As per the latest 451 Research’s industry-leading analysis, around 94% of AI adopters are using or plan to use containers within one year. Undoubtedly, containers are revolutionizing a variety of workloads across the enterprise IT space, and AI adopters seem keen on using this technology to improve their AI workloads. 55% percent say they are currently using containers to deploy their AI models into production, and a further 39% plan to do so within the next year. Furthermore, more than half (56%) of companies that plan to adopt AI in the next year say they will do so using containers. AI adopters are intrigued by the benefits of scalability and speed that containers can bring to their AI deployments. In this talk I am going to showcase how Docker containers are used to implement object detection and analytics using RedisEdge Stack.

In this talk you will understand the power of Azure DevOps which helps in automating build & release process faster for multiple languages & framework.

This talk will serve as a practical introduction to Distributed Tracing. We will see how we can make best use of open source distributed tracing platforms like Hypertrace with Azure and find the root cause of problems and predict issues in our critical business applications beforehand.

DevOps spearheads automation within the software pipeline and breaks silos between the team - creating a harmonious and collaborative environment. GitOps - DevOps on GitHub is now a reality. In this session we will learn how to set up a fully automated stack on GitHub with its in-house CI/CD tool - GitHub Actions, paired with build tools like NPM, Package Manager - GitHub Packages, Container Engine - Docker paired with third-party tools like HashiCorp Terraform for Infrastructure Automation and Ansible for Configuration Management.

Kubernetes is the most popular container orchestration platform. It helps to easily deploy & scale applications. There are times when we need to scale services based on external events such as messages in queue. In such scenarios, Kubernetes-based Event Driven Autoscaling (KEDA) project helps to scale containers to and from zero. Join this exciting session to see how we can scale a message consumer based on the number of messages in the RabbitMQ queue.

In today's times where the data is spread across clouds it would be a boon to have features to consolidate data to a cloud of choice. This feature would help users to analyze data faster spread across various clouds and eliminate any network latency in accessing data at the same time. This is possible,using a platform like SODA that enables users to access multiple clouds at the same time. Hear us talk about a few such scenarios and demonstrate data migrations between clouds using SODA.

In this talk, We will kick of with discussing about serverless computing and later move to solve a problem statement by refactoring an existing Web API written in .Net Core using Web API to a Serverless API with the help of Azure Functions. The Serverless API will be able to do CRUD operations by connecting to Azure SQL. Finally we will deploy this application to Azure for everyone to test it.

I would talk about how students can become a part of Microsoft Learn Student Ambassadors Program, how students can use Microsoft Learn and setting up an Azure account and Benefits of being of MLSA.