Client: NDA

Case Study: Incremental AWS Migration

Case study details

A company that developed a platform aimed at increasing eCommerce sales through the recovery of abandoned shopping carts struggled with handling the increased data volume on its current hosting. Consequently, the company decided to migrate to AWS but wanted to do so incrementally to ensure the integrity of the service was not jeopardized.


The client’s SaaS business, which sends physical letters for online stores, outgrew its initial small-scale Windows setup due to increased data volumes. Migrating to AWS, they chose an incremental strategy to minimize risks, costs, and downtime, ensuring a smooth transition without disrupting service.


The first step in the incremental AWS migration involved moving the system’s core to the new infrastructure while maintaining connectivity with components still on the old setup. This approach aimed to keep the system’s most crucial and maintenance-heavy part running on AWS, reducing costs and minimizing service disruptions during the transition.


The Addepto Team started by thoroughly reviewing the existing data pipeline and Data Operations, aiming to pinpoint inefficiencies and bottlenecks while setting actionable steps for improvement. Their strategy focused on adopting AWS best practices for deploying, monitoring, and governing data services to ensure scalability.

Recognizing that migration involves more than just relocating services due to differences in technology and architecture, the process demanded significant code revision and, often, complete rewriting to achieve compatibility and efficiency in the new environment.


From Windows to AWS: Smooth migration strategy ensures business continuity for SaaS platform

The client’s business was based on a SaaS platform that generates and sends traditional letters to consumers of online stores as a replacement for standard reminder emails, utilizing sales data.

The entire system was initially set up on a small-scale infrastructure relying on Windows.

As the business grew, this system proved insufficient to handle the increasing data volume, and upgrading to a higher package was not cost-effective. The company thus decided to migrate to AWS.

Migration is always a risky, time-consuming, and costly operation.

However, since migration is always a risky, time-consuming, and costly operation, they aimed to ensure the entire process would be safe and smooth without a significant amount of downtime during which services would be unavailable to users.

They opted for an incremental migration strategy, as it would allow them to mitigate these risks by breaking the migration down into manageable parts.

Our team expert opinion


Addepto Team enhances data pipeline for efficient AWS migration

The Addepto Team began with a comprehensive examination of the existing data pipeline architecture and the Data Operations processes. This evaluation was aimed at identifying any inefficiencies and bottlenecks, as well as at setting clear, actionable recommendations for refining the data pipeline and establishing a streamlined, efficient Data Operations process.

The recommendations were based on best practices for deploying, monitoring, managing, and governing data services and solutions within the AWS ecosystem, ensuring that the approach adopted was scalable and effective for both current and future needs.

During project development, our team worked on:

  • Migrating services to another infrastructure is never a straightforward task; it requires thorough code revision and refactoring. In practice, it often becomes apparent that the code needs to be completely rewritten. This complexity arises from the differences in underlying technologies, architecture constraints, and performance considerations between the old and new environments.
  • Therefore, the migration process developed by the Addepto Team entailed more than a mere lift-and-shift; it required a deep dive into the codebase to ensure compatibility, efficiency, and scalability in the new infrastructure.


Incremental migration strategy begins with core service abstraction, ensuring seamless transition

The initial step in adopting an incremental migration strategy involved abstracting the core of the service and migrating it without losing connectivity with the rest of the system, which remained on the old infrastructure.

The objective was to ensure that the “heart of the system,” the most maintenance-intensive component, was operational on the new infrastructure while the remaining components stayed on the old one.

This strategy facilitated a smoother transition by prioritizing the migration of the most critical and resource-demanding part of the system, thereby reducing operational costs and minimizing disruptions to the overall service during the migration process.

Technologies that we use



Cloud Storage


Amazon SQS

Amazon SQS – It is a managed message queuing service by AWS. It enables developers to send, store, and retrieve messages between software components, facilitating decoupling and scaling in distributed systems, microservices, and serverless apps.
Amazon DynamoDB

Amazon DynamoDB – It is a fully managed NoSQL database service by AWS. Amazon DynamoDB offers fast, predictable performance and seamless scalability for storing and retrieving any amount of data and handling any level of request traffic.
S3 (Simple Storage Service)

S3 (Simple Storage Service) – It is a scalable, high-speed, web-based cloud storage service provided by Amazon Web Services (AWS). It is designed for online backup, archiving, and storage of data and applications on AWS
Amazon Lambda

Amazon Lambda – It is an event-driven, serverless computing platform provided by Amazon Web Services (AWS).

Amazon Elastic Container Service (ECS) Fargate

Amazon Elastic Container Service (ECS) Fargate – It is a fully managed container orchestration service provided by Amazon Web Services (AWS). It helps developers deploy, manage, and scale containerized applications with ease.


Addepto Delivered

The deployment of the new solution on AWS resulted in significant cost savings, as the company could adopt a “pay as you go” cloud strategy, paying only for actual AWS usage instead of a flat fee for local server infrastructure.

However, the advantages extended beyond mere financial gains. The data flow saw considerable improvement through the integration of automation, making the system more fault-tolerant, easing the process of reruns, and eliminating logical errors. These enhancements in resilience and efficiency not only streamlined operational processes but also strengthened the overall infrastructure.

As a result, data management and processing became more effective and reliable, representing a major advancement towards a robust and dependable system.


  • Fixed costs for local server infrastructure
  • Manual data flow processes
  • Higher likelihood of faults and logical errors
  • Less efficient and reliable data management


  • Adopted “pay as you go” AWS cloud strategy, leading to significant cost savings
  • Improved data flow through automation integration.
  • Increased fault tolerance, easier reruns, and reduced logical errors
  • Streamlined operational processes
  • Strengthened overall infrastructure
  • Enhanced effectiveness and reliability in data management and processing

About Addepto

We are a consulting company focused on delivering cutting-edge AI and Data-driven solutions.

Here you can learn more about the technologies used in this project:

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