Switchboard Live Performance Optimization

Overview

Switchboard Live, a leading multimodal streaming platform provider, faced significant scaling challenges as their user base grew rapidly. Their platform enables content creators and businesses to simultaneously stream to multiple destinations like YouTube, Twitch, and Facebook Live. With thousands of concurrent streams and growing demand, they needed to dramatically improve their platform's performance and reliability.

Working closely with their engineering team, we conducted a thorough analysis of their infrastructure and identified several critical bottlenecks in their Kubernetes deployment and application architecture. The platform was experiencing high latency, resource constraints, and occasional service disruptions during peak usage.

This case study details how we helped Switchboard Live achieve up to 18x performance improvements through strategic Kubernetes optimization, architecture refinements, and implementation of robust monitoring solutions. The improvements not only enhanced platform stability but also reduced infrastructure costs while supporting their continued growth.

Challenge

• Platform experiencing performance bottlenecks under load
• Limited visibility into system performance metrics
• Inefficient resource utilization
• Scaling issues during peak streaming periods

Solution Architecture

Kubernetes Infrastructure Improvements

We implemented several key improvements to the Kubernetes infrastructure:

• Helm Charts - Created standardized deployments
• Prometheus - Comprehensive metrics collection
• Grafana - Performance visualization
• Custom Metrics - Application-specific monitoring

Architecture Optimization

Separation of Concerns

We split the application into distinct components:

1. API Nodes

   • Handle client requests
   • Manage streaming sessions
   • Route control plane traffic

2. Worker Nodes

   • Process video streams
   • Handle media transcoding
   • Manage stream distribution

Performance Monitoring

Implemented comprehensive monitoring:

• Application Metrics

  • Request latency
  • Stream processing time
  • Resource utilization
  • Error rates

• System Metrics

  • CPU/Memory usage
  • Network throughput
  • Disk I/O
  • Pod health

Results

The optimization efforts delivered dramatic improvements:

• 2x overall platform performance improvement
• Up to 18x improvement in specific streaming operations
• 50% reduction in resource costs
• 99.99% platform availability

Key Benefits

1. Enhanced Performance

   • Faster stream processing
   • Reduced latency
   • Better resource utilization

2. Improved Scalability

   • Independent scaling of components
   • Better handling of traffic spikes
   • Optimized resource allocation

3. Better Visibility

   • Real-time performance metrics
   • Early problem detection
   • Data-driven decision making

Implementation Process

1. Assessment

   • Collected baseline metrics
   • Identified bottlenecks
   • Analyzed resource usage

2. Optimization

   • Created Helm charts
   • Implemented monitoring
   • Separated workloads

3. Validation

   • Load testing
   • Performance benchmarking
   • Metric verification

Lessons Learned

1. Data-driven approach was crucial for identifying issues
2. Separation of workloads significantly improved scalability
3. Comprehensive monitoring enabled proactive optimization
4. Helm charts standardized deployments and reduced errors

Conclusion

Through careful optimization of both infrastructure and architecture, we helped Switchboard Live achieve significant performance improvements. The new monitoring capabilities and separated architecture provide a foundation for continued optimization and scaling as their platform grows.