Client

ReachMobi
A fast-growing digital marketing and audience engagement company operating large-scale data pipelines, high-traffic APIs, and cloud workloads across AWS.

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Challenge

ReachMobi’s platform was scaling rapidly, but so were its AWS expenses and operational bottlenecks. Teams were dealing with:

• Rising cloud infrastructure costs with limited visibility
• Underutilized EC2 instances and oversized clusters
• Expensive on-demand compute patterns that could be optimized
• Redundant or inefficient data pipelines
• Manual processes that slowed deployment and maintenance
• Logging, alerting, and monitoring gaps that made optimization difficult

The company needed a full cloud cost strategy, system-wide automation improvements, and a more efficient engineering workflow.

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Solution Delivered

1. $2.4 Million Annual AWS Cost Optimization

I performed a deep audit of ReachMobi’s AWS usage and re-architected high-cost services to reduce waste while increasing performance. Key actions included:

EC2 & Compute Optimization

• Identified oversized, underutilized instances
• Moved workloads from on-demand to reserved & spot where appropriate
• Consolidated services and reduced cluster sprawl
• Right-sized auto-scaling groups based on real usage patterns

S3, Redshift & Data Storage Optimization

• De-duplicated S3 buckets and removed cold data
• Transitioned data to lower-cost tiers where possible
• Tuned Redshift clusters to reduce compute hours and improve performance

Load Balancing & Traffic Routing

• Reduced unnecessary ALBs and streamlined routing
• Optimized request flows to eliminate redundant compute

Monitoring & Cost Governance

• Implemented cost dashboards
• Added automated alerts for abnormal spending
• Built forecasting models for predictable cloud budgeting

Total result: ~$2.4 million in annual savings without sacrificing performance.

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2. Workflow Automation & System Reliability Improvements

Beyond cost savings, I helped ReachMobi optimize engineering workflows and backend operations through automation and architectural improvements.

Backend System Improvements

• Automated recurring operational tasks
• Added structured logging and distributed tracing
• Improved CI/CD pipelines for faster deployments
• Rebuilt microservices with cleaner, more scalable .NET patterns
• Eliminated repeated manual code deployments and nighttime maintenance tasks

Data Pipelines & API Optimization

• Refactored high-traffic microservices to reduce latency
• Improved performance of scheduled data ingestion jobs
• Reduced call frequency and unnecessary compute
• Added retry logic, failover strategies, and better error handling

Error Reduction

• Eliminated numerous production issues caused by manual triggers
• Built self-healing or automatically restarting jobs
• Added monitoring dashboards to detect anomalies early

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Results

🔹 $2.4M Annual AWS Savings

Cloud cost efficiency increased dramatically through right-sizing, deletion of waste, compute restructuring, and storage optimizations.

🔹 Improved Performance & Faster Deployments

Infrastructure changes resulted in:

• Faster API responses
• More stable pipelines
• Reduced on-call burden

🔹 50–70% Reduction in Manual Ops Work

Automation removed countless wasted hours across engineering teams.

🔹 Scalable Cloud Architecture for Future Growth

ReachMobi now has:

• Predictable cloud costs
• A more efficient development pipeline
• A healthier engineering culture and workflow

🔹 Zero Impact on Production Reliability While Cutting Costs

All savings came without degrading customer experience.

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Technologies & Tools Used

• AWS (EC2, S3, Redshift, Lambda, CloudWatch, EKS/ECS)
• C# / .NET 6–8 microservices
• Cost Explorer & AWS Budgets
• CI/CD pipelines (GitLab)
• Observability: CloudWatch, custom logging frameworks, dashboards

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Impact Summary

I helped ReachMobi transform its cloud cost structure and engineering workflows, delivering $2.4 million in recurring savings, eliminating redundant processes, and improving system reliability. The result is a leaner, faster, and more scalable platform that supports high-growth operations without runaway AWS expenses.