Azure Cosmos DB Conf 2026 – Call for Proposals

Share your real‑world engineering story. Teach the community. Shape the future.

Azure Cosmos DB Conf 2026 is now accepting 25‑minute, demo‑driven technical session proposals. We’re looking for deep, practical talks that show how you solved real problems using Azure Cosmos DB, Azure DocumentDB, or OSS DocumentDB—including modernizing workloads and building multi‑cloud, GenAI/agentic AI, and high‑scale applications. 

Submission Guidelines

Speaker & Submission Rules

• Each individual may submit up to three (3) proposals.
• Sessions may include multiple speakers, including teammates or customer collaborators.
• We strongly encourage submissions from speakers across all backgrounds, identities, experience levels, and regions. 

Session Format

All accepted sessions are 25‑minute technical talks that must include a demo.

Every proposal must demonstrate: 

1. A Real Developer Problem

Examples:

• scale, latency, or cost challenges
• data modeling or consistency tradeoffs
• migration complexity
• multi‑cloud operational issues
• AI challenges such as: AI Orchestration: Managing state and memory for long-running multi-agent workflows, Vector Performance: Balancing recall accuracy with query latency in high-scale RAG systems, Token/Cost Efficiency: Implementing intelligent caching or data tiering to reduce LLM operational costs. 

2. A Working Solution 

• Azure Cosmos DB
• Azure DocumentDB
• OSS DocumentDB
• or combinations across cloud environments and platforms.

Include:

• architecture and reasoning
• SDK usage patterns
• tradeoffs and decisions
• real code paths and data flows 

3. A Strong Demo Plan 

Your session must include a live, repeatable demo that clearly shows:

• the problem
• the solution
• the payoff for developers trying the same thing

This event focuses on practical, real‑world engineering lessons—talks that show how you solved a problem, not just high‑level concepts.

Topics We Want to See in 2026 

1. Intelligent Applications with AI + Azure Cosmos DB/Azure DocumentDB

• Vector search with Azure Cosmos DB
• LLM integration using Microsoft Foundry/Azure OpenAI Service
• RAG architectures using Microsoft Foundry Agent Framework, Semantic Kernel, LangChain, LlamaIndex
• Hybrid operational‑and‑generative AI patterns
• Building AI applications at scale on multi‑cloud or polyglot architectures 

2. Design Patterns & Best Practices

• NoSQL data modeling for efficenty
• Partitioning for scalability
• Multi-region for availability
• Performance tuning and cost optimization
• Observability and debugging patterns

3. Moving Workloads, Modernizing Applications, and Data Migration

• Migrating monoliths to cloud-native architectures
• Refactoring unscalable relational applications
• Migration strategies, tooling, and schema transitions
• ETL flows and downtime mitigation approaches
• Reducing operational complexity while improving global performance and scalability
• Lessons learned and common pitfalls from real-world migrations
• Migrating from open-source DocumentDB engines to managed Azure DocumentDB or Azure Cosmos DB

4. Multi‑Cloud, Cross‑Cloud & Hybrid Architectures

Show how you’ve used Azure Cosmos DB or Azure DocumentDB in:

• multi‑cloud deployments
• hybrid scenarios
• cloud portability or cloud neutrality strategies
• interoperable data and API patterns
• Real examples shine: the tradeoffs, complexity, and what you learned

5. Innovative Real‑World Use Cases

• We’re looking for detailed, technical stories where Azure Cosmos DB, Azure DocumentDB, or OSS DocumentDB solves a real engineering challenge. These talks should show how the system was built—not just what the industry problem was.
• Your session should clearly articulate:
• The problem: scale, latency, fraud detection, personalization, multi‑region constraints, or data freshness issues.
• The architecture: data model, partitioning strategy, consistency choices, indexing, APIs, or patterns that made the solution work.
• The implementation: live demo of key flows, Change Feed usage, vector search, multi‑agent AI orchestration, or operational pipelines.
• The lesson: what you learned, what you’d do differently, and what other developers can repeat.

Example categories:

• High‑volume transactional systems (retail, banking, logistics)
• Real‑time detection pipelines (fraud, anomaly detection, risk scoring)
• Search, discovery & personalization (recommendation engines, retrieval layers for GenAI / RAG)
• Customer-facing GenAI features (chat, agents, copilots powered by Cosmos DB)
• Agentic & multi‑agent AI systems backed by operational + vector data
• Healthcare, finance, manufacturing, gaming — but with deep technical detail, not industry overviews

These talks must deliver repeatable engineering patterns, not conceptual descriptions. Show the real architecture, the real code, and the real decisions that made it work.

6. Developer Tools, SDKs & Productivity

Deep dives into:

• Python, Node.js, Java, .NET, Rust, Go
• VS Code workflows and debugging
• GitHub‑based CI/CD and automation
• Azure Data Studio extensions
• OSS tooling and frameworks supporting DocumentDB workloads 

Examples from Previous Azure Cosmos DB Confs

Get inspired by past sessions that highlight the kind of practical, demo‑driven engineering stories we love to feature at Azure Cosmos DB Conf: 

• OmniRAG – The Right Way to Do Retrieval Augmented Generation with Azure Cosmos DB
• Cosmos DB as the Backbone for AI‑Enabled Enterprise Applications
• Real‑Time Scoring to Improve Personalization with Adobe Experience Platform 

Why Your Experience Matters

Azure Cosmos DB Conf is about learning from your real engineering work — decisions you made, problems you hit, what surprised you, what you’d do differently, and the practical lessons you can give the next developer. Experience‑driven talks make the biggest impact.

Submit Your Proposal

Bring your expertise, demos, patterns, and lessons learned to thousands of developers worldwide.

We invite you to be part of Azure Cosmos DB Conf 2026 and share your proposals.