Executive Summary

  • Client: An Automobile Manufacturer of real-time navigation and location-based services.
  • Challenge: High infrastructure costs and latency issues with on-premise servers.
  • Solution: A scalable Azure cloud migration strategy with edge computing.
  • Results:
    • 40% reduction in annual infrastructure costs.
    • 50% faster response times for users.
    • 30% growth in active users due to improved service reliability.

“American Chase’s Azure solution made our platform faster, smarter, and more cost-effective.“

 – CTO

Client Background

Who They Are

The client powers navigation for 10M+ users worldwide, offering real-time routing for logistics, ride-sharing, and emergency services. Their mission is to deliver “precision at every mile.”

Pre-Challenge State

  • Struggled with high latency, especially in remote regions.
  • Relied on outdated on-premise servers across three continents.

“Our users demanded real-time accuracy, but our infrastructure couldn’t keep up.“

 – CTO

The Challenge

Pain Points

  1. Costly Infrastructure: $2M+ annual spend on server maintenance and upgrades.
  2. Latency Issues: 3-5 second delays in route calculations impacted user trust.
  3. Scalability Gaps: Couldn’t handle traffic spikes during peak hours or emergencies.

Business Impact

  • Declining user retention due to slow performance.
  • Missed opportunities in emerging markets with unreliable connectivity.

Client Goals

  • Reduce operational costs while improving service speed.
  • Deploy servers closer to end-users for low-latency responses.
  • Scale dynamically during high-demand scenarios.

The Solution

Approach

  • Migrated client’s entire infrastructure to Microsoft Azure, leveraging edge computing and geo-replication.
  • Adopted a phased migration strategy to minimize downtime.

Technologies Used

  • Cloud Platform: Azure Virtual Machines, Azure Kubernetes Service (AKS).
  • Database: Azure Cosmos DB for globally distributed, low-latency data access.
  • Networking: Azure Content Delivery Network (CDN) and Traffic Manager.
  • Analytics: Azure Monitor and Power BI for performance insights.

Key Features

  1. Edge Computing Nodes: Deployed Azure servers in 15+ regions to serve users closer to their location.
  2. Auto-Scaling: AKS dynamically adjusted resources during traffic surges
  3. Cost Optimization: Reserved Azure instances and serverless functions reduced idle resource costs.

Implementation Process

Timeline

  • Phase 1 (Assessment): 3 weeks auditing existing workflows and mapping Azure architecture.
  • Phase 2 (Migration): 4-month transition to Azure, including data replication and testing.
  • Phase 3 (Optimization): Fine-tuned performance with Azure Advisor and Cost Management tools.

Team Structure

  • Cloud architects, DevOps engineers, data migration specialists, and cybersecurity experts.

Overcoming Hurdles

  • Trained Client’s IT team on Azure management tools.
  • Ensured zero downtime during migration using Azure Site Recovery.

Results and Impact

Quantitative Metrics

-40%

Cost Savings

Reduced infrastructure spend from $2M to $1.2M annually.

50%

Faster Response Times

Route calculations in <1.5 seconds globally.

30%

User Growth

Expanded into 5 new markets with reliable edge nodes.

Qualitative Benefits

  • 🌍 Improved accuracy for users in remote areas (e.g., rural healthcare logistics).
  • 🔄 Simplified IT management with centralized Azure dashboards.

“The Azure migration was a win-win: our costs dropped, and our users got faster service.“

 – CTO

Project Snapshot

  • Client: Navigation & Logistics, Global
  • Project Duration: 6 months
  • Technologies: Azure, AKS, Cosmos DB, CDN
  • Key Metric: 40% cost reduction

“American Chase didn’t just move us to the cloud—they redefined how we serve the world.“

 – CTO