As generative AI (GenAI) platforms scale to support enterprise-grade workloads, authentication and authorization (A&A) become critical components for ensuring security, compliance, and efficient resource management. Modern AI platforms, such as the SAP AI infrastructure, leverage CNCF (Cloud Native Computing Foundation) tools to address these challenges. This article explores the technical intricacies of A&A in GenAI platforms, focusing on scaling challenges, CNCF tool integration, and practical solutions derived from real-world implementations.
The SAP AI infrastructure is structured into three core modules: training, serving, and GenAI. These modules rely on a robust CNCF ecosystem to manage scalability and security:
The CNCF tools—Istio, Gardener, Argo Workflows, and KServe—form the backbone of this architecture, enabling horizontal scaling, fine-grained access control, and dynamic resource allocation.
Problem: High-latency JWT parsing (60ms) under load limited request throughput (<20 req/s) due to reliance on Lure Filter and Go SDK.
Solution: Offloaded JWT parsing to an external gRPC service using Envoy, enabling native Go processing for improved performance.
Lesson: While Envoy Filters suffice for low-load scenarios, high-throughput systems require external processing to avoid bottlenecks.
Problem: Managing per-tenant JWKS URIs via Istio Authorization Policies led to excessive Sidecar resource consumption (16GB memory + 5 cores) and latency.
Solution: Externalized policy logic using OPA (Open Policy Agent) with database caching to reduce Sidecar overhead.
Lesson: Centralized policy engines like OPA are essential for managing large-scale authorization rules efficiently.
Problem: Thousands of Virtual Services for LLM subscriptions caused Envoy resource exhaustion and increased latency.
Solution: Replaced Virtual Services with database-backed ID lookups, injecting metadata via request headers.
Lesson: Routing rules should be decoupled from Envoy to avoid linear scalability issues.
Problem: MTLS in logging systems caused instability under high throughput (1TB/day), necessitating trade-offs between security and performance.
Solution: Deployed Ambient to offload encryption to the network layer (L4), eliminating Sidecar overhead.
Lesson: For high-throughput systems, native protocols like Ambient or WireGuard are preferable to Sidecar-based encryption.
Problem: Kubernetes Jobs faced race conditions during CNI initialization and Pod startup, leading to premature Job completion failures.
Solution: Implemented Init Containers for sidecar orchestration or adopted Istio Ambient to eliminate Sidecar containers entirely.
Lesson: Sidecar containers must be carefully synchronized with main containers to avoid resource contention.
Problem: Kserve init containers failed to access S3 due to unstarted sidecars during model downloads.
Solution: Adjusted init container order or transitioned to Ambient mode to ensure sidecar readiness.
Lesson: Initialization sequencing must be explicitly managed via Taints/Tolerations or architectural redesign.
Customization for High Load: Standard CNCF configurations require tuning for high-throughput workloads. For example, Envoy Filters are insufficient for large-scale JWT processing, necessitating external gRPC services.
Sidecar Management: Sidecar containers introduce complexity. Solutions like Init Containers or Ambient mode mitigate risks of resource contention and initialization conflicts.
Security vs. Performance Trade-offs: Temporary fixes (e.g., open-port workarounds) may compromise security. Long-term strategies, such as Ambient encryption or native protocols, are critical for stability.
Policy Externalization: Tools like OPA enable scalable authorization by decoupling policy logic from Sidecar overhead, ensuring consistent enforcement across distributed systems.
Language and Tooling Evolution: Transitioning from Go to Rust for external processors improves stability and performance, reflecting the importance of language choice in CNCF-based architectures.
The challenges of authentication and authorization in GenAI platforms underscore the need for a CNCF-centric approach that balances scalability, security, and operational efficiency. By leveraging tools like Istio, OPA, and Ambient, organizations can address A&A complexities while maintaining high availability and performance. As AI workloads grow, adopting these best practices will be essential for building resilient, enterprise-grade GenAI platforms.