Cloud migration offers more than just cost savings. It unlocks scalability, operational flexibility, stronger security, and faster access to innovation.

But realizing those gains requires more than just relocating systems. By following the right cloud migration steps, your team can minimize disruption, maintain data integrity, and move to the cloud with confidence.

In this guide, we’ll break down each phase of the process and offer tips for executing it effectively.

What is cloud migration?

Cloud migration is the process of moving organizational assets, applications, and workloads from on-premises infrastructure to a cloud provider. Migration doesn’t just reduce costs and improve performance — it also modernizes legacy systems and makes cloud-native technologies accessible.

But migration isn’t always straightforward. Depending on the systems involved, it may require re-architecting applications, mapping dependencies, or adapting workloads to fit a new cloud environment. That’s why a clear, step-by-step cloud migration strategy is a must. To make things simpler, we’ve broken the process down into five core phases.

6 steps for a successful cloud migration

To reduce risk and keep teams aligned, any cloud initiative should follow a clear set of cloud migration phases, from early assessment through post-cutover optimization.

1. Assessment and discovery

Before modernizing, you need a full picture of what you’re working with. Take inventory of your current infrastructure: Map out on-premises servers, apps, and data sources, flagging anything that’s not cloud-ready. This helps take stock of what you can easily move over and what might need a redesign first.

Use this stage to document dependencies, uncover bottlenecks, and identify legacy systems that might break during migration. After assessment, you should have a clear picture of your data landscape — what’s working, what’s migrating, what’s staying, and what needs to be rethought.

2. Planning and design

Now that you know what you’re working with, it’s time to outline your data migration roadmap. Start by choosing the right cloud destination for you, setting up permissions controls, and deciding what takes priority in the migration. Based on your goals and which pieces you’re migrating first, you can also sketch a rough timeline for the migration.

3. The migration phase

The migration stage is where your data finally begins to move. Depending on your goals, this might happen incrementally or all at once. Either way, your data teams will need to extract and load data from on-premises systems into the cloud. With automated ELT pipelines from platforms like Fivetran, this process scales reliably, ensuring continuous, secure data movement.

If you notice any bottlenecks or simply want to speed things up, Fivetran offers specialized database migration tools that automate and streamline bulk data transfer, helping you move faster with fewer errors. 

4. Testing and validation

Before switching over to your new cloud systems, run tests to confirm that systems and data behave as expected. Run a few application tests, and see how your new performance stacks up against previous benchmarks. For applications, you can use stress tests to see if cloud resource scaling is correctly configured. 

Even if things seem to be working well, don’t make the mistake of overlooking validation — the step where you make sure all migrated data is complete and accurate. Although automated ELT pipelines often include validation techniques, you should run a final validation to confirm data completeness and accuracy. 

5. Cutover

After passing all tests and validation checks, you can cut over from your legacy systems to the newly hosted cloud environments. If the new environment is properly configured and validated, the cutover should involve minimal to no downtime. Some organizations choose to archive their legacy systems as a failsafe, while others decommission them once the cloud system is up and running.

6. Ongoing optimization

Once you’ve migrated to the cloud, the real work begins. Keeping your cloud systems running efficiently involves monitoring data pipeline performance, fine-tuning workloads, and managing costs. But with the right automation in place, you can spot any issues early, improve performance, and scale without adding manual upkeep.

Cloud migration strategies

Not every system or dataset makes the same journey to the cloud. One legacy system might be surprisingly modern and ready to migrate instantly. Another might have layers of interdependencies that mean it needs refactoring.

Here’s how the different strategies stack up.

Rehosting

Rehosting involves exporting an exact copy of your workload and uploading it to the cloud. Also known as “lift and shift,” this approach is best for modern applications that could benefit from cloud scalability without requiring architectural changes.

Tools like Fivetran help maintain data continuity during rehosting by automating secure data replication from on-prem systems to cloud destinations.

