Migrating to Jira Service Management: Challenges and Best Practices

Why Migrating to Jira Service Management Is More Than a Data Import

Organizations modernizing their IT Service Management (ITSM) landscape increasingly choose Jira Service Management (JSM) as their strategic platform. Whether the source system is USU Service Management (USM), Redmine, ServiceNow, Matrix42, Ivanti, BMC Remedy, or another ITSM solution, one challenge remains the same: migrating large volumes of tickets and their associated data without disrupting business operations.

At first glance, ticket migration may appear straightforward. Export data from one system, import it into another, and continue working. In reality, successful ITSM migration projects are significantly more complex. Tickets are only one part of the story. Organizations must also preserve comments, attachments, workflows, user references, asset relationships, ticket links, and historical context.

Migrating service management platforms is often a once-in-a-decade initiative. Getting it right requires careful planning, a clear migration strategy, and tooling capable of handling both technical and business requirements.

Why ITSM Migrations Are More Complex Than Expected

Most ITSM platforms have evolved over many years. During that time, organizations customize workflows, add fields, integrate CMDBs, define approval processes, and accumulate vast amounts of historical ticket data.

A migration project typically needs to addressTicket records and metadata

• Comments and communication history

• Attachments and embedded images

• User references and reporter information

• Asset and configuration item relationships

• Ticket links and dependencies

• Workflow states and transitions

• Custom fields and business-specific data structures

When migrating from systems such as USM, Redmine, ServiceNow, or other enterprise ITSM platforms, these elements often require mapping and transformation before they can be imported into Jira Service Management.

The Challenge of Scale

Migration projects often begin with an estimate of a few thousand tickets, only to discover significantly larger datasets during analysis.

In enterprise environments it is not uncommon to encounter:

• Tens of thousands of tickets

• Hundreds of thousands of comments

• Large attachment repositories

• Complex relationships between tickets and assets

The volume itself is not necessarily the biggest challenge. The real difficulty lies in moving large amounts of data within acceptable project timelines while preserving data quality and traceability.

For example:

• Comments often require individual processing.

• Attachments are uploaded separately from issues.

• Rich text content must be converted into Atlassian-supported formats.

• Embedded images frequently require extraction, upload, and reference remapping.

• API rate limits must be respected to avoid throttling.

Without a dedicated migration strategy, even technically successful migrations can take far longer than expected.

USM to Jira Service Management Migration

One of the most common migration scenarios is moving from USU Service Management (USM) to Jira Service Management.

USM environments frequently contain:

• Incident tickets

• Service requests

• Change records

• Asset and configuration item relationships

• Extensive ticket histories

• Custom workflows and business processes

A successful migration requires more than simply moving tickets. Organizations typically want to preserve:

• Original ticket references

• Ticket descriptions and communication history

• Attachments

• User relationships

• Asset references

• Auditability and traceability

In many cases, maintaining mappings between the original USM identifiers and the newly created Jira issues is essential for compliance, reporting, and future audits.

For organizations already using integrations between USM and Jira, existing connectivity can significantly simplify migration projects. The USU Service Management Connector for Jira can serve as a foundation for migration workflows, helping transfer ticket data, maintain references between systems, and support migration tracking. While large-scale migrations typically require additional transformation and orchestration logic, leveraging an existing integration layer can substantially reduce implementation effort and risk.

The Real Challenge: Migration Speed and Cutover Time

Field mapping, workflow mapping, and data transformation are important parts of every migration project. However, in large-scale ITSM migrations, they are rarely the biggest risk.

The real challenge is often the amount of time required to move the data.

A modern service desk environment can contain tens of thousands of tickets, hundreds of thousands of comments, and large volumes of attachments. While mapping rules can usually be defined and tested in advance, the actual transfer of data is constrained by API limits, processing overhead, and the complexity of preserving ticket history.

This becomes particularly important when migrating to Jira Cloud, where tickets, comments, attachments, and related objects are frequently processed separately. As the volume of data grows, migration duration can increase significantly.

The impact is most visible during the migration of active tickets.

Historical vs. Active Tickets

Historical or closed tickets can often be migrated gradually over several days or weeks before the final go-live. Since these tickets are no longer actively changing, they can be transferred in batches without affecting day-to-day operations.

Open tickets are different.

At some point, users must stop working in the legacy system and start working exclusively in Jira Service Management. To achieve this, all active tickets need to be migrated within a defined maintenance window and validated before users can access the new platform.

This creates a critical requirement:

The migration of active tickets must be completed quickly enough to support a clean cutover from the old system to Jira Service Management.

If the migration takes too long, organizations face difficult choices:

• Extend the maintenance window

• Freeze changes in the source system for an extended period

• Accept incomplete data during go-live

• Introduce complex synchronization mechanisms between systems

For this reason, migration performance and throughput are often more important than field mapping itself.

Optimizing Migration by Reducing Data Volume

When discussing migration performance, the first instinct is often to look for technical optimizations. However, one of the most effective ways to reduce migration duration is to reduce the amount of data that needs to be transferred.

Not every piece of historical information provides the same business value.

Many ITSM environments contain years of automatically generated content, duplicated information, status updates, notification logs, and other records that may no longer be relevant for day-to-day operations after the migration.

Before migrating large datasets, organizations should evaluate which information is truly needed in the target system.

Examples include:

• Automatically generated status updates

• Notification and email processing logs

• System-generated comments

• Duplicate information stored in multiple locations

• Historical data with little operational relevance

In some cases, multiple comments can be consolidated into a single summary entry that preserves the important context while significantly reducing the number of records that must be migrated.

