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Streams Replication Manager Prefixless Replication

Cloudera

It is also important to have multiple options (like normal and prefixless replication) to do the replication process, since every solution has its own advantages. It is also important to have multiple options (like normal and prefixless replication) to do the replication process, since every solution has its own advantages.

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Let’s Flink on EKS: Data Lake Primer

OpenCredo

This post is a getting-started guide intended to assist engineers in setting up an open model infrastructure for real-time processing. Here at OpenCredo we love projects that are based around Kafka and/or Data/Platform Engineering; in one of our recent projects, we created an open data lake using Kafka, Flink, Nessie and Iceberg.

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The Importance of Distributed Tracing for Apache-Kafka-Based Applications

Confluent

Apache-Kafka ® -based applications stand out for their ability to decouple producers and consumers using an event log as an intermediate layer. Distributed tracing has been key for helping us create a clear understanding of how applications are related to each other. Distributed tracing with Zipkin. Let’s imagine a “Hello, World!”

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How to Connect KSQL to Confluent Cloud using Kubernetes with Helm

Confluent

Confluent Cloud, a fully managed event cloud-native streaming service that extends the value of Apache Kafka ® , is simple, resilient, secure, and performant, allowing you to focus on what is important—building contextual event-driven applications, not infrastructure. and Helm/Tiller 2.8.2+ Click on the “Clients” option.

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Drafting Your Camunda Cloud Architecture: Connecting The Workflow Engine With Your World

Bernd Rucker

Camunda Cloud Architecture Blog Post Series?—?Part Part 1 Have you started your first project using process automation as a service with Camunda Cloud ? Or what’s a job worker, what should it do, and how many do you need? Start process instances using the Java Client : processInstance = zeebeClient.newCreateInstanceCommand().bpmnProcessId("someProcess").latestVersion().variables(

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How ML System Design helps us to make better ML products

Xebia

The classic article on Hidden Technical Debt in Machine Learning Systems explains how small the model is compared to the system it operates in. This blogpost illustrates the steps of the design process. A demand forecasting case will be used to demonstrate the process. Design process There is no single way to do system design.

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Using Streams Replication Manager Prefixless Replication for Kafka Topic Aggregation

Cloudera

Businesses often need to aggregate topics because it is essential for organizing, simplifying, and optimizing the processing of streaming data. It enables efficient analysis, facilitates modular development, and enhances the overall effectiveness of streaming applications. If not, you can check out this related blog post.

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