Implementing guardrails around containerized large language models (LLMs) on Kubernetes is crucial for ensuring security and compliance. This involves setting resource limits, using namespaces for isolation, and implementing access controls to mitigate risks associated with running LLMs in a production environment. Properly configured guardrails can help organizations leverage the power of LLMs while maintaining operational integrity.

Kubernetes offers powerful orchestration capabilities for containerized applications, but it lacks security features by default. Users must implement additional security measures to safeguard their Kubernetes environments against potential threats and vulnerabilities. Understanding these risks is crucial for effective deployment and management.

Uber successfully migrated its stateless container orchestration platform from Apache Mesos to Kubernetes, leveraging the industry's standard for enhanced stability and functionality. The migration involved overcoming significant challenges related to scale, integration, and feature parity while implementing custom solutions tailored to Uber's specific requirements. Future blog posts will detail additional migrations within Uber's architecture.