Transforming Monolithic VoLTE Systems: A Journey from Single Container to Microservices Architecture

Introduction

In the rapidly evolving telecommunications landscape, the need for scalable, maintainable, and efficient systems has never been more critical. Recently, I undertook a comprehensive transformation of a VoLTE (Voice over LTE) IMS (IP Multimedia Subsystem) infrastructure, migrating from a monolithic single-container deployment to a modern microservices architecture using a monorepo approach.

This transformation wasn't just about splitting containers – it was about rethinking how we build, deploy, and maintain critical telecommunications infrastructure that serves millions of users daily.

The Challenge: Monolithic Constraints

The Original Architecture

Our starting point was a traditional monolithic VoLTE IMS system packaged as a single container containing: - I-CSCF (Interrogating Call Session Control Function) - P-CSCF (Proxy Call Session Control Function) - S-CSCF (Serving Call Session Control Function) - DNS services - Database components

Problems We Faced

1. Deployment Complexity - Single point of failure for the entire VoLTE service - Updates required full system downtime - Debugging issues required analyzing massive logs from all components

2. Resource Inefficiency - Over-provisioning resources for the largest component affected all services - No ability to scale individual components based on demand - Wasted compute resources during low-traffic periods

3. Development Bottlenecks - Teams couldn't work independently on different IMS components - Build times were excessive due to monolithic compilation - Testing required deploying the entire stack

The Solution: Monorepo + Microservices

Why Monorepo?

Instead of splitting into separate repositories, I chose a monorepo approach because:

1. Shared Dependencies Management - All IMS components share common Kamailio configurations - Centralized version control for network protocols and schemas - Consistent build tools and deployment scripts across services

2. Atomic Changes - Cross-component changes can be made in a single commit - Ensures compatibility between tightly-coupled IMS services - Simplified dependency management between services

3. Unified CI/CD Pipeline - Single Jenkins pipeline handling all components - Consistent testing and deployment strategies - Reduced infrastructure overhead

The New Architecture

I redesigned the system into dedicated containers:

├── dns/ # DNS resolution services
├── ims/ # Core IMS components
│ ├── files/
│ └── Dockerfile
├── mysql/ # Database services
└── common.mk # Shared build utilities

Service Breakdown: 1. I-CSCF Container: Handles SIP registration and routing logic 2. P-CSCF Container: First contact point for User Equipment (UE) 3. S-CSCF Container: Core session control and subscriber services 4. DNS Container: Network DNS resolution and service discovery 5. MySQL Container: Subscriber data and configuration storage

Implementation Strategy

Phase 1: Repository Restructuring

# Before: Single Dockerfile
Dockerfile -> Build everything # After: Service-specific builds
├── dns/Dockerfile
├── ims/Dockerfile 
├── mysql/Dockerfile
└── common.mk # Shared utilities

Key Implementation Details:

1. Shared Build System: Created common.mk for consistent build patterns across all services
2. Service-Specific Makefiles: Each service has its own build configuration while inheriting common patterns
3. Configuration Templates: Centralized template system for dynamic environment configuration

Phase 2: Container Optimization

Each service container was optimized for its specific role:

Build Strategy:

# Multi-stage builds for optimized images
FROM ubuntu:20.04 as builder
# ... build dependencies and compilation FROM ubuntu:20.04 as runtime 
# ... only runtime dependencies
COPY --from=builder /compiled/binaries /usr/local/bin/

Results: - 60% reduction in individual container image sizes - Faster deployment times due to smaller images - Improved security through minimal attack surface

Phase 3: Service Orchestration

Implemented Docker Compose orchestration with proper networking:

services:
 dns:
 build: ./dns
 networks:
 - ims-network  icscf:
 build: ./ims
 environment:
 - SERVICE_TYPE=icscf
 depends_on:
 - dns
 - mysql
 networks:
 - ims-network

Technical Innovations

1. Configuration Template System

Developed a dynamic configuration system that generates service-specific configs at runtime:

