View a markdown version of this page

TELCOREL03-BP02 Design a stateful, session-aware load balancing solution for cloud network functions (CNFs) to enable scaling and resilience - Telco Lens
Implementation guidance Resources

TELCOREL03-BP02 Design a stateful, session-aware load balancing solution for cloud network functions (CNFs) to enable scaling and resilience

Cloud network functions (CNFs) such as AMF, SMF, and UPF in 5G architectures are typically designed to be horizontally scalable. However, these components maintain subscriber session state, and scaling events (up and down) can disrupt session continuity, leading to call drops, session re-establishment delays, or degraded user experience. To address this challenge, it is recommended to design a stateful, session-aware load balancing solution for CNFs that enables seamless scaling and resilience. This can be achieved by collaborating with the CNF vendors and relevant CNF communities to explore how cloud-based services can be adapted to support seamless session handling.

Desired outcome:

  • Provide a highly available and scalable load balancing solution that can maintain session state for telco network functions deployed as cloud-based workloads.

  • Verify seamless failover and state preservation during scaling events or instance failures, minimizing service disruptions for end users.

  • Enable efficient load distribution and resource utilization by intelligently routing traffic based on current capacity and workload patterns.

  • Integrate with Kubernetes-based deployment models and service abstractions used by telco CNFs.

  • Deliver carrier-grade performance and availability to meet the stringent requirements of telco control plane and signaling workloads.

Implementation guidance

Design a stateful load balancing architecture that maintains session state and seamless failover, leveraging in-memory data stores or distributed databases to replicate session data across instances. Integrate the load balancing solution with Kubernetes-based cloud-based network functions, providing a standardized interface and allowing CNFs to configure load balancing parameters. Implement a highly available and fault-tolerant design, with automated failover and dynamic scaling capabilities. Enhance observability and monitoring to maintain visibility into the load balancing system's performance, errors, and configuration changes. Automate the deployment and lifecycle management of the load balancing solution to verify consistency.

Implementation steps

  • Design a stateful load balancing architecture:

    • Use AWS application load balancing services, such as Application Load Balancer (ALB) and Network Load Balancer (NLB), to handle the traffic routing and load distribution.

    • Implement session stickiness and connection tracking mechanisms to maintain session state and verify seamless failover.

    • Utilize Amazon ElastiCache (For example, Redis) or Amazon DynamoDB to store and replicate session data across the load balancing instances.

  • Integrate with Kubernetes-based CNFs:

    • Develop a Kubernetes Ingress Controller or Gateway API implementation to provide a standardized interface for telco CNFs to leverage the stateful load balancing solution.

    • Implement custom annotations or custom resource definitions (CRDs) to allow telco CNFs to configure load balancing parameters, such as session timeouts and stickiness.

    • Verify the load balancing solution can discover and register telco CNF instances through Kubernetes service discovery mechanisms.

  • Optimize for carrier-grade performance:

    • Configure the load balancing instances to leverage high-performance AWS instance types, such as C5 or M5 families, to handle the throughput and latency requirements of telco workloads.

    • Use AWS Nitro System-based instances for optimized networking and CPU performance.

    • Integrate with AWS Direct Connect and AWS Global Accelerator to provide low-latency connections and Regional load distribution.

  • Implement high availability and fault tolerance:

    • Deploy the load balancing solution across multiple AWS Availability Zones for redundancy and resilience.

    • Configure health checks, automated failover, and connection draining to verify seamless failover during instance or Availability Zone failures.

    • Leverage AWS Auto Scaling to dynamically scale the load balancing capacity based on traffic patterns and resource utilization.

  • Enhance observability and monitoring:

    • Integrate the load balancing solution with Amazon CloudWatch for comprehensive monitoring of performance metrics, error rates, and health status.

    • Implement Amazon CloudWatch dashboards and alarms to provide visibility into load balancing behavior and trigger alerts for anomalies or potential issues.

    • Use AWS CloudTrail and AWS Config to track configuration changes and maintain an audit trail of load balancing activities.

  • Automate deployment and lifecycle management:

    • Package the load balancing solution as an AWS CloudFormation template or Terraform configuration for consistent and repeatable deployment.

    • Integrate the solution with AWS CodePipeline and AWS CodeBuild for automated CI/CD workflows, including testing and deployment.

    • Use AWS Config and AWS Systems Manager to manage the configuration of the load balancing components and verify adherence with defined policies.

Resources

Key AWS services: