Data On-premise to Cloud Migration:
A Step-by-Step Checklist for Success

Data On-premise to Cloud Migration: A Step-by-Step Checklist for Success

Migrating from on-premise IT infrastructure to the cloud is one of the most impactful yet challenging technological endeavors an organization can undertake. Moving years’ worth of vital company data and critical applications off privately controlled servers onto a public cloud platform is no small feat. However, with careful planning and execution, this migration can allow businesses to truly unlock the myriad of much-touted benefits offered by the cloud — scalability, cost savings, flexibility, and more.

This comprehensive guide covers key practical steps technology decision-makers should include in their on-premise to cloud migration checklist to ensure a smooth and successful transition that aligns with their unique business needs.

Conduct a Thorough Assessment of Existing On-Premise Infrastructure

The first phase of any migration project is gathering complete information on current IT systems and requirements. Without understanding what exists on-premise — including applications, data stores, server hardware, network architectures and more — mapping out a cloud transition strategy is virtually impossible. Teams should conduct full assessments of the following:

Inventory All Data and Applications

Document what data repositories, databases, software platforms and other solutions are currently running on local servers, along with metadata like volume, throughput, access frequency and more. This provides clarity on the scale of datasets and applications needing cloud migration services and solutions to be done.

Map Application and Data Interdependencies

Diagram the connections and interdependencies between applications and underlying databases or data lakes. Identifying integration touchpoints ensures related systems are migrated in sync to avoid disruption while clarifying the shift’s impact on downstream business processes relying on that data.

Analyze Performance and Infrastructure Requirements

Profile essential workloads across metrics like computing power, memory, storage, network bandwidth, data ingress/egress speed and latency. This establishes appropriate cloud instance types, storage options and network configurations to procure in advance.

Additional Resources: Cloud-Based ERP Solutions: Benefits, and Costs

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Evaluate and Select the Optimal Cloud Deployment Model

With a clear picture of on-premise systems and requirements, the next major milestone is choosing the right cloud deployment model that aligns with the organization’s needs and preferences regarding control, flexibility and capital expenditure.

Public Cloud

Public cloud providers like AWS, Azure and Google Cloud offer shared, multi-tenant infrastructure and platforms. This allows customers to avoid large upfront investments in owned data centers, making the public cloud ideal for businesses focused on agility and Opex spending.

Private Cloud

A private cloud consists of dedicated single-tenant infra and platforms operated solely for one organization. This ensures greater customization, security and control—at a higher cost. Private clouds suit companies with strict governance needs and a sufficient capital expenditure budget.


Hybrid combines public and private cloud, allowing businesses to run sensitive workloads privately while leveraging public cloud benefits where possible. Though more complex to manage, hybrid enables the best of both worlds.

Further, decision-makers must choose between Infrastructure-as-a-Service (flexible but more hands-on), Platform-as-a-Service (more opinionated tooling and services) and Software-as-a-Service (fully prepackaged solutions requiring little configuration). Aligning to internal developer skill sets and application needs here is vital.

Carefully Evaluate and Select a Cloud Services Provider

Choosing the right public cloud vendor is arguably the most crucial decision in this migration checklist. While the “big three” market leaders — AWS, Microsoft Azure, and Google Cloud Platform — offer many overlapping services, each has unique strengths and weaknesses to weigh based on the assessed application requirements and target infrastructure defined earlier.


With the most mature and extensive global cloud infrastructure offering, AWS suits most custom migration needs. The breadth of services, scalability and proven enterprise reliability makes AWS hard to beat for customized production workloads. However, all this reconfigurability means hands-on effort is still required.

Microsoft Azure

Azure shines when it comes to tight integration with Windows, .NET applications, hybrid on-premise infrastructure and tooling like Power Platform, Dynamics 365 and Teams. Large Windows-centric enterprises benefit greatly from Azure’s specialized platform. Yet, it still lags behind AWS in some services.

Google Cloud Platform

Google’s cloud plays to its core data and AI strengths with unmatched analytics, machine learning, big data and containerization capabilities. For data-driven apps or ML engineering teams, GCP is likely the best fit. However, it does have fewer global regions than AWS and Azure presently.

Thoroughly testing applications on each major vendor’s free trial tier and investigating unique service support is time well invested here.

Meticulously Map Out the Migration Execution Plan

With the foundation set around deployment models, the chosen cloud provider, and resourcing requirements, the phases of actual application and data migration are next. IT leads should aim to minimize business disruption without compromising on thorough testing.

Set Up Initial Cloud Environment and Tooling

Meticulously Map Out the Migration Execution Plan

First, the core cloud network architecture spanning VPCs, subnets, network security groups, routing policies, restricted access roles and other cybersecurity controls should be established per internal governance standards. Additionally, essential migration and management utilities like data transfer tools, backup/recovery software, monitoring dashboards and automation tooling should be deployed early on.

Schedule Migration in Phases by Priority

The actual migration rollout must be orchestrated in multiple testing phases, arranged by the priority level of applications from non-critical to mission-critical. This ensures minimal downtime impact on key business processes while allowing iterative validation of successful configuration and performance in the cloud environment after each batch.

Validate Extensively After Each Phase

In perhaps the most crucial checkpoint, teams must rigorously test systems’ functionality, security and performance after migration to validate seamless operation as expected. Any stability, latency or compatibility issues must be swiftly addressed through cloud architecture adjustments or supplementary services/tooling.

Finally, after confirming successful data and application functionality through testing, traffic can be permanently redirected to the cloud platform, allowing the legacy on-premise hardware to be decommissioned. However, teams should have rollback contingency plans in place during this flip.

Migrating an enterprise from maintained servers to the public cloud is truly a multifaceted, long-term endeavor spanning people, processes and technologies. While the benefits make the effort worthwhile, meticulous planning and phased execution are critical for minimizing business disruption during this transition. Information technology leaders can leverage this comprehensive checklist, which covers critical assessment, cloud model selection, provider evaluation, staged migration, and cost optimization, to lead their organization’s data center exit successfully.

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