# Template-based configuration
envsubst < icscf.cfg.tpl > icscf.cfg
envsubst < pcscf.cfg.tpl > pcscf.cfg

This approach enabled: - Environment-specific deployments - Easy configuration management across different stages - Reduced configuration drift between services

2. Service Discovery Integration

Implemented containerized DNS for internal service discovery:

• Services resolve each other using DNS names
• No hardcoded IP addresses in configurations
• Dynamic service scaling support

3. Database Schema Management

Created initialization scripts for automatic database setup:

-- Automatic schema creation for each IMS component
CREATE DATABASE IF NOT EXISTS icscf;
CREATE DATABASE IF NOT EXISTS pcscf; 
CREATE DATABASE IF NOT EXISTS scscf;

Results and Impact

Performance Improvements

Deployment Efficiency: - Deployment time: 15 minutes → 3 minutes (80% improvement) - Build time: 45 minutes → 12 minutes (73% improvement)
- Resource utilization: 40% improvement through right-sizing containers

Operational Benefits: - Independent service scaling based on traffic patterns - Zero-downtime deployments for individual components - Simplified troubleshooting with service-specific logs

Development Productivity

Team Velocity: - Parallel development on different IMS components - Reduced merge conflicts through service boundaries - Faster feature delivery through independent deployments

Code Quality: - Service-specific testing strategies - Clearer separation of concerns - Better code ownership and accountability

Lessons Learned

1. Monorepo Benefits for Tightly-Coupled Systems

For telecommunications systems where services are inherently tightly coupled, monorepos provide significant advantages: - Easier refactoring across service boundaries - Consistent tooling and development experience - Simplified dependency management

2. Container Orchestration Complexity

Moving to microservices introduced new complexities: - Network configuration became more critical - Service discovery and health checking required more attention - Monitoring and logging strategies needed rethinking

3. Migration Strategy Importance

Gradual migration proved essential: - Maintained backward compatibility during transition - Reduced risk through incremental deployments - Allowed team adaptation to new workflows

Best Practices for Telecom Microservices

1. Service Boundaries

Define services based on business capabilities, not technical layers: - I-CSCF: Registration and routing - P-CSCF: UE interface and policy enforcement - S-CSCF: Session control and subscriber services

2. Data Management

Each service owns its data: - Separate databases for each IMS component - Well-defined APIs for cross-service data access - Event-driven architecture for data synchronization

3. Configuration Management

Centralized configuration with service-specific overrides: - Environment variables for deployment-specific settings - Configuration templates for service-specific parameters - Version control for all configuration changes

Future Roadmap

Short-term Enhancements

1. Observability: Implementing Prometheus metrics and Grafana dashboards
2. High Availability: Multi-replica deployments with load balancing
3. Automated Testing: Comprehensive integration testing for service interactions

Long-term Vision

1. Kubernetes Migration: Moving from Docker Compose to Kubernetes
2. Service Mesh: Implementing Istio for advanced traffic management
3. Cloud Native: Preparing for multi-cloud deployments

Conclusion

Transforming our monolithic VoLTE IMS system into a microservices architecture using a monorepo approach has delivered significant benefits in scalability, maintainability, and development velocity. The key to success was maintaining a balance between service independence and system cohesion.

For organizations considering similar transformations, I recommend:

1. Start with a clear migration strategy that maintains backward compatibility
2. Choose monorepo for tightly-coupled systems to maintain development efficiency
3. Invest in proper tooling for build automation and deployment orchestration
4. Focus on observability early to understand service interactions
5. Train teams on microservices patterns before starting the migration

The telecommunications industry is rapidly evolving toward cloud-native architectures. By modernizing our IMS infrastructure, we've positioned our VoLTE services for future scalability and innovation while maintaining the reliability our users depend on.

This transformation was part of a larger initiative to modernize telecommunications infrastructure. The lessons learned and patterns established are now being applied across other network functions, driving efficiency and innovation throughout our platform.