Atlassian Data Center migration plan

This article provides a  high-level process plan for migrating an Atlassian Server application to Data Center.  

The purpose is to provide an overview and potential timelines for project activities before, during, and after the migration process. It covers enlisting personnel, evaluating technology options, and ensuring that the current Server application is ready for migration.

The timelines discussed in this article are based on a number of our customers who have successfully installed Data Center, but it is important to note that the actual timeline will vary based on factors unique to your environment including, but not limited to, environment size, complexity, and preparedness  

A deeper technical discussion into the technology options and installation configurations are out of scope for this article.

 


 

Migrating to Data Center will have an impact on your users' experience and workflows, various stakeholders throughout the organization, and other infrastructure components.  

This timeline shows the phases of a successful implementation. It identifies what to expect throughout each phase and ensures that the implementation front loads as much staffing, planning, and decision-making as possible to manage problems as they arise throughout the process. Customers who follow this process tend to have a more productive and positive experience when deploying to Data Center.

A Data Center migration is either:

  • in-place, where a single Server application is deployed as a multi-node Data Center application, or
  • consolidated, where multiple Server applications running on isolated nodes (for example, different instances of JIRA being used by different teams) are deployed as a single multi-node Data Center application

This document focuses on the in-place migration process. If you need to consolidate instances in your migration, see Overview of Atlassian Data Center instance consolidation.

 


Build a project team

Enlist people and align the team on the Data Center goals.

Enlist people

An ideal Data Center deployment is a fully fledged project with defined roles and responsibilities across teams. As early as possible, you should communicate with individuals and stakeholders who are interested and impacted by a move to Data Center. Where possible, recruit and enroll these people to be a part of the process. Here is an overview of roles that will make the process more successful.

Strategic
Executive Sponsor Given the scope of migrating to Data Center, it will be useful to have executive buy-in for the project.
Steering Committee A project steering committee provides strategic and tactical guidance.
Technical Product/Project Manager The technical product (or project) manager owns the schedule, ensures task completion, and resolves cross-functional issues. This person also communicates project updates to stakeholders and announcements to end users.
Technical Account Managers An Atlassian Technical Account Manager can provide guidance on the deployment plan and ensure that the right parts of the customer organization are involved in the process.
Tactical
Power Users These are often JIRA project administrators or Confluence space administrators. They will be crucial in verifying functionality and performance during testing to ensure that Data Center is operating properly.
Helpdesk, Sysadmins Frontline staff address L1 support issues that may arise during migration, allowing the Atlassian product administrator to focus on the more critical issues during the process.
Database Administrator
The Database Administrator (DBA) provides frontline support during the process as well. The DBA also reviews and updates the organization's disaster recovery plan to align with Data Center's DR operation.
Network Engineer The network engineer analyzes connectivity and updates networking requirements for Data Center. The network engineer can also provide expertise and guidance on selecting and configuring the load balancer, which is an essential component in Data Center.
Site Reliability Engineer The SRE ensures that Data Center properly operates and scales with the rest of the organization's technology infrastructure.
Security Engineer The security engineer ensures that Data Center adheres to the organization's security practices.
Premier Support Atlassian Premier Support provides fast 24/7 support for any issues the team may experience during the deployment. Premier Support can also help review the current Server installation and validate whether it's ready for a move to Data Center.

Align the team on your Data Center goals

Data Center offers a variety of benefits, and customers choose it for reasons specific to their needs. It's important that these reasons, the associated goals, and metrics showcasing the impact and improvements of Data Center are communicated and agreed upon throughout the organization and well documented, particularly if personnel change during the project. During implementation, the team will evaluate a go/no-go decision based on these criteria. Deploying confidently to production requires that all stakeholders align on mutually agreed-upon business, functionality, and performance goals for the migration. Proper upfront alignment ensures a smoother installation, testing, and release process.

 


Review your current Server installation

Benchmark and fine-tune your server application, assess and upgrade governance, and review installed add-ons.

