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AI-Driven Analytics Software

Optimizing Cloud Costs & Infrastructure Efficiency

WhiteCup leverages cloud-based infrastructure to power its CRM and BI solutions, enabling businesses to streamline operations and gain actionable insights. However, increasing cloud costs were impacting overall efficiency and profitability.

Client:
Whitecup

WhiteCup leverages cloud-based infrastructure to power its CRM and BI solutions, enabling businesses to streamline operations and gain actionable insights. However, increasing cloud costs were impacting overall efficiency and profitability. By implementing a structured cost optimization strategy, WhiteCup significantly reduced its cloud spend while improving system performance and scalability.

πŸ“Œ Industry: CRM, BI, AI-Driven Analytics Software

πŸ“Œ Key Technologies / Platforms: AWS (EC2, RDS, S3, Lambda), Kubernetes, Terraform, Cost Explorer, Auto Scaling

The Challenge

As WhiteCup expanded its cloud-based offerings, its AWS infrastructure costs surged due to: Β 

βœ” Underutilized resources – Several EC2 instances and RDS databases were over-provisioned.

βœ” Lack of auto-scaling – Servers ran 24/7, even during non-peak hours.

βœ” Unused storage & snapshots – Old snapshots and unoptimized S3 storage led to unnecessary costs.

βœ” Expensive licensing – WhiteCup used on-demand pricing instead of reserved instances.

These inefficiencies resulted in unnecessary cloud expenses and lower cost predictability.

The Solution: Cost Optimization Strategies Implemented

1️⃣ Compute Cost Optimization (EC2 & RDS)

  • Right-Sized Instances: Identified oversized EC2 and RDS instances and adjusted them based on actual usage.
  • Reserved Instances & Savings Plans: Migrated from on-demand to 1-year Reserved Instances (RIs) and Compute Savings Plans.
  • Auto-Scaling Implementation: Enabled EC2 Auto Scaling based on traffic patterns, reducing idle resource costs.

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2️⃣ Storage Optimization (S3 & Snapshots)

  • S3 Lifecycle Policies: Moved infrequently accessed data from S3 Standard to S3 Intelligent-Tiering.
  • Unused Snapshots Cleanup: Automated deletion of old EBS snapshots.
  • Data Compression & Deduplication: Compressed large BI logs before storing them in S3.

3️⃣ Cost Monitoring & Governance

  • AWS Cost Explorer & Budgets: Β 
  • Set up automated alerts for cost anomalies.
  • Implemented tag-based cost tracking for each product team.
  • CloudWatch Cost Savings: Β 
  • Identified and removed unused metrics to reduce CloudWatch costs.
  • FinOps Best Practices: Established monthly cost review meetings to ensure continued savings.

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Impact & Results

βœ” πŸ’° Significant overall cost reduction on AWS by 25 %

βœ” πŸš€ Optimized EC2 & RDS instances through right-sizing & reservations

βœ” πŸ“‰ Lowered storage costs by optimizing S3 & snapshots

βœ” πŸ“Š Reduced CloudWatch costs by eliminating unused metrics

These strategies helped WhiteCup improve cloud efficiency, reduce waste, and optimize costs while maintaining high performance.

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