Microsoft, Principal Product Manager
Redmond, Washington, United States
Azure Data Platform MVP for 12 years in a row, now Product Manager in Azure SQL team, focusing on developer experience. Developer at heart, heavy metal lover; once a biker, now waiting for kids to grow old to start to travel the world again.
Area of Expertise
Jamstack is one of the most modern architecture patterns and has been getting a lot of traction lately. In this session, we'll see an end-to-end demo of how we can build a Jamstack site in Azure, using Azure Static Web Apps and Azure Functions, and taking advantage of well-known and less known features of Azure SQL that will make you – the developer – productive and efficient as never before. From Graph Models to JSON, from REST to GraphQL, this code-heavy demo packed session will show all you need to build end-to-end modern, scalable, solutions. CI/CD included.
Join the Azure SQL Product Group to learn how developing apps with modern database capabilities, CI/CD and DevOps, backend API development, and IoT becomes easier, more efficient, and more scalable with Azure SQL Database. This day long hands-on workshop will focus on two real world scenarios that you can modify for your projects. The main scenario includes learning how to create, build, and deploy modern full stack applications in Azure with the language of your choice (Python, Node.js, .NET) and with a Vue.js frontend. The second scenario includes building IoT solutions that scale with the support of Azure SQL Database. Through these scenarios, you will get familiar with Azure SQL Database (Hyperscale and Serverless), Azure Functions, Azure Static Web Apps, Logic Apps, VS Code, Azure IoT Hub, and GitHub Actions.
IoT, Online Gaming, Microservices, Event sourcing: environment and architectures that can generate a steadily stream of data that will for sure be stored, queried and analyzed at some point. Azure SQL can easily manage the amount of generated data, working together with tools like Event Hubs, Stream Analytics, Azure Functions or Azure Databricks, to allow developers to create powerful stream processing solution. What about, for example, creating a solution to update in real-time the most played songs of a music streaming service? Or keeping track of player status in an MMPORG game? Or looking after connected vehicles? In this session we'll see how Azure SQL can help in the creation of solution that needs streaming - and thus real-time or near real-time - capabilities.
The ToDoMVC app has been around for a while and it is a great sample app to get started on front-end building. But what about the full-stack? And what if we want to create a complete Serverless Full-Stack solution? Well with Azure Static WebApps, Azure Functions, Node and Azure SQL, this is much simpler than anyone could expect! Let's see how simple is that!
One day a customer comes to you with a very simple requirement: ingest, process and store at least 10,000 msg/sec using only PaaS solutions. Is this possible? How? What is the correct architecture to sustain such volume (or go ever higher than that) and what are the implementation best practices to make sure everything is balanced and you're not just throwing money at the problem? In this session we'll show how to architect, build and deploy such solution. We will start from 10,000 msg/sec…and we'll see together how high we can go (and we’ll go pretty high!), so that you can be sure that even the most demanding workload can be handled, gaining a good understanding of how Azure work behind the scenes for us.
Stream processing is becoming more and more important in many scenarios. It can be found in Microservices Architectures, Near Real Time Operational Analytics, IoT and Smart Building solutions and Real Time Data Processing. Azure offers a lot of options to implement a Streaming At Scale solution, and a good knowledge of the pros and cons of the various technologies involved is vital to architect and implement the correct Lambda or Kappa architecture for your solution.
In this session we'll go through the most common way to implement a Streaming at Scale solution, sharing what we have learned from many engagements with the most diverse customers throughout the world.
An overview of the innovation and disruption that Azure SQL brought to the market in the last years, a glimpse of what will come in near future, an insight of Azure SQL is build and engineered, and some best practices you can take home and use right away.
Learn how to implement a fully working, end-to-end, full-stack solution using Azure Static Web Apps, Azure Functions and Azure SQL Serverless. In this session we’ll see and build together the simple (but not too simple!) To-Do list reference app, using Vue.js, CI/CD, Unit Testing and more!
Azure SQL offre diverse opzioni per effettuare lo scale-out del database, specialmente con Azure SQL Hyperscale. In pochi secondi e' possibile creare una replica del database ed utilizzarla per indirizzare tutte le richieste Read-Only che, come sappiamo, sono la maggior parte in caso di scenari OLTP. In questa sessione vedremo che possibilità ci sono e le best practices per sfruttare al meglio questa abilita unica di Azure SQL. E se stai pensando "beh ma perché non usare una cache distribuita al posto che il database", allora questa sessione e' proprio per te!
Modern cloud databases offer the ability to scale-out in addition to scale-up. While the goal may seem to be the same - providing enough resources to serve even the most demanding and unpredictable workload - in reality a software architect can take advantage of the ability to scale out to create solution that provide better performances with lower costs and higher resiliency. In this session I'll show how Azure SQL Hyperscale can help you in creating fast, smarter, and more efficient solutions.
