Today marks a pivotal moment for AI infrastructure as Cloudian announces a groundbreaking integration that fundamentally simplifies how organizations deploy and scale AI inferencing workloads. Our new unified platform combines the proven performance of HyperStore object storage with Milvus, the world’s leading open-source vector database, eliminating the complexity and bottlenecks of managing separate storage and inferencing systems.
The AI Inferencing Revolution is Here
AI inferencing represents the “production phase” of artificial intelligence — the moment when trained models transition from development labs to real-world applications that millions of users depend on daily. Whether it’s a search engine generating personalized results, a streaming service recommending movies, or a chatbot answering customer questions, inferencing is the engine that powers the AI experiences reshaping our world.
But here’s what many organizations discover: successful AI inferencing isn’t just about having powerful models. It’s about having the right infrastructure to support the massive data requirements that modern AI systems demand. Recent industry data reveals that KV cache volumes for reasoning models are projected to reach 2-5TB per concurrent user by 2026 — a staggering 20-50x increase compared to traditional inferencing models.
Why Storage is the Silent Hero of AI Inferencing
Traditional thinking treats storage as a passive repository, but in AI inferencing workflows, storage becomes the performance foundation that determines success or failure. Modern AI systems require rapid access to vast amounts of contextual data, vector embeddings, and model states — all while maintaining the low latency that users expect from intelligent applications.
Consider a sophisticated recommendation engine: when a user interacts with your platform, the AI system must instantly access their historical data, retrieve similar user patterns from vector databases, and generate personalized suggestions — all within milliseconds. This demands storage infrastructure that can handle thousands of concurrent data streams with consistent, predictable performance.
The challenge intensifies with Retrieval-Augmented Generation (RAG) workflows, which enhance AI responses by dynamically embedding relevant documents into prompts. These systems can increase data storage requirements by 10-20x while demanding real-time access to maintain conversational flow.
Enter Milvus: The Vector Database Powering Modern AI
Vector databases represent a fundamental shift in how AI systems store and retrieve information. Unlike traditional databases that organize structured data in rows and columns, vector databases like Milvus specialize in storing high-dimensional vectors — mathematical representations of complex, unstructured data like text, images, audio, and video.
Key Storage Integration Points:
- Cloudian HyperStore serves as the unified storage foundation, handling raw data, processed vectors, model artifacts, and metadata
- Milvus runs on auxiliary nodes while leveraging HyperStore for persistent storage of vector indexes and collections
- Data flows seamlessly between storage and compute without the bottlenecks of traditional multi-system architectures
- Parallel processing enables thousands of concurrent similarity searches across massive vector datasets
Milvus, maintained by the LF AI & Data Foundation, has emerged as the world’s most advanced open-source vector database. It enables organizations to store billions of vectors and perform similarity searches in milliseconds, making it the backbone of real-time AI applications across industries. From IKEA and Walmart to PayPal and Salesforce, leading enterprises rely on Milvus to power their AI-driven experiences.
The magic happens through similarity search: when a user query arrives, the system converts it to a vector and uses Milvus to instantly find the most similar vectors in the database. This enables everything from semantic search and recommendation engines to fraud detection and personalized content delivery.
The Cloudian-Milvus Integration: Breaking Down Barriers
Our breakthrough integration eliminates a critical pain point that has long plagued AI infrastructure teams: the complexity and performance bottlenecks of managing separate storage and vector database systems. Instead of wrestling with data movement between disparate platforms, organizations can now deploy a unified solution that delivers exceptional performance while dramatically simplifying operations.
In this integrated architecture, Milvus runs on auxiliary nodes while leveraging the Cloudian HyperStore cluster as its foundational storage layer. This design delivers several transformative advantages:
- Exabyte Scalability: Start with your current needs and grow seamlessly without architectural disruption. Our distributed storage architecture eliminates the scaling bottlenecks that force costly infrastructure overhauls.
- Exceptional Performance: With 35GB/s per node read throughput and NVIDIA GPUDirect RDMA support, we’re demonstrating clear differentiation in Milvus performance. Preliminary testing shows remarkable improvements in inferencing throughput that we’ll detail in an upcoming performance analysis.
- Seamless Integration: Full S3 API compatibility ensures trouble-free operation with all AI tools and frameworks, from LangChain and LlamaIndex to TensorFlow and PyTorch. There’s no vendor lock-in, no proprietary APIs to learn, and no complex integration challenges.
- Enterprise-Grade Foundation: Built-in data protection, multi-tenancy, and security features that enterprise IT teams demand, backed by the reliability that Cloudian customers have trusted for years.
Real-World Impact Across Industries
This unified platform addresses the diverse needs of organizations building the next generation of AI applications:
- AI and ML architects developing RAG systems, recommendation engines, and semantic search applications now have a single platform that eliminates data movement bottlenecks while delivering the latency and scalability their applications demand.
- CTOs and heads of AI at enterprises can finally standardize on infrastructure that scales from pilot projects to production workloads without requiring costly architectural changes or vendor lock-in.
- Platform and infrastructure teams managing data lakes and AI pipelines can consolidate their storage requirements onto a single, unified system that supports vector databases, feature stores, and model repositories simultaneously.
- AI infrastructure vendors and integrators delivering solutions for clients can now offer a proven, scalable backend that eliminates the complexity of managing multiple storage systems.
The Future of AI Infrastructure is Unified
The integration with Milvus represents more than a technical achievement — it embodies our vision of AI infrastructure that adapts to your needs rather than forcing you to adapt to its limitations. As AI continues its rapid evolution from perception models to sophisticated reasoning systems, the infrastructure demands will only intensify.
Organizations that choose unified, scalable platforms today position themselves to capitalize on tomorrow’s AI innovations without being constrained by infrastructure decisions made in isolation. Whether you’re building your first AI application or scaling to support millions of users, this integrated platform grows with your ambitions.
Performance testing continues to demonstrate exceptional results, with comprehensive benchmarks and optimization guidance coming soon. For organizations ready to explore how this unified approach can accelerate their AI initiatives, we’re happy to share preliminary performance data and discuss specific use case requirements.
Getting Started: Simple Configuration, Powerful Results
Despite its sophisticated capabilities, the Cloudian-Milvus integration is designed for straightforward deployment. Detailed configuration instructions ensure that your team can quickly implement and begin realizing the benefits of unified AI infrastructure.
The AI revolution is accelerating, and the organizations that will lead it are those that choose infrastructure capable of evolving with the technology. With Cloudian’s AI inferencing platform, you’re not just solving today’s challenges — you’re building the foundation for tomorrow’s breakthroughs.