Benchmark your Server application

Take a baseline measurement of your system functionality and performance relevant to the organization's goals for moving to Data Center. Throughout testing, the team can measure the expected improvements resulting from migrating to Data Center.

Fine-tune your Server application

Data Center's horizontally scalable multi-node cluster allows the application to handle significantly more concurrent users. While this is a significant gain, particularly for organizations that are growing and adding users to their Atlassian tools, it's important to remember that Data Center does not inherently improve the performance of the individual nodes themselves. Any performance issues not related to concurrency, arising from suboptimal configurations or usage in the Server application, may persist or even worsen in Data Center. For example, a JIRA Server application with a large number of custom fields will likely experience performance degradation. Deploying this JIRA application with Data Center will not improve performance as the existing custom fields will continue to degrade performance. In this example, it is important to review custom field usage and eliminate them where not necessary to improve performance. To fully leverage Data Center's value, it's important to first completely review and optimize the existing Server installation to remove as many performance impediments as possible.

For example, in JIRA, an increase of the following factors can impede application performance:

  • number of JIRA issues
  • number of custom fields
  • number of email notifications
  • number of add-ons
  • number of workflow step executions
  • choice of server running the application

Review each of these factors to see where usage can be peeled back as much as possible in order to maximize performance.  Although you may spend 1-2 weeks to achieve the necessary performance optimizations, we've found that customers who don't do this early on tend to have a longer and more challenging deployment.

For help optimizing your application, see the following links:

Assess and update governance

How users interact with the application also affects application performance. For example, users that run frequent reports can place strain on the system causing performance degradation. These usage characteristics will need to be addressed before deploying Data Center. It may be necessary to place certain restrictions on scripts that make REST calls and other kinds of integrations. Specifically, scripts that execute many write operations can impede cluster performance as these write operations will sync across all nodes. The team will need to determine the correct balance between user functionality and performance that aligns with the organization's needs.

Review installed add-ons

As noted above, using a large number of add-ons may degrade application performance. Remove add-ons that aren't crucial to system functionality to increase overall system performance. As some add-ons are not compatible with Data Center (certified Data Center add-ons can be found in Atlassian Marketplace ), it will be necessary to investigate alternatives where required. For more information, see Evaluate add-ons for Data Center migration.

 


Document current processes

After application tuning, document aspects of the Server installation. This will help guide configuration options for Data Center deployment, influence process modifications motivated by Data Center, and identify whether issues observed after deployment are new or already existing. Some items to note are:

  • General system behavior benchmarks regarding operation, functionality, or performance of the Server application to identify if the Data Center deployment exhibits new or previously existing behavior
  • API access patterns for the application (heavy API usage may indicate a need to provision specific nodes to handle API traffic)
  • Backup processes and frequency
  • Reporting processes, frequency, and recipients
  • Monitoring tools and what is being measured
  • Scheduled maintenance routines
  • Disaster Recovery plans for the organization

Processes across different application instances will need to be documented, assessed, and appropriately consolidated into a single set of processes for the Data Center application. It is important to communicate these changes to each of the impacted teams continuously.

 


Evaluate technology decisions

Getting ahead of the following technology decisions and tasks will help the team more quickly design a production-ready cluster environment tailored to the organization's needs.

Components

These are the key components of the multi-node cluster environment. Atlassian doesn't make specific recommendations on which vendors and options to use, but see We're here to help below for getting help with these decisions.

 

Load Balancer

The load balancer distributes requests from your users to the cluster nodes and provides high availability for your application. For more information about load balancers, see the following links:

Application nodes

Data Center nodes share the workload of incoming requests. All nodes, which must be in the same data center, are active and process requests. If a node fails, the load balancer will send requests to the remaining nodes in the cluster.

While some are guides for a single Server deployment, these links should give you a starting point as you consider what you need:

Shared database

Data Center applications generally support the same databases the Server application supports.

