In this blog, we will go over how to ingest data into Azure Data Explorer using the open source Kafka Connect Sink connector for Azure Data Explorer running on Kubernetes using Strimzi. Kafka Connect is a tool for scalably and reliably streaming data between Apache Kafka and other systems using source and sink connectors and Strimzi provides a “Kubernetes-native” way of running Kafka clusters as well as Kafka Connect workers.

Azure Data Explorer is a fast and scalable data exploration service that lets you collect, store, and analyze large volumes of data from any diverse sources, such as websites, applications, IoT devices, and more. It has a rich connector ecosystem that supports ingestion into Azure Data Explorer as detailed here. One of the supported sources is Apache Kafka and the sink connector allows you to move data from Kafka topics into Azure Data Explorer tables which you can later query and analyse. …


Originally published here: https://devblogs.microsoft.com/cosmosdb/build-fault-tolerant-applications-cassandra/

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Azure Cosmos DB is a resource governed system that allows you to execute a certain number of operations per second based on the provisioned throughput you have configured. If clients exceed that limit and consume more request units than what was provisioned, it leads to rate limiting of subsequent requests and exceptions being thrown — they are also referred to as 429 errors.

With the help of a practical example, I’ll demonstrate how to incorporate fault-tolerance in your Go applications by handling and retrying operations affected by these rate limiting errors. …


This blog provides a practical example of how to use Azure Stream Analytics to process streaming data from Azure Event Hubs. You should be able to go through this tutorial using the Azure Portal (or Azure CLI), without writing any code. There are also other resources for exploring stream processing with Azure Stream Analytics at the end of this blog post.

What’s covered?

  • A quick overview of the use case, solution, and its constituents
  • How to setup the required Azure services: Event Hubs, Stream Analytics and Blob storage
  • How to configure and test your Azure Stream Analytics Job with sample…

About

Abhishek Gupta

Currently working with Kafka, Databases, Azure, Kubernetes and related open source projects | Confluent Community Catalyst (for Kafka)

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