How do you coordinate the work of thousands of users, balance the need for teams to innovate, optimize performance, and comply with reporting standards and industry regulations? At Johnson & Johnson we were faced with such a challenge. With 15 Atlassian application instances and tens of thousands of users, we needed to find a viable way to manage applications and our users efficiently. Come hear about our journey—the challenges, best practices, lessons learned, and ROI during one of the largest data transformation migrations we've ever embarked on.

1. MARC GIDWANI | IT DIRECTOR | JOHNSON & JOHNSON
A Journey to Enterprise Agility
Migrating 15 Atlassian Instances to the Data Center

2. Agenda
Challenges
Solution
Consolidation & data transformation
Initiative breakdown
Benefits
Governance & maintenance

3. Agenda
Challenges
Solution
Consolidation & data transformation
Initiative breakdown
Benefits
Governance & maintenance

4. Agenda
Challenges
Solution
Consolidation & data transformation
Initiative breakdown
Benefits
Governance & maintenance

5. Agenda
Challenges
Solution
Consolidation & data transformation
Initiative breakdown
Benefits
Governance & maintenance

6. Agenda
Challenges
Solution
Consolidation & data transformation
Initiative breakdown
Benefits
Governance & maintenance

7. Agenda
Challenges
Solution
Consolidation & data transformation
Initiative breakdown
Benefits
Governance & maintenance

8. Bridging the gap between bottom-up
agility and top-down enterprise
governance
THE CHALLENGES OF ENTERPRISE AGILITY

9. Managing 15
Atlassian application
instances – Jira,
Confluence &
Bitbucket
THE CHALLENGES OF ENTERPRISE AGILITY

10. Our major challenges
Total Cost of Ownership
Owning multiple application
instances in an enterprise
setting has numerous costs
attached to it
Processes consistency
Multiple instances =
inconsistency in processes,
workflow implementations,
and third-party apps
Regulatory compliance
Implementing the strict QSC
rules across 15 instances is a
daunting and expensive
undertaking.

11. Data Center Deployment
Consolidating 15 servers into a centrally-administered
enterprise instance
SOLUTION

12. The benefits of Data Center for enterprises
Scalability
High availability, zero
downtime & no
additional licensing
fees.
Performance
Consistent
performance & user
experience at scale.
Flexibility
Minimal infrastructure
configurations & costs
with AWS.
Security
Offsite Disaster
Recovery in the event
of a system outage.

13. Consolidation &
data transformation

14. Phases
Roles &
Responsibilities
Best practices
Phases
• Phase I: Data gathering & specifications
• Phase II: Data transformation
• Phase III: Development
• Phase IV: Staging
• Phase V: Production
Process
overview

15. Phases
Roles &
Responsibilities
Best practices
Roles & Responsibilities
• Primary team: Johnson & Johnson IT
Team
• Migration team: Botron Software
(Platinum Solution Partner)
• Source System owners
• Quality & Compliance
• Atlassian TAM
• Atlassian Premier Support
Process
overview

16. Phases
Roles &
Responsibilities
Best practices
Best practices
• Rigorously analyze & qualify
your Source & Target data
• Define Data Center parameters
for the number of custom fields,
3rd party apps, etc. on the Target
instance
• Evaluate the value of custom
fields & third-party add-ons
Process
overview

17. Consolidation & migration
Breakdown of the phases of the initiative
INITIATIVE BREAKDOWN

18. Phase I: Data Gathering &
Specifications

19. • Requirements for enterprise Target instance
• AMS (Application Migration Specifications)
• Data gathering & specifications for better clarity into the
complexity of the future consolidation & migration
PHASE I: DATA GATHERING & SPECIFICATIONS

20. • Defining parameters for Data Center Target
instance (e.g. custom fields, enterprise
security model etc.)
• Daily stand-ups with Source System
owners
• Alignment of criteria during AMS creation &
decision-making
PHASE I: ALIGNMENT BETWEEN SOURCE & TARGET INSTANCE

21. Phase I: Initial data gathering & specifications
Potential conflicts Source/Target
Heavy workflow customizations,
conflicting project keys, custom fields,
etc.
3rd party apps
Analysis of the 3rd party apps of each
Source system
Security & User management
Define Target Security model, and
analyze users, their permissions,
access rights & ownership.
Integrations
Analysis & integration of Atlassian
applications (Jira, Confluence,
Bitbucket)

22. Phase II: Data transformation
Transforming data based on the pre-defined Data Center governance
parameters

23. Custom fields of Source instances
Hundreds of custom fields were identified across all
Source instances, impacting the performance &
future maintenance of Target
Requirements for Target instance
Qualify the value of the custom fields & reduce their
numbers
The solution?
Implementing only verified custom fields, while
preserving the value of the rest in a text field for
future reference & historic value. Implement strict
governance rules

24. Custom fields of Source instances
Hundreds of custom fields were identified across all
Source instances, impacting the performance &
future maintenance of Target
Requirements for Target instance
Qualify the value of the custom fields & reduce their
numbers
The solution?
Implementing only verified custom fields, while
preserving the value of the rest in a text field for
future reference & historic value. Implement strict
governance rules