Bitbucket Data Center does not currently support MySQL.

When setting up your shared database, make sure that it allows at least the number of maximum connections across all nodes. For example, if you have 3 nodes that can each support a maximum of 50 connections, then your shared database must allow at least 150 connections. It's likely that you will need to configure additional connections for administrative or other purposes.

Shared file system

All Data Center applications require a shared file system, such as network attached storage via a file system protocol, such as NFS. All nodes in the cluster should have access to a shared directory in the same path. Examples of what the shared file system stores include plugins, shared caches, repositories, attachments, and avatars.

For more information on any of these components for each product, see the following links:

Cluster setup

It's a good idea to spend time evaluating, configuring, and optimizing your cluster configuration to ensure that it meets your organization's needs as best as possible. Here are a few examples of things that have come up when reviewing some of our customers' installations:

  • Evaluate if a cluster with fewer larger nodes or a cluster with more smaller nodes is a better fit for your environment.
  • Account for cascading failure when determining node size. This occurs when an instance fails and the remaining instances cannot handle the incoming load.
  • Consider traffic segmentation so that specified nodes exclusively handle specific kinds of traffic.
  • Investigate virtualization and automation tools such as Docker, Chef, and Puppet to better manage scaling the cluster.
  • Invest in robust monitoring tools such as New Relic, Splunk, and ELK.
  • Ensure existing monitoring tools are reconfigured to handle multi-node environments.

 


Implement your test & deployment process

Test your Data Center installation and launch your Data Center on production.

Test your Data Center installation

In order to confidently deploy Data Center to production, the team should run through an iterative set of functional tests, integration tests, and performance tests to vet the Data Center installation. Team members should agree to a set of metrics to effectively evaluate a go/no go decision for deploying Data Center. The following is a general process we recommend to customers for a successful deployment. 


The timing for each step is an average we've seen across our customers who have successfully installed Data Center. 

  • Test: After migrating the application to a test environment, the team should run a collection of user acceptance tests, which verifies functionality, performance, and integrations relevant to the organization. Each test may span 1 to 2 weeks and ensure that a set of metrics are being met. This is an iterative process that should test a variety of characteristics to ensure that the application is production-ready. This is the most intensive part of the migration process and typically takes about 3 - 6 months to execute.
  • Refine: Results from the user acceptance tests will help direct the team how to optimize configurations in the application and harden processes governing application usage. It ensures that the organization's processes and application configurations are tightly coupled.
  • Document: The team should be documenting everything throughout the entire process and then use this time to sort and refine all documentation related to installation, configuration, network diagrams, architecture diagrams, lessons learned, bugs, resolutions, and anything else relevant to the application.

Launch your Data Center on production

  • Commit: Using the results of the testing and refinement, the team evaluates if Data Center is ready for production. If not, iterate back to testing to identify shortcomings and gaps.
  • Execute: Organizations typically push to production over a weekend or some other time of low usage. Some customers opt for a "mock deploy" to test and verify their launch process. Ensure that notifications are sent to end users throughout this process. 
  • Support: It's critical that the team monitors the Data Center application after launch and checks for any functional or performance issues.



  We're here to help

An Atlassian Technical Account Manager provides strategic guidance for customers interested in moving their applications to Data Center. The TAM collaborates with the customer to develop best practices for configuring, deploying and running a Data Center application a way that aligns with the organization's operations and long-term goals.

Atlassian Premier Support provides 24/7 support for customers during the Data Center migration process. Premier Support also offers health check analyses to validate the readiness of a customer's environment.

Atlassian Enterprise Partners offer a wide array of services enabling enterprise organizations to get the most out of their Atlassian tools, including Data Center migrations. For customers looking to consolidate application instances into a single Data Center deployment, an Enterprise Partner can be a valuable resource.

Customers can also read and ask questions in the Atlassian Community for help with Data Center as well.


 

Last modified on Aug 30, 2017

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