As industries race to capture the value of AI, legacy and disconnected systems become harder to maintain and integrate with modern software and AI applications. Some companies resist moving to the cloud or consolidating their infrastructure for compliance and privacy reasons; for others, the logistical hurdles have blocked cloud migration. By consolidating infrastructure and embracing a cloud-first strategy, companies can minimize the costs of technical debt while building the robust framework necessary to thrive in an increasingly automated landscape.
What is Cloud Migration?
The cloud migration process involves moving a company’s digital assets, operations, and processes to the cloud, or from one cloud to another. These assets include databases, applications, and services vital to the organization’s operations. This is why a methodical approach to cloud migration is crucial and why choosing the right strategy matters.
A cloud migration strategy establishes the process through which you execute the movement of critical business functions. Taking a data-first approach to cloud migration will help ensure the integrity and accessibility of your information, and also help you optimize your infrastructure to meet your organization’s unique needs.
Before exploring the leading migration strategies, we’ll examine the best practices to follow while implementing your migration.
7 Cloud Migration Best Practices
Migrating data to the cloud, or between cloud services, poses a number of challenges that can be avoided by following standard best practices.
1. Define your goals
Having a clearly defined destination will set you on the right path for successful cloud migration. Knowing where you’re going is always important before you begin a journey. Ask your teams questions like:
- What’s driving your migration?
- What business needs are you trying to meet through this process?
- What are our top priorities for post-migration?
Don’t forget to consider your future growth in this phase. For example, if you anticipate that your company will be using AI Agents to automate your business processes within the next 2-3 years, planning for it now can help ensure your cloud infrastructure is positioned to control costs and scale your computing power.
Above all else, make sure your goals are achievable. Research has shown that most cloud migration projects either don’t achieve the desired results or take far longer than expected. You may find you need to break your migration down into multiple smaller stages or phases.
2. Create cloud architecture to meet your business goals
During this discovery process, you may find that your optimal solution combines cloud migration with other data services, such as data warehousing. A data architect can help you map out which structures you need to best meet your business goals.
3. Work with a cross-disciplinary team
Crafting your data migration strategy with data scientists, developers, and cloud architects is a good start. But don’t forget to bring other key stakeholders on board. This migration should be planned to meet the needs of other business units that rely heavily on this data.
Involve executive leaders who can help set optimization goals and gain buy-in from other business unit leaders. Doing this at the start of a migration project can prevent problems later.
4. Consider a multicloud strategy
While this approach is not for everyone, some organizations benefit from a multicloud strategy.
Reasons to consider moving your data to more than one cloud service include:
- Different vendors may have different applications or services that meet your industry-specific needs.
- Another vendor may be able to provide a cloud-based solution at a lower cost than your primary platform.
- If you have data that is subject to regulatory oversight, a second vendor may be ideal for handling this high-risk data.
- Not having “all your eggs in one basket” can mitigate the impact of cloud provider downtime, both expected and unexpected.
5. Tidy up your data before migrating
Before migrating your data, invest in your overall data quality: clean up any discrepancies, duplicates, misapplied fields, or other issues that might make it difficult for the cloud platform to parse where that data belongs.
Data hygiene is always a best practice. But a data audit ahead of migration will save you a great deal of time and frustration both during the process and when your information resides in the cloud.
6. Search out a low-code platform
Cloud migration requires a certain amount of one-time coding. This is known as “throwaway” code since it is useless after the migration is complete.
An Integration platform as a service (iPaaS) with low-code tools and agentic workflows reduces the time spent writing repetitive code, and has features that allow your team to create any required temporary code quickly.
7. Optimize data management with iPaaS
Another benefit of iPaaS is that your integration process and data management systems are centralized on a single platform. Offsite data management requires regular backups to keep your cloud data current.
With an integrated iPaaS, your data can be securely managed, automated, and integrated from a single point of control. This allows you to directly add processes for data discovery, cleansing, and synchronization to your data management system, ensuring data flows smoothly and accurately between applications.
What are the Common Challenges of Cloud Migration?
Cloud migration involves moving data, applications, or other business elements to a cloud computing environment. While this process offers many benefits, it also presents several challenges. Here are some common ones:
Cost Management:
Migrating to the cloud can incur unexpected costs, especially if the migration process is not well-planned. Additionally, pay as you go models can lead to higher than expected operational costs. Either way, budget is not always clear, which can be a tough sell for businesses.
Data Security and Compliance:
If not done properly, moving data to the cloud presents new security threats. Along with exposing yourself to new threats, ensuring that data storage and meeting regulatory requirements can be challenging, particularly across different regions and industries.
Downtime and Disruption:
During the migration process, services may be disrupted, affecting business operations. And as with any migration, there is the possibility of incomplete or even failed migration attempts, which can result in loss of data.
Addressing these challenges requires a clear understanding of business needs, and a well-defined migration strategy. Collaboration with experienced cloud service providers and leveraging best practices can help mitigate risks and ensure a smooth transition.
7 Cloud Migration Strategies
Even with the many opportunities presented by data modernization, the process itself can be daunting. That’s why the right process and the proper data integration techniques are important.
While there’s more than one way to migrate data to the cloud, many experts have been on this journey and offered guidance to others. The following cloud migration strategies are based on research originally conducted by Gartner and expanded upon by Amazon:
1. Rehost
This is also referred to in industry-speak as “lift and shift.” Rehosting is simply moving a direct copy of an organization’s data infrastructure directly onto the cloud. This strategy benefits smaller organizations without complex data architecture, though it sacrifices the option of restructuring data to work with newer cloud-native technologies.
2. Replatform
A step beyond rehosting, this strategy is known as “lift, tinker, and shift.” The data architecture remains the same, but strategic changes are made to ensure the full use of cloud-based services.
3. Relocate
Transferring your architecture from the on-premises solution provided by a vendor to the cloud solution offered by the same vendor. This means that the only thing you need to migrate is your data, minimizing application and data downtime.
4. Refactor
If your primary goal is to improve data management without any other significant changes, replatforming might be the best strategy. It involves making a few optimizations but retaining your existing data architecture.
5. Repurchase
The least complicated technique, repurchasing involves purchasing a data management system as software as a service (SaaS). An example of repurchasing is an organization moving from its native CRM platform to a platform like Salesforce.
6. Retire
An audit of your data management system may reveal that certain functions are no longer needed. Those can be turned off or retired. This will help you streamline any future cloud migration plans.
7. Retain
If your audits and analysis show that now is not the time to conduct your migration to the cloud, it is perfectly acceptable to hit pause and wait until there is a qualifying reason to make the move.
Cloud migration is complex, but your data strategy shouldn’t be. Ensure your migration is built on a foundation of integrity and scale. Access the latest Gartner® Magic Quadrant™ for Master Data Management to see why Boomi is the preferred choice for connecting and governing the modern enterprise.