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tricentis

Ensuring the performance of your Kafka-dependent applications

Jun 13, 2024 By Daniel Murillo In Tricentis
In today’s data-driven world, Apache Kafka has emerged as an essential component in building real-time data pipelines and streaming applications. Its fault tolerance, scalability, and ability to handle high throughput makes it a great choice for businesses handling high volumes of data.
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confluent

How to Use Flink SQL, Streamlit, and Kafka: Part 2

Jun 10, 2024 By README In Confluent
In part one of this series, we walked through how to use Streamlit, Apache Kafka, and Apache Flink to create a live data-driven user interface for a market data application to select a stock (e.g., SPY) and discussed the structure of the app at a high level. First, data with information on stock bid prices is moved via an Alpaca websocket, then, it’s produced to a Kafka topic in Confluent Cloud where it is also processed with Flink SQL.
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confluent

86% of IT leaders say data streaming is a priority for IT investment in 2024

Jun 6, 2024 By Confluent In Confluent
Confluent survey: 90% of respondents say data streaming platforms can lead to more product and service innovation in AI and ML development. 86% of respondents cite data streaming as a strategic or important priority for IT investments in 2024. For 91% of respondents, data streaming platforms are critical or important for achieving data-related goals.
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How to Analyze Data from a REST API with Flink SQL

Jun 6, 2024 By Confluent In Confluent
Join Lucia Cerchie in a coding walkthrough, bridging the gap between REST APIs and data streaming. Together we’ll transform the OpenSky Network's live API into a data stream using Kafka and Flink SQL. Not only do we change the REST API into a data stream in this walkthrough, but we clean up the data on the way! We use Flink SQL to make it more readable and clean, and in that way we keep more of the business logic away from the client code.
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Defining Asynchronous Microservice APIs for Fraud Detection | Designing Event-Driven Microservices

May 31, 2024 By Confluent In Confluent
In this video, Wade explores the process of decomposing a monolith into a series of microservices. You'll see how Tributary bank extracts a variety of API methods from an existing monolith. Tributary Bank wants to decompose its monolith into a series of microservices. They are going to start with their Fraud Detection service. However, before they can start, they first have to untangle the existing code. They will need to define a clean API that will allow them to move the functionality to an asynchronous, event-driven microservice.
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