Drivers for migrating to the cloud - Migrating Magento Open Source or Adobe Commerce on Cloud Infrastructure Self-Service to AWS

Drivers for migrating to the cloud

The drivers behind starting a new Magento Open Source or Adobe Commerce on Cloud Infrastructure Self-Service setup or moving an existing on-premises setup to the cloud are numerous but the most common strategic drivers include: reducing capital expenditure, decreasing ongoing cost, improving scalability and elasticity, improving time-to-market, and attaining improvements in security and compliance. In addition, situational and business drivers also influence the move to the cloud.


Supporting your organization’s DevOps strategy may be a primary driver for migrating to cloud or may be an unanticipated benefit. In either case, migrating to cloud provides a technical foundation to supporting your organization’s DevOps strategy by way of the same capabilities expected of cloud and as defined by NIST: On demand and self-service, broad network access, pooled resources, rapid elasticity—all delivered as a metered service providing you the ability to control how your organization consumes it.

Each of these capabilities directly maps to demands placed on a technology organization, regardless of your organization’s adoption of DevOps, Site Reliable Engineering (SRE), and so on, but most importantly, it is the ability to programmatically define infrastructure and configuration, that is, infrastructure as code (IaC), and using that ability to dynamically create/tear down environments as part of a well implemented software development life cycle (SDLC) process.

In addition to providing a supporting technology platform for the enablement of DevOps processes on AWS around Magento Open Source or Adobe Commerce on Cloud Infrastructure Self-Service to AWS provides a collection of services that can offer (in the absence of) or augment your existing software configuration management (SCM) solutions, including AWS CodeCommit, AWS CodeBuild, AWS CodePipeline, and AWS CodeDeploy, which provides for a managed source control, build, continuous integration/continuous deployment (CI/CD) and deployment services.

Data center consolidation

Data center consolidation is a key requirement driver that may warrant the need to move to the cloud. For example, an organization’s current data center can no longer support the business need for growth in terms of current space, power, and cooling. Also, an organization’s current data center may have too many single point of failures and carry inherent risks of outages.

Mergers and acquisitions

Mergers and acquisitions are a situational driver, and might require an organization to separate and consolidate application setup. Also, an organization may face the sale of a building, rental fees, or increases in co-location costs that may result in similar needs to consolidate or separate application setup, leading to the need to move to the cloud.

Digital transformation

Digital transformation is more than simply digitizing data, and it involves the transformation of business and organizational activities, processes, competencies to accelerate deliverables that differentiate an organizations core business. The need for digital transformation in organizations have resulted in the evolution of organization’s IT department to become more agile and innovative to adapt to the changing needs of an organization.

AWS Cloud infrastructure setup frees an organization’s IT department from the heavy lifting of racking, stacking, and powering servers to focus on the organization’s own customers. Concentrating on the projects that differentiate an organization’s core business, rather than the infrastructure, substantially improves products, services, delivery, and ultimately the ability to compete.

Benefits of the cloud

Organizations considering a transition to the cloud are often driven by their need to become more agile and innovative. The traditional capital expenditure (CAPEX) funding model makes it difficult to quickly test new ideas. The AWS Cloud model gives you the agility to quickly spin up new instances on AWS, and the ability to try out new services without investing in large upfront, sunk costs (costs that have already been incurred and can’t be recovered). AWS helps lower customer costs through its pay-for-what-you-use pricing model.

Operational improvements

The value proposition of migration of on-premises Magento Open Source or Adobe Commerce on Cloud Infrastructure Self-Service or enterprise edition to AWS is further enhanced by the availability of several services that provide for operational insight and agility.

Operational insight into the platform from not only a technical perspective (for example, requests per hour) but also from a business operational perspective (for example, orders per hour), particularly when the two sets of data can be married, providing a near real-time look into campaign performance, platform operations costs, and a variety of other indicators.

This data provides a basis for, and support of, change as does the agility afforded by AWS, allowing for a content and functional deployment pipeline, A/B testing and feedback loops, allowing for continuous improvement, measurement and pivoting when it comes to the user experience of Magento Open Source or Adobe Commerce on Cloud Infrastructure Self-Service on AWS.

Technology improvements

The momentum of a migration presents an opportune time to look at technical improvements. Enabled with AWS, these technical improvements can be implemented in a commitment-free manner, evaluated and codified.

A typical Magento on-premises installation might leverage as little as one server or numerous servers, based on scale and architecture, but in addition to servers, third-party services might be leveraged as well, such as content delivery networks, and indexing services.

The breadth and depth of the AWS service offerings, as well as the billing constructs available on AWS serve to eliminate the baseline quantity of servers to be managed as well as provide a means to consolidate vendors, achieve larger quantities of scale, and have predictable baseline and burst cost models as it relates to operating the infrastructure. This is exclusive of the potential gain in efficiency around management of the platform, furthering lowering operating costs.