Case Studies | SaaS B2B

The last workload off DigitalOcean

AI Service and Qdrant Vector Database Migration

About

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

Challenge

The challenge had three focus areas.

Completing the consolidation

With the rest of the client already on AWS, keeping the AI service and its vector database on DigitalOcean meant cross-cloud calls, duplicated operational overhead, and a security surface split across two providers. The goal was to finish the job and run everything in one place.

Migrating a stateful vector database safely

The AI service relies on a Qdrant vector database for matchmaking. Moving it needed a plan for persistence and for repopulating the vector collections without risky data transfer, while preserving the daily jobs that keep those vectors current.

Replacing third-party tooling and manual steps

The service used Datadog for monitoring and needed a dependable deployment path. The client wanted AWS-native observability and an automated, credential-safe pipeline so the team could deploy and operate the service confidently.

Solution

We delivered the migration in structured phases, provisioning the foundation as code, deploying the services, proving them against real traffic, and only then cutting over, with DigitalOcean kept live as a safety net throughout.

48 hrs

Continuous successful scheduled-job execution required for sign-off

< 5 min

Rollback to DigitalOcean, kept live as a safety net during cutover

1 cloud

This final workload completing the client's AWS consolidation

By the numbers:

  • 48 hrs - Continuous successful scheduled-job execution required for sign-off
  • < 5 min - Rollback to DigitalOcean, kept live as a safety net during cutover
  • 1 cloud - This final workload completing the client's AWS consolidation
Changes

The migration met its acceptance criteria: the AI service running on ECS Fargate and responding correctly, Qdrant populated with freshly generated vectors, and the daily scheduled jobs executing successfully, with DigitalOcean and Datadog fully decommissioned afterwards.

  • Fully consolidated — With the AI service and Qdrant on AWS, the client now runs entirely on one cloud provider, ending cross-cloud calls and duplicated overhead.
  • Safe, transfer-free data move — Vector collections were regenerated daily from RDS rather than copied, removing data-transfer risk and validating the pipeline before go-live.
  • AWS-native observability — CloudWatch infrastructure and application alarms plus an operational dashboard replaced Datadog, including alerts for conditions such as zero artists returned.
  • Automated, credential-safe deploys — A GitHub Actions pipeline using OIDC builds and ships to ECS with no long-lived keys.
  • Handover — Included the migration runbook, operational procedures, and CloudFormation templates so the client can maintain and iterate on the service independently.

With every workload now on AWS and defined as code, the client's intelligent marketplace is set up to integrate more tightly with its platform and to build on its AI capabilities, no longer split across clouds but ready to support whatever the business takes on next.

AWS Stack

Amazon ECS

On Fargate for running the AI service and Qdrant as serverless containers that scale on demand.

Amazon EFS

For persistent, encrypted storage backing the Qdrant vector database.

Amazon ECR

And AWS Cloud Map for container image hosting and private service discovery.

AWS Secrets Manager

And IAM for secure, least-privilege handling of credentials and access.

Amazon CloudWatch

For infrastructure and application monitoring, alarms, and dashboards, replacing Datadog.

AWS CloudFormation

For defining the whole environment as code.

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