Manish Sharma
Principal Program Manager, Azure Cosmos DB engineering team
Gurugram, India
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Manish Sharma is a Principal Program Manager in Azure Cosmos DB engineering team. He has an experience of 19 years and have experience in architecting high volume/large scale databases ranging from RDBMS, NoSQL & BigData. Currently, he is responsible for Technological product adoption in India & APAC.
He has authored a book titled “Cosmos DB for Mongo Developers” published by Apress and also authored on Open Source For You (OSFY). He is a certified Azure Solution Architect, Cloud Data Architect, AWS Sol. Architect, .NET Solution Developer and PMP certified. He is a regular speaker in various technical conferences organized by Microsoft (FutureDecoded, Azure Conference, specialized Webinars) & Community (GIDS, Docker, DPS etc.) for Client-Server, Cloud & Data technologies.
He has expertise in NoSQL (Document data model & Graph Data Model) & Searching technologies e.g. Lucene, Solr, Elastic Search, Azure Search etc. & Cloud e.g. Azure, AWS, Softlayer & OpenStack etc. technologies. He had also worked on JAVA, SPRING, .NET, UWP, Client-Server architecture-based applications, SOA integration projects
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How I have improved the Database performance from 5 seconds to 1 millisecond?
In this session, I will talk about a customer engagement which got started from customer getting 5 seconds against their expected benchmark of 50 milliseconds. I will discuss the optimization pointers and how we implemented them.
Dynamic storytelling and NPC interactions using generative AI & Azure Cosmos DB in game development
In this session, we explore the fusion of generative AI and Azure Cosmos DB within the realm of game development. Dive into the dynamic world of storytelling, where non-player characters (NPCs) evolve beyond scripted roles. Discover how generative AI enhances NPC interactions, adapts to player choices, and breathes life into virtual game worlds.
Building generative AI applications with Azure Cosmos DB and Java
Join us and learn about the versatile vector database capabilities of Azure Cosmos DB with Java. In this session, you’ll discover how the integration of your operational and transactional data with native vector indexing and search functionalities can enrich your generative AI applications at incredible scale. Learn how to build RAG pattern solutions and manage conversational chat histories, by seamlessly connecting with Azure Open AI.
Cosmos DB – Mongo API: Design to get max out of the most powerful service.
Azure Cosmos DB is Microsoft’s globally distributed, horizontally partitioned, multi-model database service. The service is designed to elastically (and independently) scale throughput and storage across any number of geographical regions. Azure Cosmos DB offers guaranteed low latency at the 99th percentile, 99.99% high availability, predictable throughput, and multiple well-defined consistency models. Azure Cosmos DB is the first and only globally distributed database service in the industry today to offer comprehensive Service Level Agreements (SLAs) encompassing all four dimensions of global distributions.
In this session, we will take one use case and design on Mongo API. During the design, the important concepts of Azure Cosmos DB will be touch based to make sure the design performs optimally with minimal cost e.g. partitioning, global distribution, consistency, auto-scaling, cost calculation & optimization options.
Manish Sharma
Principal Program Manager, Azure Cosmos DB engineering team
Gurugram, India
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