Case Studies | SaaS B2B

Consolidating a multi-cloud SaaS onto AWS

Inside Out AWS Migration

About

A SaaS B2B business working with Cloud Combinator on AWS. The client is anonymised at their request.

Challenge

The engagement addressed four focus areas.

A fragmented multi-cloud estate

Frontend, database, cache, and AI each lived with a different vendor, so billing, observability, security, and governance were spread thin. The client wanted a single AWS estate that consolidated these concerns without a risky big-bang rewrite.

Database portability and connection scaling

Neon's serverless HTTP driver could not talk to standard AWS database endpoints, and dozens of backend functions opening fresh connections would exhaust a conventional database. The target needed managed pooling so application connections could scale safely.

AI model quality risk

Moving inference to Bedrock could not be allowed to regress agent reasoning or Terraform drafting quality. Any migration of the AI core had to be gated on measured evidence rather than assumption.

A zero-disruption cutover

Inside Out is a live B2B product, so the plan had to be phased and reversible, running new components in parallel with the old and flipping traffic only once each layer was validated.

Solution

Cloud Combinator organised the work into tracks that could start immediately alongside those gated on DNS cutover or on the model evaluation, sequenced across six phases.

6

Phase migration runbook across four parallel tracks

60-80

Eval test cases across four scoring categories

90%+

Of the baseline score required to pass the model eval

By the numbers:

  • 6 - Phase migration runbook across four parallel tracks
  • 60-80 - Eval test cases across four scoring categories
  • 90%+ - Of the baseline score required to pass the model eval
Changes

Cloud Combinator delivered the full migration architecture and the operational plan to execute it: a six-phase runbook across four parallel tracks, a component-by-component design for Amplify, Aurora, ElastiCache, and EventBridge, a risk register with mitigations, and the Bedrock evaluation framework that de-risks the AI decision. Each track is sequenced so the client can consolidate onto AWS incrementally and reversibly.

  • Single AWS estate — A target design consolidates frontend, database, cache, scheduling, and AI onto AWS, replacing four separate vendor control planes.
  • Safe connection scaling — Aurora Serverless v2 with RDS Proxy in transaction mode gives the backend a managed connection pool in place of the Neon serverless driver.
  • Evidence-gated AI — A four-category eval harness with a defined pass bar and a joint decision gate ensures Bedrock is adopted only if it meets the quality bar.
  • Reversible cutover — Parallel-run schedulers, staged driver swaps, and a DNS flip with reduced TTLs keep every step recoverable.
  • Handover — Phase-by-phase runbooks, a pre-cutover checklist, and a risk register equip the client's engineers to execute and validate each stage.

With the plan and eval framework in place, the client is positioned to consolidate onto AWS track by track, retire its redundant cloud subscriptions, and make an informed decision on Bedrock, all with a route toward a Well-Architected Review and Foundational Technical Review readiness.

AWS Stack

AWS Amplify Hosting

For the Next.js frontend and backend-for-frontend.

Amazon Aurora Serverless

V2 with RDS Proxy for a pooled, scalable data layer.

Amazon ElastiCache

For Redis for caching and queues inside the VPC.

Amazon EventBridge Scheduler

With AWS Lambda for scheduled digest and reaper jobs.

AWS Secrets Manager

For centralised, reference-based secret management.

Amazon Route

53 and AWS Certificate Manager for DNS cutover and TLS.

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