Guaranteed Rate - Flexiana
Flexiana.com
Guaranteed Rate Software Development

Guaranteed Rate is a leading digital mortgage provider.

Services we provided:

DevOps / Infrastructure Engineering
Back-end Development (Clojure-based Services)
Infrastructure Automation

Technologies used:

  • Infrastructure: Terraform, AWS EKS, AWS IAM, KOPS, Vault, Docker
  • Backend: Clojure (clojure.test), PostgreSQL, Redis, DynamoDB, Elasticsearch, Amazon S3
  • CI/CD: GitHub Actions

About Guaranteed Rate

Guaranteed Rate is a leading U.S. residential mortgage company specializing in digital mortgage solutions. Their platforms streamline loan approvals, compliance, and document management while handling large-scale, secure workloads across multiple environments.

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Application Architecture:

1. Infrastructure Modernization: KOPS to EKS Migration

The project involved migrating Clojure-based services from KOPS-managed Kubernetes clusters to Amazon EKS to improve scalability, reliability, and operational efficiency.

Key Challenges & Solutions:

Dark Deploy Strategy:

  • Deployed services to EKS without immediate traffic cutover, ensuring zero downtime.
  • Validated performance and stability before full migration.
Multi-Environment Support:
  • Development → Staging → Production rollout with Terraform-managed infrastructure.
  • Configuration via Vault for secrets and environment variables.
CI/CD Pipeline:
  • GitHub Actions automated builds, testing, and deployments.
  • OIDC-based AWS authentication for secure role assumption.
  • clojure.test suites for post-deployment validation.
Results:
  • ✅ Zero-downtime migration to EKS
  • ✅ Reduced operational overhead and long-term costs
  • ✅ Improved scalability with AWS-native features
2. Automated Loan Data Deletion Service

A Clojure-based service was developed to orchestrate the safe removal of loan records across interconnected systems, preventing orphaned data or compliance violations

Key Components:
Dependency Validation:
  • Pre-deletion checks to ensure no broken relationships between services.
Service-Specific Logic:
  • Custom modules for different storage systems (PostgreSQL, DynamoDB, S3, Elasticsearch).
Resilience & Observability:
  • Retry queues for failed deletions.
  • Audit logging for compliance tracking.
Economic Impact:
  • Retry queues for failed deletions.
  • Audit logging for compliance tracking.
Economic Impact:
  • Saved thousands monthly by eliminating redundant cloud storage costs.

Technical Stack:

  • Clojure for backend logic (reusable across services).
  • Vault for secure credential management
  • GitHub Actions for CI/CD.
Environments & Deployment

  • Development: Initial EKS migration and internal testing.
  • Staging: Regression and integration validation.
  • Production: Rollout after staging approval.
Deployment Pipeline:

  • Build: Docker images generated from project.clj.
  • Test: Automated clojure.test suites.
  • Deploy: Terraform for infrastructure, GitHub Actions for orchestration.
  • Validate: Dark deploys and QA coordination.
Technologies & Libraries Backend (Clojure):

  • Duct (application architecture)
  • HugSQL (PostgreSQL interaction)
  • clj-http (API calls)
  • Vault-clj (secrets management)
Infrastructure:

  • Terraform (AWS provisioning)
  • KOPS → EKS Migration
  • Vault (secrets management)
Testing & QA:

  • clojure.test (unit/integration tests)
  • GitHub Actions (CI/CD)
  • Observability: Logging, metrics, and retry mechanisms.
Results & Impact

  • ✅ Successful EKS migration with no service disruption.
  • ✅ Automated, compliant data deletion reducing storage costs.
  • ✅ Unified CI/CD with GitHub Actions and Terraform.
  • ✅ Future-ready infrastructure for scaling mortgage services.
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