The Cloud + AI Conference is a community focused event by and for the cloud community.

The Atlanta Cloud + AI Conference draws upon the expertise of local and regional administrators, architects, and experts who come together to share their real-world experiences, lessons learned, best practices, and general knowledge with other interested individuals.

• AI Applications & Intelligent Systems
  • LLM-powered applications
  • Retrieval Augmented Generation (RAG)
  • AI copilots and developer assistants
  • AI agents and multi-agent systems
  • Prompt engineering strategies
  • Tool-using AI systems
  • AI application evaluation
  • Guardrails and hallucination mitigation
• AI Infrastructure & Model Operations
  • Model deployment platforms
  • LLM inference optimization
  • GPU infrastructure and scheduling
  • AI workload orchestration
  • Model serving architectures
  • AI observability
  • Model performance monitoring
  • Cost-efficient inference
• Data Platforms for AI
  • Vector databases and embedding pipelines
  • Lakehouse architectures
  • Streaming data platforms
  • Feature stores
  • Data quality and validation
  • Metadata and lineage
  • Data governance
• Cloud Native Architecture
  • Microservices architecture
  • Event-driven systems
  • API-first architecture
  • Service mesh adoption
  • Stateful cloud-native systems
  • Workflow orchestration
  • Distributed consistency patterns
  • Internal developer platform architectures
  • Golden paths and platform design patterns
• Kubernetes & Workload Orchestration
  • Kubernetes architecture
  • Cluster scaling strategies
  • Multi-cluster operations
  • Operator patterns
  • Scheduling and resource management
  • GPU scheduling for AI workloads
  • Platform networking
  • Self-service Kubernetes platforms
• Serverless & Event Platforms
  • Function-as-a-Service architectures
  • Event streaming systems
  • Event-driven microservices
  • Durable workflows
  • Serverless AI inference
  • Async processing architectures

• Cloud Infrastructure & Infrastructure as Code
  • Infrastructure as Code patterns
  • GitOps workflows
  • Immutable infrastructure
  • Multi-cloud architectures
  • Resource provisioning automation
  • Cloud networking design
  • Storage and compute optimization
  • Self-service infrastructure platforms
• Observability, Reliability & SRE
  • Observability platforms
  • OpenTelemetry pipelines
  • Distributed tracing
  • Service Level Objectives (SLOs)
  • Incident management
  • Chaos engineering
  • Debugging production systems
  • Developer productivity metrics
• Security, Identity & AI Safety
  • Zero trust architecture
  • Identity and access management
  • Secrets management
  • Software supply chain security
  • Runtime threat detection
  • AI model security
  • Prompt injection defenses
  • AI governance and compliance
• Multi-Cloud, Edge & Hybrid Systems
  • Hybrid cloud architecture
  • Edge computing platforms
  • IoT platforms
  • Multi-cloud orchestration
  • Edge AI inference
  • 5G-enabled distributed workloads
• Professional Development & Soft Skills
  • Career management and mentorship
  • Team building and leadership
  • Starting or running a tech consulting business
  • Resume building and interview preparation
  • Public speaking and presenting
  • Effective communication for engineers
  • Managing organizational change
  • Leading cloud and AI transformations
• Cloud & AI Foundations (Student / Beginner Track)
  • Introduction to cloud computing
  • Containers and Kubernetes basics
  • Introduction to AI and machine learning
  • Building your first cloud application
  • Prompt engineering fundamentals
  • DevOps basics and CI/CD
  • Git and collaborative development
  • Career paths in cloud and AI
  • Building a technical portfolio