A Clear Migration Path to AWS for a SaaS Association Platform

This association management software provider serves chambers of commerce, trade associations, and nonprofits through two core products: a membership management platform and a content management system. Operating a multi-tenant SaaS model with a database-per-customer architecture, the company's on-premises footprint had grown substantially alongside its member base. With a significant share of database servers and operating systems approaching or past end-of-support, moving infrastructure to AWS represented a clear opportunity to improve resilience, reduce operational overhead, and position the platform for long-term scalability. Rather than committing to migration without a structured foundation, the company engaged Protagona to conduct a disciplined assessment — a deliberate first step before any infrastructure change of this consequence.

The engagement aimed to produce a complete migration readiness assessment covering all servers, databases, network topology, and application dependencies across both product lines. Deliverables included a proposed AWS landing zone design, a side-by-side comparison of migration strategy options, a phased migration roadmap, and a financial model quantifying the cost impact of moving to AWS — giving the client's team a clear, evidence-based basis for execution decisions.

Several dimensions of complexity required careful analysis before migration planning could begin. The multi-tenant database architecture meant hundreds of member databases resided across a small number of physical servers, each carrying roughly 480 tables and 23 views per customer database. Hard-coded IP addresses throughout the application landscape and linked SQL Server configurations meant a server-by-server migration approach would carry significant risk without detailed dependency mapping first.

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Beyond application architecture, 13 database servers were running out-of-support SQL Server versions and 12 servers were running out-of-support operating systems — all exclusively on Windows. A key analytical question was whether re-platforming the messaging and caching layers from Windows-based ActiveMQ and Couchbase to Linux-based Amazon MQ and Redis was viable alongside the core migration, and how the cost and timeline tradeoffs of each path compared. Coordinating deep-dive technical sessions across load balancers, queue services, application servers, and databases — while producing a financially grounded recommendation — required both architectural depth and structured program management across the full 44-server environment.

Protagona began by reviewing Cloudamize's automated assessment of all 44 in-scope servers alongside the existing infrastructure inventory, then conducted structured deep-dive sessions covering load balancers, message queuing, application servers, and databases. This dual approach confirmed server configurations, mapped network topology and data flows, and surfaced the dependency relationships between the two product lines that would govern migration sequencing.

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From that foundation, the team designed a proposed AWS landing zone with a full organizational unit structure, VPC layout, subnets, and security group architecture. Two migration strategies were developed in parallel. Option 1 was a phased lift-and-shift organized into four waves, prioritizing lower-risk databases in early phases to validate cutover procedures before tackling larger and more complex server groups. Each phase included defined cutover testing procedures, with target database downtime under 15 minutes per instance and a canary deployment pattern using DNS and CNAME updates to route a controlled percentage of member traffic to AWS before full cutover. AWS Systems Manager was incorporated to automate configuration management across the rebuilt EC2 environment, and AWS Fault Injection Service was included in the final phase for resiliency validation.

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Option 2 extended the lift-and-shift by re-platforming the messaging and caching layers from Windows-based ActiveMQ and Couchbase to Amazon MQ and Redis on Linux — reducing ongoing Windows licensing spend and long-term operational footprint at the cost of additional refactoring. The financial analysis, grounded in Cloudamize right-sizing data, showed that combining right-sizing with 3-year Reserved Instance commitments could reduce annual infrastructure costs by 43% compared to on-demand lift-and-shift pricing.