev Environment Developer Branch CI Server QA/ Staging Environment Mainline App Store and Play store CI Server Local Dev Environment Developer Branch QA/ Staging Environment Code Revision QA Code Revision QA Immediate Deploy Detects Branch Change Delivery to Staging Detects PASS QA PASS Merge to Main Bad ReleaseCI Build FailedQA Failed CI Build FailedCode Review Failed Code Commit Delivery to Staging Code Commit Automated Test Data for debugging and Unit tests Automated Test Data for Integration, Regression and E2E Tests (Production Data) Automated Test as per End user conditions (Production Data)
  • 36. © TechArcis Confidential and Proprietary 34 Key takeaways © TechArcis Confidential and Proprietary 2 Automated TDM is key to deliver on the promise of DevOps, CI / CD and hit continuous release targets Global teams requires access of TDM infrastructure anytime, anywhere Agile and DevOps is the new norm Drive “Continuous” Quality at Speed in this disruption1 3 Teams must build an integrated solution that provides all the data types required to meet a diverse set of testing needs. DevOps success depends on effective use of Automated TDM solution Prod Better TDM with Data as a Service: Bring Quality, Speed, and Security to Test Data With DaaS, we can leverage the same capabilities for managing the data that the code talks to. 4
  • 37. © TechArcis Confidential and Proprietary Thank You Your Trusted Quality Assurance Partner Quality Assurance I Testing Transformation I Outsourcing www.techarcis.com We are a Technology Company with 100% specialization in QA and Testing