Make Your AI Search Always-On with Zilliz Global Cluster
About this webinar
Mission critical AI applications require highly available search infrastructure. They need low-latency access globally, resilience during regional failures, and fast failover during disaster recovery.
In this webinar, we will introduce Zilliz Cloud Global Cluster that powers production AI systems with high availability and low latency. You’ll learn how to deploy global clusters, its architecture, and how it automatically handles data replication and regional failures.
What You’ll Learn
- Live demos of global cluster deployment, auto sync across regions, and failover process
- How global clusters use a primary and read-only secondary architecture provide more resilience than single region deployment
- How read traffic is routed to the nearest healthy region
- What happens during failover and how write switching works
- How to think about RPO, RTO, and operational trade-offs
AMA Session
You’re welcome to ask your questions live by turning on your mic, or simply drop them into the chat. This is a chance for you to bring up your own use cases, challenges, and ideas, and have a direct conversation with the Zilliz team.
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Meet the Speaker
Join the session for live Q&A with the speaker
Jiang Chen
Director of Technical GTM
Jiang is currently Director of Technical GTM at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.
Rohit Nijhawan
Solutions Architect, Zilliz
Rohit Nijhawan is a Solutions Architect at Zilliz. He works closely with enterprise customers in many verticals, enabling the design and implementation of use cases in GenAI, Recommender Systems, and semantic search using the Zilliz Cloud Vector Database. He is a seasoned big data and NoSQL architect and has worked at Databricks, Cloudera, and MongoDB. He also doubles as an advocate for developers, helping launch and test Proofs of Concept with Milvus.