Tania Stormovski
Principal Software Architect / Microsoft MVP
Florianópolis, Brazil
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I am passionate about solving complex problems and delivering high-quality software that meets the needs of the business and the users.
As a software architect at Ambev Tech, I design and implement scalable, reliable, and secure solutions
applications, using .NET, microservices, and event driven architecture.
I am also a Microsoft MVP Developer Technologies, a recognition that reflects my deep knowledge and
enthusiasm for Microsoft products and services, as well as my contribution to the technical community.
With over 15 years of experience in software and solution development and architecture, I have also led and managed teams of developers and architects, providing technical guidance, coaching, and feedback helping building your career .
I enjoy working in positive and collaborative environments, where I can learn from others and share my expertise and my main goal is always achieve the best results and create software solutions that make a difference in the world.
Area of Expertise
Topics
Route Events with Azure Stream Analitycs
How create a event driven architecture with filter and redirects capabilities using Azure Stream Analytics as a tool for filter, transform and redirect message from stream sources.
An event router plays a crucial role in event-driven architecture (EDA), especially in complex systems involving numerous event producers and consumers. Essentially, the event router serves as the middle-man in the communication line, intercepting and distributing the events from their source to their intended recipients.
Using Azure Stream Analytics, you can create a Stream Analytics job that takes messages from Event Hubs as input and uses a SQL-like query to filter, transform, and redirect the messages to Service Bus. The query can be written using SQL-like syntax, allowing you to specify the input fields, filters, groupings, aggregations, and other transformation calculations that you want to apply to the data. You can then specify the job output to be sent to Service Bus using a preconfigured connector.
As for latency, Stream Analytics is designed to offer low processing latency, supporting adjustable time windows that allow you to control how long messages remain in the processing pipeline. In general, latency depends on the size and complexity of the query, as well as the volume of messages processed, but can range from a few seconds to a few minutes.
Stream Analytics is optimized for cost. There are no upfront costs involved — you only pay for the streaming units you consume.
It aslo can be a very interesting alternative in the initial stages of integration, where validation of the routing flow and filters is still necessary, in this sense being an intermediate step towards a definitive solution.
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