Ginkgo Bioworks, A Leading Biotech Company, Migrates to Atlassian Cloud

When internal resources are scarce and the upkeep of mission-critical applications becomes more of a cumbersome task that increases risk instead of reducing it, it's time to call in a professional. And that is exactly what our client Ginkgo Bioworks, an industry-leading biotech company that specializes in genetic engineering, decided to do. 

With upcoming initiatives and heavy business implications that were highly dependent on throughput, our client had an imperative need to move their current instances of Jira Software and Confluence to Atlassian's cloud offering. 

By completing the migration, our client would address the lingering issues revolving around their server versions of the aforementioned applications which were at end of life support (EOL), consistently experiencing major downtime, lacking dedicated resources to maintain the instance in terms of governance administration, and lacking experience with tool configuration as it was previously siloed to one of their many subsidiaries.

Before our Delivery Team started the migration, they learned through discovery that there were certain data points and transfers to be considered that involved apps. Some of these apps provided a straight migration path, while others would require the extraction of data to aggregate then migrate to the cloud. This extra step would cause a lot of manual effort which was accounted for during the planning, discovery, and design phase of the project.

Access to Ginkgo's environment would prove to be a challenge as the security and risk management approval for additional assets (in this case laptops) would need to be shipped to our team in order for us to administer the project.

The migration project was initially slated for 6 weeks to include 2 applications, Jira and Confluence, along with several apps. We were also positioned and prepped to assist with the automation and customization of workflows and issues within Jira.

Through much R&D (Research and Development) by Atlassian along with the Cloud Migration Assistant, migration paths to the cloud have become less ambiguous and difficult due to the improvement of process design and proactive support. This tool would also prove invaluable as it helped with the extraction/transition of users without disruption and spamming updates to their personal email accounts.

Our team communicated and worked closely with a few different groups, including the Database, Engineering, Access Management, DevOps, and ITSM teams. There was also constant collaboration with dedicated stakeholders within the organization for quality assurance, feedback loops, and course-correcting. 

During the project and specifically, towards the end of it, our team experienced some turbulence when it came to Atlassian Access SSO user provisioning and how it related to configuring with Ginkgo's existing Okta deployment, which extended the project for an additional week. Although this was a challenge, our Atlassian Cloud Migration engagements are generally structured in a way to account for any unforeseeable challenges that may arise.

After a total of 7 weeks, our team successfully migrated Jira and Confluence applications which included 78 projects, 700 users, 73 groups, and 125 spaces for our client, respectively. Gingko Bioworks was extremely grateful for the close attention to detail provided by our team and has transitioned to ongoing application front-end support through our Modern Service Management program.

Cloud migration isn't the end of this story, and it shouldn't be the end of yours, either. Once you've migrated, it's time to invest in connected data and real-time dashboards that help your teams stay on top of strategy and execution. Check out the tl;dr on enterprise intelligence in the cloud!

RELATED: Learn more about Ginkgo Bioworks' cloud success story in our on-demand webinar with AWS