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Overview

Highworth Capital, a US-based asset management firm, was struggling with rising costs and complex data management on AWS. The company needed a platform that could scale seamlessly, support advanced data analytics, and reduce infrastructure expenses. Bacancy led the migration to Google Cloud with zero downtime, implementing BigQuery for faster insights and building a compliant, scalable environment.

Technical Stack

  • Google BigQuery
  • Google Cloud Storage
  • Google Kubernetes Engine
  • Google Dataflow
  • Google Cloud SQL
  • Terraform
  • Prometheus

    • Industry

    BFSI

  • region

    • Region

    USA

  • project-size

    • Project Size

    Confidential

Highlights

Reduced overall cloud costs by nearly 30% after migration.

Improved data analytics speed and accuracy with BigQuery.

Achieved seamless migration with zero downtime.

Improved audit readiness with Terraform-based IaC.

Challenges & Solutions

Rising infrastructure costs on AWS with unpredictable billing patterns

  • Solution: Our GCP migration consultants move critical workloads to GCP using committed use discounts and preemptible VMs, reducing monthly spend by 28%. At the same time, we worked with finance teams to establish a predictable billing structure that simplified budget planning and improved cost visibility.

Complex data pipelines for real-time portfolio risk analysis

  • Solution: We rebuilt fragmented pipelines on GCP using BigQuery and Dataflow, creating a centralized system that processed large datasets in seconds instead of minutes. This enabled risk teams to run complex calculations in real time and strengthened decision-making for live trading scenarios.

Strict regulatory compliance and data residency requirements

  • Solution: We leveraged GCP’s compliance blueprints and automated policy enforcement to ensure every workload ran in region-specific zones. Data residency checks were integrated into deployment pipelines, giving auditors complete traceability while meeting all financial regulatory standards.

Limited scalability for high-volume trading simulations

  • Solution: We containerized simulation workloads on GCP Kubernetes Engine (GKE) with autoscaling policies, allowing resources to expand instantly during trading peaks. When demand dropped, resources scaled back automatically, cutting idle costs while keeping simulations accurate and responsive.

Lack of visibility into system health across multi-region deployments

  • Solution: We implemented GCP Operations Suite integrated with Prometheus metrics, setting up live dashboards and proactive alerts. This gave operations teams a single pane of glass to monitor multiple regions, detect issues early, and reduce downtime during critical trading hours.

Data synchronization issues during live cloud migration

  • Solution: We implemented Cloud Spanner for HighWorth’s transactional databases and used Google Cloud SQL to replicate data continuously from AWS RDS. Change Data Capture (CDC) pipelines ensured all transactions stayed in sync, allowing portfolio applications to remain fully operational throughout the migration.

Core Features

  • Full workload migration without downtime.
  • Real-time financial analytics with BigQuery.
  • Containerized workloads with auto-scaling.
  • Optimized cost structure with committed use discounts.
  • no.-of-resources

    • No. of Resources

    12

  • time-frame

    • Time Frame

    10 Months

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