Automate & Secure LLM Deployments

Overview

Every day, companies waste thousands of dollars on poorly deployed LLM applications—experiencing downtime, security breaches, and runaway costs that could have been prevented. This comprehensive course teaches you to build automated CI/CD pipelines specifically designed for LLM applications, implement enterprise-grade security controls, and optimize for scale and cost. Through hands-on labs based on real-world scenarios, you'll work with Docker, Kubernetes, Terraform, and cloud platforms to build production-ready systems. Each module includes practical exercises where you'll solve actual deployment challenges faced by companies scaling LLM applications. For DevOps, platform, and AI engineers deploying and operating large-scale LLM systems, with a focus on automation, security, cost optimization, and building reliable, high-performance AI platforms. Learners should have a basic understanding of Docker, APIs, and cloud platforms. Familiarity with CI/CD, Python, and basic security practices is helpful but not required. By course completion, you'll have deployed a secure, scalable LLM platform capable of handling millions of requests while maintaining 99.9% uptime. Perfect for DevOps engineers, platform engineers, and technical professionals ready to operationalize LLM applications.

Syllabus

Automated Deployment Foundations

Build automated CI/CD pipelines for LLM applications using GitHub Actions, Docker containerization, and blue-green deployment strategies. You'll configure workflows that automatically build container images, scan them for vulnerabilities, and deploy them with zero downtime. Through hands-on practice, you'll transform manual deployment processes into reliable automation that builds, scans, pushes, and blue-green deploys LLM applications to production environments.

Security & Compliance Implementation

Implement comprehensive security controls for production LLM APIs using identity and access management, secret management, and automated security scanning. You'll configure least-privilege IAM roles, set up secure secret ARNs for API keys and credentials, and run Trivy scans to confirm zero critical security findings. The module covers LLM-specific security concerns including prompt injection prevention, rate limiting, and audit logging for compliance requirements

Production Monitoring & Scaling

Ensure production reliability and cost efficiency by implementing comprehensive monitoring, automated rollback strategies, and cost optimization techniques for LLM systems. You'll create CloudWatch alarms to track critical metrics, simulate latency spikes to verify automated rollback rules, and configure auto-scaling policies that handle traffic variations. The module also covers cost optimization strategies including response caching, intelligent model routing, and resource management to reduce operational expenses