Replatforming

With replatforming, businesses make small adjustments to optimize a workload for the cloud without changing its underlying architecture. For example, you could replatform analytical data from a traditional database into a cloud data lake to improve scalability without a major overhaul.

When using tools like Fivetran’s automated ELT pipelines, you can replatform without interruption, as your data sync seamlessly between on-premises and cloud systems. 

Repurchasing

Instead of refactoring or reconfiguring a legacy system, you can onboard a cloud-native SaaS platform with the same capabilities. Although repurchasing is a quick fix, it does mean that your teams will have to bring themselves up to speed with new systems. Also, if you have any custom workflows, you’ll have to rebuild these from scratch. 

Refactoring

Refactoring is the most extensive cloud migration strategy because it requires redesigning applications for the cloud. For monolithic legacy applications, this includes breaking them down into microservices, making it easier to rebuild components independently. Refactoring is only advised for high-value apps that need the benefits of the cloud but are too integral to replace. 

Fivetran supports the refactoring process by automatically handling complex data migrations. With reliable, schema-aware ELT pipelines maintaining consistent data flows, your team can focus on rebuilding applications while knowing their data is fresh and accurate.

Cloud migration benefits

Cloud environments make data easier to move, connect, and analyze, giving teams the agility they need to turn data into insight faster than ever.

Here are a few benefits of cloud migration: 

• Faster, flexible access to data: Authorized users can instantly access up-to-date data from a central source.
• Real-time insights: Live data pipelines power timely, informed decisions.
• Simplified integration: Cloud platforms unify your data stack and eliminate manual syncing.
• Stronger security and compliance: Cloud providers offer built-in, sophisticated security features, automated patching, and tools to help meet regulatory standards and governance requirements.
• Access to innovation: Migrating legacy systems to a cloud data warehouse makes it easier to adopt AI, machine learning (ML), and advanced analytics.

Common cloud migration challenges

Moving to the cloud has huge potential, but it’s not without its hurdles. Luckily, planning ahead can help you avoid most of the pitfalls — from data downtime to unexpected costs.

Here are some of the most common challenges in cloud migration and how you can stay one step ahead: 

• Poor planning and strategy: Every single asset, application, and system has unique requirements when migrating to the cloud. Although it’s tempting to skip planning, that will only lead to data loss and downtime. To keep your data in sync, follow a structured migration roadmap, automating validation and movement wherever you can.
• Unpredictable costs: Manually overprovisioning or missing optimization opportunities will make cloud costs quickly add up. Look for ways to mitigate human error by using automated systems that scale intelligently and adjust resources in real time.
• Managing technical complexity: Refactoring legacy systems is a complex and time-consuming task that shouldn’t be taken lightly. Fivetran automatically handles schema drift and keeps pipelines consistent, so your data flows smoothly even as your systems change.
• Ensuring data security: Cloud security requires shared responsibility — both your company and your provider play a role. To get your data safely from A to B, you need to integrate encryption tools, use secure connectors, and regularly validate your data.

By anticipating these challenges early and following a cloud migration checklist, your organization can use strategies to effectively manage and mitigate risk.

Accelerate your cloud data migration with Fivetran

Fivetran streamlines cloud migration by providing automated ELT pipelines, ensuring your data moves efficiently, accurately, and securely. With enterprise-grade security and built-in compliance features, Fivetran helps make cloud migration a breeze. 

Get started for free or book a live demo today. 

FAQs

What are the 4 Rs of cloud migration?

The four Rs of cloud migration are rehost, replatform, refactor, and replace. While these are the most common strategies, retraining and repurchasing are two alternative solutions. 

How do you migrate an application to the cloud?

To successfully migrate an app to the cloud, you need to assess its requirements, select a migration strategy, prepare the app for migration, then move its data and systems to the cloud. Reliable data replication during the process ensures continuity, prevents data loss, and keeps downstream apps running smoothly.

What’s a cloud migration roadmap?

A cloud migration roadmap is a detailed plan that includes all the systems you’ll move, the strategies you plan to employ, and the steps to completion.

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