Learn how to create, build, and deploy modern full stack applications in Azure leveraging the language of your choice (Python, Node.js, or .NET) and with a Vue.js frontend. Topics covered include modern database capabilities, CI/CD and DevOps, backend API development, REST, and more. Using a real-world scenario of trying to catch the bus, you will learn how to build a solution that leverages Azure SQL Database, Azure Functions, Azure Static Web Apps, Logic Apps, Visual Studio Code and GitHub Actions.
Il trasporto pubblico è una benedizione, ma a volte può essere una sfida. Se perdo l'autobus, devo aspettare 30 minuti per il prossimo. Sarebbe bello creare una semplice applicazione che, usando le informazioni sulla circolazione degli autobus in tempo reale ed una GeoFence mi notifichi quando e' il momento giusto per uscire dall'ufficio. Con l'aiuto di Azure Function, Azure SQL e un servizio come IFTTT, e' presto fatto e in questa session lo vedrete con i vostri occhi.
How easy is managing dynamic schemas with Azure SQL? Is that possible at all? Or there are some compromises to make? And if that's possible, will it be fast? Easy to manage? Scalable? In this session we'll see how Azure SQL has evolved in the last years, with tons of innovations that bring together the best of relational and post-relational features, giving the developer all the needed options to manage and balance agility and consistency, scalability and manageability. Come and see how to use Azure SQL to support even the most complex and demanding backend API, with almost no plumbing code. It will be eyes opening!
Azure SQL Database is so similar to SQL Server that it is easy to forget that you are actually running on the cloud. In this session, we'll see some of the best practices you have to keep in mind to make sure performance are the best possible, taking into account things like network latency, the default read committed snapshot isolation level and other "little" small things that can make a huge difference in your solution.
Pensate ancora che la gestione di schemi dinamici o "liquidi" (anche per Martin Fowler non esiste lo "schemaless!) sia una capacita riservata solo a soluzioni NoSQL? E' ora di aggiornarsi! Da anni ormai features post-relazionali sono presenti in Azure SQL e, integrate con la potenza del query optimizer, creano un ambiente unico, in grado di gestire le più svariate necessita, fornendo un'ampio spettro di soluzioni per anche la piu agile delle soluzioni. Non perdetevi questa sessione!
Integration with Azure Databricks brings a lot of value to Data Scientists as they can query and manipulate data right on Azure SQL without having the need to push and pull data around, spending time and resources that can be instead used for analyzing and discovering data. In this session we'll see how you can connect to Azure SQL using the latest connector, how we can manipulate data on Databricks that resides on Azure SQL and also how we can efficiently store cleaned, curated and enriched data back into Azure SQL, to create an amazing platform for a Data Scientist.
Public transportation is a blessing, but sometimes it can be a challenge. If I miss my bus, I might have to wait for 30 minutes to catch the next one. It would be great if someone could create a simple application that gets real-time bus information, also allowing the creation of geofence: when the bus enters that area, you know it’s time to leave the office. You can catch the bus right on time and never have to wait for the next one! I’ve been using it for more than a year now and it…just works. Like magic.
With the aid of Azure Function, Azure SQL and a service like IFTTT, creating such solutions is fun, and paves the way for improvements and integrations that make people’s lives easier.
In this session we’ll analyze the solution from the inside out.
Azure SQL natively support to JSON is really a game changing feature as it allows both object model and relational model to happily live together, allowing application developer and database developer to use the best model - or even both - for their need. It also provide great performances and flexibility and helps to achieve great scalability and agility. In this session we'll see how one can create REST API with the language if its choice while leveraging JSON to communicate efficiently and comfortably with the database and to create hybrid data models, taking the best from relational and non-relational world.
How to create a REST API using Azure SQL, Dapper, .NET and JSON and live forever happily after. In this session we’ll start from a blank project and we’ll implement a fully working REST API, learning how to leverage the native support in JSON to easily and efficiently having .NET and Azure SQL working together with minimal effort but great performances. We’ll also see how to use Dapper to reduce the amount of code we need to write, all with a fully functioning CI/CD pipeline created using GitHub Actions.
Azure SQL may not be the database you're using, as you think it is way too expensive, and really not flexible or scalable enough for your new project. Let me show you three small, incredibly precious, gems hidden in Azure SQL engine core that will at least make you think.
I'll show you how much less code you have to write to create an API solution that can be accessed at scale, that supports completely secured access to data stored in the database it allows users to access to, and that also provides support for intelligent data syncing so that the API will can provide a list of changed data since a user access it last time.
If that's not amazing I honestly don't know that it is. Oh yeah, everything will work with any platform and language, even though I'll show samples only using Python and .NET Core.
In this session we'll start from scratch, from the creation of an Azure SQL database to safely store your data, to the creation of a fully functioning solution for Mobile and Desktop, that will allow the management of a virtual classroom. All without writing a line of code, using the most advanced no-code platform, designed to boost productivity and that can used literally by anyone!
Microsoft, Principal Product Manager
Redmond, Washington, United States