In this session we will start with a modern app and optimize it for Kubernetes using Azure Kubernetes Service (AKS), In addition to migrating to AKS, we will take advantage of native Azure services like Cosmos DB API for Mongo DB ( in the process comparing options like running dockerized Mongo DB or hosted Mongo DB Atlas). We will also discuss the Kubernetes concepts like service discovery, external services, and service catalog and how they relate to AKS and Cosmos DB interaction. Finally, we will look at Cosmos DB capabilities like the Virtual Network Service Endpoints as a way to secure the traffic between AKS and Cosmos DB.
Leading enterprises are using AI to power innovation across industries, including healthcare, automotive, and finance. In this session, gain insight into how these enterprise AI solutions are implemented using Azure Cognitive Services on Spark and Azure CosmosDB. Cognitive Services on Spark enable working with Azure’s Intelligent Services at massive scales with the Apache Spark distributed computing ecosystem. We will demonstrate how customers like SAP, NASCAR, MediaValet and OpenText are using Custom vision service, Video Indexer, Text analytics, Bing and speech services at cloud scale and how customers like Kroger are able to mitigate privacy and security concerns by deploying cognitive services on-premise as containers.
In this session, Mark explains how blockchains work, including how they use hashes, transactions, blocks and proof-of-work consensus algorithms to build distributed ledgers. He presents the capabilities of some of the most common blockchain networks, then describes how the Confidential Consortium Framework (CCF) addresses their limitations to make blockchains suitable for a wide variety of business consortiums.
Come learn how to integrate, deploy and modernize your data platform to Azure SQL Database Hyperscale. Hyperscale offers a data tier that has infinite scale, optimized for highly transactional workloads and offers seamless integration with all the game changing benefits of being a fully managed database while still offering all the familiar SQL functionality. Easily build new applications or modernize legacy applications and integrate with new serverless functions through Azure Functions or introduce advanced self service reporting with PowerBI, without introducing additional complexity or compromising on an enterprise ready features for your data platform.
We’ll start with a few industry examples to inspire you and a quick overview of Azure Databricks before diving into the heart of this technical session. After going through the various aspects of Machine Learning (ML), including supervised learning, unsupervised learning, and deep learning options, we will share exciting demos to help you understand how Databricks can meet your ML needs. You’ll leave this session armed with GitHub examples that you can use to build on your session learnings with real-world scenarios.
Learn how you can use Data Box Edge with built-in FPGAs to deliver accelerated intelligence at the edge - all controlled and managed from Azure. We’ll demo step by step so you can clearly understand how to achieve this in your environment.
Building end-to-end IoT solutions can be more complicated than people realize. Different services, languages, and platforms affect all parts of the IoT solution: devices, cloud services, code and your business systems. In this session you will learn how IoT Central and latest IoT platform innovations simplify development of IoT solutions even further, enabling your enterprise to focus on getting business value expected from IoT investments. After attending this talk, you will have a clear understanding of how we are simplifying IoT with Azure IoT Central and our new Azure IoT platform innovations to create scalable IoT solutions.
Current trends in software and backend architecture have been evolving towards a more loosely coupled more granular design. I am sure most of you have heard of microservice based architectures. The latest development on that front in the past couple of years has been the advent of Serverless which allows you to run applications in very cost effective ephemeral services. This is why it is important to have a proper gateway for your API that is able to route all your requests to the designated endpoint. GraphQL stands out in that respect as being a mature open sourced standard started at Facebook. We will first have a look at how we set up our own GraphQL server locally, then we will explore the Query language and schema definitions it provides which allows you essentially query your mesh of services from a single point of entry. The beauty of that is it will notify you early if any of your endpoints is misbehaving or the schemas are out of date by erring out. Another advantage of this is that it allows for your API documentation to be a real time process and it will give you what one may call an API playground where you can query and explore your API. After we explore our Serverless API we will have a look at the more advanced features and standards around mutators and resolvers and then we will close by going all in, full Serverless and deploy our GraphQL server to a function in the cloud.
PayMe is a social payments app, built on modern technology stack by HSBC and launched in Hong Kong market catering to 1.5 million customers and growing. In this session, we will take you through our journey to design and develop a highly scalable microservices architecture which is currently serving 500 million transactions per day on the Azure Database for MySQL service. We will share how we leverage the integrations with rest of Azure ecosystem with Azure Databricks and Azure Cosmos DB - to do real-time, ML-based predictive analytics, and generate insights for both consumers and merchants on the platform. Come and attend this session to see how we are leveraging cloud technology to revolutionize the way social payments are done in Asia market.
Hear about the newest releases in AKS, from the experts.