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Dynamic Server Capacity Optimization for Sales Engagement Platform
  1. case
  2. Dynamic Server Capacity Optimization for Sales Engagement Platform

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Dynamic Server Capacity Optimization for Sales Engagement Platform

knubisoft.com
Information technology
Advertising & marketing
Telecommunications

Inefficient Server Resource Utilization

The client's sales engagement platform maintained fixed cloud server capacity regardless of usage patterns, resulting in excessive infrastructure costs while requiring constant high availability for video conferencing and real-time data processing workloads.

About the Client

Innovative US-based IT company developing sales engagement and management solutions that integrate content, communications, and actionable insights

Optimize Server Usage and Reduce Operational Costs

  • Implement dynamic server scaling based on real-time demand
  • Reduce cloud infrastructure costs by 40-60%
  • Maintain platform stability during peak usage periods
  • Improve resource allocation visibility through monitoring integration

Core System Requirements

  • Service discovery for server capacity metrics collection
  • Custom load balancer with dynamic request routing
  • Auto-scaling orchestration for server clusters
  • Real-time performance monitoring dashboard
  • Historical usage pattern analysis for capacity planning

Technology Stack

Java
Spring Framework
AWS Cloud Infrastructure
Docker
Kubernetes
Prometheus
Grafana
MySQL

Third-Party Integrations

  • Datadog Monitoring
  • FFmpeg Media Processing
  • Selenium Test Automation

System Quality Attributes

  • Horizontal scalability to handle 10x traffic spikes
  • 99.99% system availability SLA
  • Sub-second request processing latency
  • Enterprise-grade security compliance
  • Self-healing system recovery capabilities

Business Value Realization

Enables cost-effective scaling through demand-based resource allocation while maintaining optimal performance levels for mission-critical sales engagement operations, with measurable reductions in cloud infrastructure expenditure and improved operational efficiency metrics.

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