Case Study · Cloud Migration

Modernizing an insurance platform: AWS to Google Cloud

Migrating Insurance Samadhan's workloads from AWS to Google Cloud for greater scalability, cost efficiency, and operational resilience.

Customer
Insurance Samadhan
Industry
InsurTech
Migration
AWSGoogle Cloud
AWSmigratingGoogle Cloud
EC2
Compute Engine
Amazon EKS
GKE (multi-zone)
S3
Cloud Storage
MongoDB
Compute Engine (replicated)
Kafka
Managed Kafka
Section 01

About the Customer

Insurance Samadhan
InsurTech

Insurance Samadhan is a leading InsurTech platform specializing in grievance redressal for rejected, delayed, or fraudulent insurance claims. Pursuing a transparent, digital-first, and scalable service, the company set out to migrate its infrastructure from AWS to Google Cloud, improving scalability, reducing operational costs, and lifting performance.

Section 02

Business Requirement

Migrate Insurance Samadhan's platform and workloads from AWS to Google Cloud. Three challenges defined success:

Scalability

Handling a growing user base and data volume was becoming difficult and expensive on AWS.

Cost Optimization

AWS spend was not optimized, prompting a move to a more cost-effective platform.

Seamless Migration

The cutover had to be executed with minimal disruption to live services.

Section 03

Value Delivered

Migrating to Google Cloud translated directly into the outcomes that mattered most, measured against the challenges above.

Cost Optimization
0%
Lower cloud costs

Reduction in infrastructure costs within the first year, based on a comprehensive cost analysis.

Scalability
0%
More scale headroom

Supports a larger user base with no performance degradation.

Performance
0%
Faster responses

Improvement in response times from optimized infrastructure and networking.

Section 04

Recommended Solution

A phased migration to Google Cloud, built around security, performance, and cost-effectiveness.

Infrastructure Migration

EC2 → Compute Engine with Managed Instance Groups; Amazon EKS → multi-zone GKE; S3 → Cloud Storage via Storage Transfer Service. Databases moved to Compute Engine with MongoDB in primary-secondary replication using a backup-and-restore strategy.

Data Migration Strategy

Strict data-integrity validation at every phase, backup-and-restore for databases, and scheduled backups for reliable recovery.

Security & Compliance

AWS→GCP IAM role mapping, Cloud Armor for DDoS and web protection, Security Command Center (Premium), deletion protection on critical databases, and a Bastion Host with Pritunl VPN for secure remote access.

Performance Optimization

Auto-scaling Compute Engine, Cloud Functions with Cloud Scheduler to start and stop VMs on schedule, and auto-scaling GKE to absorb load spikes without disruption.

Application Integration

AWS → Google Cloud Managed Service for Apache Kafka for managed, highly available event streaming; Elastic Load Balancers → Cloud Load Balancing.

Section 05

Architecture

Technology Stack07
PythonMongoDB (replication)GrafanaPrometheusLokiPromtailKafka
GCP Services Used16
VPCIAMCompute EngineCloud FunctionsFilestoreGKECloud Load BalancingCloud ArmorCloud KMSArtifact RegistryCloud BuildCloud StorageCertificate ManagerManaged KafkaSecurity Command Center (Premium)Cloud Logging & Monitoring
Section 06

Cloud Ambassadors Solution

Cloud Ambassadors executed a phased migration with validation at every step:

Infrastructure Migration

  • Built the GCP landing zone: VPC, subnets, firewalls, and Cloud Armor.
  • Migrated AWS virtual machines with the Migrate to VM service.
  • Stood up GCP Managed Kafka for real-time event streaming.
  • Established AWS↔GCP VPN connectivity for secure data transfer.

Data & Database Migration

  • Moved S3 data to Cloud Storage via Storage Transfer Service.
  • Migrated AWS MongoDB to Compute Engine with primary-secondary replication for high availability.
  • Validated data integrity after each migration phase.

Compute & GKE Migration

  • Migrated EC2 instances to Compute Engine with replicated configuration.
  • Migrated EKS containers to GKE with proper service configuration.

Monitoring & Logging

  • Cloud Monitoring with alerts on key performance metrics.
  • Grafana and Prometheus configured per client request.
  • Cloud Logging for GKE and Cloud SQL, plus Loki and Promtail for centralized logs.

Testing & Optimization

  • Verified performance and application functionality post-migration.
  • Tested database connectivity and data accessibility from applications.
  • Tuned auto-scaling and monitored usage for cost improvements.
Section 07

Business Outcome

Beyond the headline metrics, the migration produced lasting gains across security, scaling, and cost.

Stronger security posture

Tightly controlled firewalls and customer-managed certificates reduced data-breach risk, backed by GCP's built-in IAM, VPC controls, and encryption.

Elastic, cost-aware scaling

Google Cloud's elastic infrastructure, especially GKE, scales automatically with demand and scales down when idle, improving efficiency and cost.

Further savings ahead

A 1- or 3-year resource reservation was recommended for additional cost savings, making GCP a more cost-effective provider.

Planning a similar migration?

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