Kafka

Data

Kafka in Action (Teaser) • Viktor Gamov & Tim Berglund • GOTO 2022

Viktor Gamov’s co-authored book “Kafka in Action” ensures that you have a list of recipes to dive into. Joined by Tim Berglund, VP DevRel at StarTree, they explore the fundamentals of Apache Kafka. Learn what Kafka can help you achieve, what Viktor’s favorite MCU film is and what “Highway to Mars” by Beast In Black […]

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Big Data Data IoT

Kafka Streams 101: Getting Started

To understand Kafka Streams, you have to begin with Apache Kafka®, a distributed, scalable, elastic, and fault-tolerant event streaming platform. The storage nodes in Kafka, brokers, are just instances of the Kafka storage layer process running on your laptop or server. At the heart of each broker is a log, an append-only file that holds […]

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CosmosDB

Learn how to Connect Azure Cosmos DB with Apache Kafka

Hear how a Microsoft CosmosDB customer leveraged their existing Kafka investments and persist event messages in a durable managed database system in Azure.

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CosmosDB

Kafka Connect for Azure Cosmos DB – Episode 21

In this video, Mark Brown is joined by Abinav Rameesh to talk about and dig into the new Kafka Connector for Azure Cosmos DB. Kafka, with its rich ecosystem of source and sink connectors, enables microservices to communicate with each other while still being independent of the underlying databases. Learn more about the Kafka connector […]

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Big Data

Kafka + Spark Streaming + Hive Example

Davis Busteed walks us through building a proof of concept for Spark Streaming from a Kafka Source to Hive. Check out the README and resource files at https://github.com/dbusteed/kafka-spark-streaming-example 

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Azure Big Data IoT

Big data processing with Azure Event Hubs for Apache Kafka

Are you working with Apache Kafka and want to simplify management of your infrastructure? Lena Hall joins Scott Hanselman to show you can keep using Apache Kafka libraries for hundreds of projects, and try Azure Event Hubs behind the scenes to focus on code instead of maintaining infrastructure      Related Links Apache Kafka Applications Can Work […]

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Azure Data Data Warehouse

Modern Data Warehousing Part 1: Azure Data Ingestion Options

In this video, Chris Seferlis  discusses stage one of the Modern Data Warehouse Process: Data Ingestion. Related Links: Azure Data Factory – https://azure.microsoft.com/en-us/services/data-factory/ Azure Databricks – https://azure.microsoft.com/en-us/services/databricks/ Azure HDInsight – https://azure.microsoft.com/en-us/services/hdinsight/ Azure Synapse – https://azure.microsoft.com/en-us/services/synapse-analytics/ Azure Data Box – https://azure.microsoft.com/en-us/services/databox/ Event Hubs – https://azure.microsoft.com/en-us/services/event-hubs/ Kafka on HDInsight – https://docs.microsoft.com/en-us/azure/hdinsight/kafka/apache-kafka-introduction IoT Hub – https://azure.microsoft.com/en-us/services/iot-hub/

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Azure IoT

Azure Event Hubs Supported Protocols

In this episode, Serkant Karaca and Shubha Vijayasarathy from the Azure Event Hubs team sit with Cecil to discuss the various protocols that are supported by Azure Event Hubs. They dive into the AMQP support, compatibility with Apache Kafka and even discuss some customer use cases. Useful Links Azure Event Hubs Documentation GitHub repo with […]

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Azure Big Data IoT

Azure Event Hubs with Kafka

Corey Sanders, Corporate VP – Microsoft Azure Compute team sat down with Dan Rosanova, Principal PM responsible for Azure messaging services. Dan shares some new functionality around Event Hubs with Kafka compatibility. Post any questions, topic ideas or general conversation here in the comments OR online on via Twitter with #AzureTwC

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Azure Big Data

Siphon on HDInsight Kafka

In this episode of Azure Friday, Thomas Alex discusses how Microsoft uses Apache Kafka for HDInsight to power Siphon, a data ingestion service for internal use. Apache Kafka for HDInsight is an enterprise-grade, open-source, streaming ingestion service. Microsoft created Siphon as a highly available and reliable service to ingest massive amounts of data for processing in […]

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