How do you deploy multiple machine learning models in production to solve your challenge? How do enable canary releases and A/B testing? How do you make sure a user is always served by the same version of the model?
In this demo heavy session we will show how Containers and Kubernetes, along with Azure DevOps can work for your CI/CD pipeline.
Are you thinking about running SQL Server in Kubernetes and don’t know where to start…are you wondering what you really need to know? Then this is the session for you.
You’ve heard the buzz about containers and Kubernetes, now let’s start your journey towards rapidly deploying and scaling your container-based applications in Azure
A complete overview about SQL Server Big Data Clusters including it's major components and use-cases!
Let’s dive deep into the Kubernetes Architecture and learn how it works under the hood!
Containers are the new virtual machines. They present a new way to deploy, manage, and run SQL Server never possible before. This session will present an internal view of how Docker containers work, how SQL Server runs in them, and how they work in environments such as Kubernetes
In this session Buck Woody explains how Microsoft has implemented the SQL Server 2019 relational database engine in a big data cluster leverages an elastically scalable storage layer that integrates SQL Server and HDFS to scale to petabytes of data storage. You’ll see the three ways you can interact with massive amounts of data: Data Virtualization, Data Marts, and working with a complete Kubernetes Cluster in SQL Server. You’ll also learn common use case scenarios that leverage big data and the SQL server 2019 Big Data Cluster on-premises, in the cloud, and in a hybrid architecture.
Running SQL Server in containers has huge benefits for Data Platform professionals but there are challenges to running SQL Server in stand alone containers. This session will cover what those challenges are and how Kubernetes overcomes them.
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