When you order a pizza, what if you knew every step of the process from the moment it goes in the oven to being delivered to your doorstep? Event-Driven Architecture is a modern, data-driven approach that describes “events” (i.e., something that just happened).
A real-time data infrastructure enables you to provide such event-driven data insights in real time. Israel Ekpo (Principal Cloud Solutions Architect, Microsoft Global Partner Solutions, Microsoft) and Alicia Moniz (Cloud Partner Solutions Architect, Confluent) discuss use cases on leveraging Confluent Cloud and Microsoft Azure to power real-time, event-driven architectures.
As an Apache Kafka® community stalwart, Israel focuses on helping customers and independent software vendor (ISV) partners build solutions for the cloud and use open source databases and architecture solutions like Kafka, Kubernetes, Apache Flink, MySQL, and PostgreSQL on Microsoft Azure. He’s worked with retailers and those in the IoT space to help them adopt processes for inventory management with Confluent. Having a cloud-native, real-time architecture that can keep an accurate record of supply and demand is important in keeping up with the inventory and customer satisfaction. Israel has also worked with customers that use Confluent to integrate with Cosmos DB, Microsoft SQL Server, Azure Cognitive Search, and other integrations within the Azure ecosystem.
Another important use case is enabling real-time data accessibility in the public sector and healthcare while ensuring data security and regulatory compliance like HIPAA. Alicia has a background in AI, and she expresses the importance of moving away from the monolithic, centralized data warehouse to a more flexible and scalable architecture like Kafka. Building a data pipeline leveraging Kafka helps ensure data security and consistency with minimized risk.
The Confluent and Azure integration enables quick Kafka deployment with out-of-the-box solutions within the Kafka ecosystem. Confluent Schema Registry captures event streams with a consistent data structure, ksqlDB enables the development of real-time ETL pipelines, and Kafka Connect enables the streaming of data to multiple Azure services.
EPISODE LINKS
Apache Kafka 3.5 - Kafka Core, Connect, Streams, & Client Updates
A Special Announcement from Streaming Audio
How to use Data Contracts for Long-Term Schema Management
How to use Python with Apache Kafka
Next-Gen Data Modeling, Integrity, and Governance with YODA
Migrate Your Kafka Cluster with Minimal Downtime
Real-Time Data Transformation and Analytics with dbt Labs
What is the Future of Streaming Data?
What can Apache Kafka Developers learn from Online Gaming?
Apache Kafka 3.4 - New Features & Improvements
How to use OpenTelemetry to Trace and Monitor Apache Kafka Systems
What is Data Democratization and Why is it Important?
Git for Data: Managing Data like Code with lakeFS
Using Kafka-Leader-Election to Improve Scalability and Performance
Real-Time Machine Learning and Smarter AI with Data Streaming
The Present and Future of Stream Processing
Top 6 Worst Apache Kafka JIRA Bugs
Learn How Stream-Processing Works The Simplest Way Possible
Building and Designing Events and Event Streams with Apache Kafka
Rethinking Apache Kafka Security and Account Management
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