How Atlassian Partners Ensure the Success of a Data Migration Plan

17 October 2018 | Articles, Atlassian

Data migration is a complicated process – and if it goes wrong, it can have serious repercussions for a business. A data migration that fails can result in the disruption of services to the end user; application instability, semantic errors, or user interference which can disrupt business processes.

However, the most serious risk in a data migration is in the preservation of the data itself. A poorly-executed data migration may result in the loss or corruption of critical business data, or the loss of customer data. Data loss can have serious consequences for a business – one study found that 94% of companies that suffer a catastrophic data loss do not survive, with 43% never reopening and 51% closing within two years.

Related: Implement Best Practices for Successful Jira Data Migration — Download the eBook

To ensure that data migrations are successful, it is vital to have a data migration plan in place. A proper data migration plan not only includes actually moving data from one location to the next, it also provides for the initial assessments and testing prior to the transfer as well as monitoring after execution.

Data migration may be necessary under a variety of circumstances. Perhaps your organization is conducting a storage migration, moving data blocks from one type of hardware to another. Perhaps an application is moving to a new hosting environment or changing over legacy tools to Atlassian tools.

Most frequently today, as cloud adoption grows, companies find themselves conducting large-scale migrations of data and applications from on-premise servers to a cloud environment. The process of conducting a data migration may seem overwhelming to a business that has little experience in large-scale migrations.

Download the Jira Migration Steps Case Study

To ensure the success of a data migration plan, the company should:

  1. Conduct a ‘health check’ on the receiving infrastructure

It is important to ensure that the infrastructure where the data will be located is robust, and ready to support the data and processes that will be routed to it after the migration. This includes ensuring that the new infrastructure can support an increased number of users, issues, projects, workflows, with all of the permissions and security schemes involved to ensure it works.

  1. Check versions/plugins

At this time, ensure that all software versions are the same, to eliminate the potential for data incompatibility or semantics errors. It can also be extremely helpful to locate a plugin or API that facilitates the import/export of selected data during a migration.

  1. Testing

It is vital to conduct a series of comprehensive tests, including data collision analysis, as well as testing for data accuracy, completeness, compliance and corruption. Testing must be conducted prior to the actual migration in order to correct any issues that may arise and preserve the sanctity of critical data.

Part of testing is finding the errors in the migration plan, correcting them, and re-testing. This could include looking for data translation errors, or differences in user directories, user names, and credential patterns.

  1. Execute migration to a ‘maneuver environment’

A maneuver environment is an intermediary environment, consisting of a full copy of the source environment populated with source data. Data can, however, be manipulated in the maneuver environment, offering a space where data can be changed as necessary to merge correctly to the receiving environment.

Once the pre-migration preparation and testing is conducted, all data should be backed up thoroughly in anticipation of the executed migration.

  1. Document and communicate the migration plan

Having a migration plan in place before moving forward with any data migrations is key. This document is a good timeline indicator and provides an estimate of expected downtime for production. It should document all of the actions that are required to perform the migration, along with assigning responsibility for specific tasks to specific teams or individuals, for purposes of accountability. A roll-back plan should be included in case of failure of the data migration.

  1. Execute migration

Once stakeholders are clear on the migration plan and their own responsibilities for ensuring the success of the plan, a date can be set for executing the data migration.

  1. Decommission and monitor

Once a migration has been completed successfully, the original source environment should be decommissioned, and the new environment should be monitored carefully on an ongoing basis to ensure continued success.

In conducting a data migration, it is important to include comprehensive backups and roll-back plans, just in case something goes wrong. A loss or corruption of data during a migration can have serious consequences for the enterprise as a whole. However, the risk of problems during a data migration can be minimized by following a structured process that includes analysis, planning, testing, re-testing, and monitoring the migration for success.

e-Core, as a seasoned Atlassian partner, has the knowledge and experience to help an organization make the best decisions to reduce the risks associated with data migration and consolidation of instances projects.

Looking for tools, tips, and the necessary steps for your Jira data migration to be a success? Download Jira Data Migration: Use Cases and Best Practices guide:

Download the Jira Use Cases eBook

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