25. Custom fields of Source instances
Hundreds of custom fields were identified across all
Source instances, impacting the performance &
future maintenance of Target
Requirements for Target instance
Qualify the value of the custom fields & reduce their
numbers
The solution?
Implementing only verified custom fields, while
preserving the value of the rest in a text field for
future reference & historic value. Implement strict
governance rules

26. User Permissions / Security model
Different teams were using different permission
models – e.g. groups, roles.
Requirements for Target instance
A fixed security model based on groups and models
for each project
The solution?
Analysis & mapping of the permissions models on
both systems to ensure all users will align with the
Target model, while retaining their access rights

27. User Permissions / Security model
Different teams were using different permission
models – e.g. groups, roles.
Requirements for Target instance
A fixed security model based on groups and models
for each project
The solution?
Analysis & mapping of the permissions models on
both systems to ensure all users will align with the
Target model, while retaining their access rights

28. User Permissions / Security model
Different teams were using different permission
models – e.g. groups, roles.
Requirements for Target instance
A fixed security model based on groups and models
for each project
The solution?
Analysis & mapping of the permissions models on
both systems to ensure all users will align with the
Target model, while retaining their access rights

29. 3rd party apps across Source instances
Countless 3rd party apps across all Source instances,
multiple conflicts in data & configurations
Requirements for Target instance
A manageable number of 3rd party apps with
verified value for the Data Center instance
The solution?
Rigorous analysis of the value of each app to ensure
that only a selected number of apps will be
migrated to the Data Center

30. 3rd party apps across Source instances
Countless 3rd party apps across all Source instances,
multiple conflicts in data & configurations
Requirements for Target instance
A manageable number of 3rd party apps with
verified value for the Data Center instance
The solution?
Rigorous analysis of the value of each app to ensure
that only a selected number of apps will be
migrated to the Data Center

31. 3rd party apps across Source instances
Countless 3rd party apps across all Source instances,
multiple conflicts in data & configurations
Requirements for Target instance
A manageable number of 3rd party apps with
verified value for the Data Center instance
The solution?
Rigorous analysis of the value of each app to ensure
that only a selected number of apps will be
migrated to the Data Center

32. Phase III: Development
Generating a Migration Execution Plan as a final deliverable of this phase

33. Phase III: Development
Environment preparation
Set up a staging environment using the
same OS, application, database, etc.
Execution
A series of sandbox migrations to verify
all the components are functioning
properly
Testing
A number of tests to identify changes
that need to be made to the testing
framework, so it can properly work in
the target environment
Tooling
Configuration Manager for Jira,
Custom tools for Confluence &
Bitbucket, REST API

34. Phase IV: Staging
Staging Migration Execution Plan on a clone environment

35. Execution
Migration Execution Plan was
run and all the deliverables
were collected. Timing metrics
of each step of the process
were used for planning the
production migration timeline.
Testing
Tests were performed by
both Botron Software
team and Johnson &
Johnson UAT team
Staging phase

36. Phase V: Production
Identical to the Staging phase, executed against the Target instance

37. • All migration activities were
communicated to Source System users
• Migration to production was executed
during weekend off-hours
• No major post-production issues
encountered
PHASE V: PRODUCTION

38. Standardization
Lower TCO
Reduced admin
team
Lower costs for
infrastructure
Standardization of processes
The data transformation standardized
the processes across teams and
thousands of users, thus ensuring easier
administration and seamless
compliance
Benefits

39. Standardization
Lower TCO
Reduced admin
team
Lower costs for
infrastructure
Lower TCO
The costs associated with licensing
multiple instances was reduced to a
single Data Center license
Benefits

40. Standardization
Lower TCO
Reduced admin
team
Lower costs for
infrastructure
Reduced admin team
The centrally-governed instance helped
reduce the administrative team to 5
people
Benefits

41. Standardization
Lower TCO
Reduced admin
team
Lower costs for
infrastructure
Lower costs for infrastructure
With AWS, the costs associated with
infrastructure were significantly
reduced
Benefits

42. Governance & maintenance
Best practices for Data Center governance & maintenance

43. Custom fields
Workflows
3rd party apps
Incremental
archiving
Contain & control custom fields
Define the optimal number of custom
fields the system will support to avoid
cluttering, performance &
administration bottlenecks.
Best practices

44. Custom fields
Workflows
3rd party apps
Incremental
archiving
Rules for workflows
Ensure workflows are consistent and
accommodate the needs of the users,
while their number is kept to an optimal
minimum.
Best practices

45. Custom fields
Workflows
3rd party apps
Incremental
archiving
Criteria for 3rd party apps
We all love the added value of 3rd party
applications, but an enterprise Data
Center instance needs to be efficient &
manageable. Define criteria for 3rd
party apps & keep them at an optimal
number.
Best practices

46. Custom fields
Workflows
3rd party apps
Incremental
archiving
Incremental archiving
An enterprise Data Center instance is
bound to get cluttered. A regular,
incremental archiving initiative where
old issues are archived, yet available for
audit purposes is a compliance must-
have.
Best practices

47. MARC GIDWANI| IT DIRECTOR| JOHNSON & JOHNSON |
Thank you!