Organizations may also decide to apply different migration fidelity levels depending on the ticket type or age. For example:

• Active tickets may require complete history, attachments, and detailed comments.

• Recently closed tickets may require simplified comment history.

• Older tickets may only require key information and attachments.

• Archived tickets may be retained in the source system for compliance purposes and not migrated at all.

Reducing data volume not only shortens migration duration but can also simplify validation, lower migration risk, and help ensure that active tickets can be transferred within the available maintenance window.

Comments, Attachments, and Rich Content

One of the biggest underestimations in migration projects is the effort required to move ticket history.

A ticket rarely consists of just a summary and description.

It often contains:

• Dozens of comments

• Screenshots

• Log files

• Documents

• Embedded images

• Email conversations

Rich text content must frequently be transformed into Atlassian’s document format while preserving readability.

Special handling is often required for:

• Embedded screenshots

• Inline images

• Legacy HTML formatting

• Proprietary formatting standards

This is where generic CSV imports typically reach their limits.

Why Standard Import Tools Are Not Always Enough

Organizations often ask whether Jira’s native import mechanisms are sufficient.

For simple datasets, the answer may be yes.

However, large-scale enterprise migrations typically require more advanced capabilities.

Common limitations of standard import approaches include:

• Limited attachment handling

• No preservation of complex ticket histories

• Difficulties with embedded images

• Limited support for asset relationships

• Incomplete handling of custom objects

• Reduced traceability during migration retries

This is why many enterprise migrations require dedicated migration tooling and automation.

The Importance of Staging and Validation

One of the most effective approaches is introducing a staging layer between the source system and Jira.

A staging process enables:

• Data validation

• Data transformation

• Progress tracking

• Error handling

• Safe restart capabilities

• Incremental migration execution

Rather than moving data directly from the source system into Jira, the migration pipeline can verify and prepare information before import.

This significantly reduces risk during production migration.

Migration in Phases

A phased migration approach is often the safest strategy.

Phase 1 – Historical Data

Historical and closed tickets can be migrated in advance.

Benefits include:

• Reduced cutover pressure

• Earlier validation opportunities

• Performance testing

• Process optimization

Because these tickets are no longer changing, they can be migrated over a longer period without affecting business operations.

They also provide an opportunity to optimize the migration scope. Organizations can review which comments, attachments, and historical records truly need to be preserved in Jira Service Management and which can be summarized, consolidated, or excluded from the migration.

Phase 2 – Active Tickets

Open and actively changing tickets are migrated during a controlled maintenance window.

This phase is typically the most critical part of the project because users must stop working in the legacy system and switch to Jira Service Management once the migration is completed.

Key objectives include:

• Migrating all active tickets and their required history

• Preserving operationally relevant attachments and comments

• Verifying that agents can continue their work in Jira Service Management

• Completing the migration within the agreed maintenance window

• Performing a controlled production cutover

The primary success criterion is not the migration itself, but the ability of service desk teams to start working in Jira Service Management immediately after the cutover without losing access to the information they need.

Separating historical and active data dramatically reduces operational risk and minimizes downtime.

Performance and Reliability Matter

Large migrations are not only about moving data.

They must also be:

• Reliable

• Repeatable

• Auditable

• Recoverable

A professional migration framework should include:

• Checkpointing

• Retry mechanisms

• ID mapping

• Progress monitoring

• Error logging

• Validation reporting

This ensures that interrupted migrations can continue without creating duplicates or inconsistencies.

Beyond USM: Redmine and Other ITSM Platforms

Although USM is a common migration source, the same principles apply to many other platforms, including:

• Redmine

• ServiceNow

• Matrix42

• Ivanti

• BMC Remedy

• Zendesk

• Freshservice

• Custom ticketing solutions

Each platform introduces its own technical challenges, but the core migration concerns remain the same:

• Data quality

• Relationship preservation

• Migration performance

• Downtime minimization

• Attachments and comments

• Operational continuity

Our Approach

Every migration project is different, but the underlying challenges are often similar. We understand these challenges and have developed practical approaches to address them.

Our approach focuses on:

• Early technical validation through migration proof-of-concepts

• Detailed data analysis and mapping workshops

• Automated transformation and migration processes

• Staging environments and checkpoint-based execution

• Performance optimization for large datasets

• Intelligent reduction of non-essential migration data

• Incremental and phased migration strategies

• Full traceability and auditability throughout the migration lifecycle

For USM environments, this can include leveraging and extending the USU Service Management Connector for Jira as a foundation for migration workflows, status tracking, data mapping, and synchronization between systems.

These practices help reduce migration risks and provide visibility into progress, data quality, and potential issues before production cutover.

Conclusion

Migrating to Jira Service Management is much more than importing tickets. The real challenge lies in balancing data fidelity, migration duration, and operational continuity.

Whether the source system is USU Service Management (USM), Redmine, ServiceNow, or another ITSM platform, successful migrations require careful planning, appropriate tooling, and a deep understanding of both the source and target platforms.

Preserving business context and historical information is important, but the ability to migrate active tickets within an acceptable maintenance window is often the key factor that determines the success of the project.

Organizations that invest in a structured migration strategy can significantly reduce risk, accelerate adoption of Jira Service Management, and ensure that years of valuable service history remain accessible and usable in their new platform.

Planning a Migration to Jira Service Management?

Every migration project is unique. The size of the dataset, the number of active tickets, attachment volumes, workflow complexity, and acceptable downtime all influence the migration strategy.

If you are considering a migration from USU Service Management, Redmine, ServiceNow, or another ITSM platform, we would be happy to discuss your requirements and help you identify the most suitable approach.

Schedule a call with our team to discuss your migration project.