swapna267 opened a new pull request, #815:
URL: https://github.com/apache/flink-web/pull/815

   This is follow up of , 
   
   https://github.com/apache/flink-web/pull/811 with the build file updates and 
modified date for the blog post.
   
   This PR contains a technical blog post titled **"From Stream to Lakehouse: 
Kafka Ingestion with the Flink Dynamic Iceberg Sink"**. 
   
   The article addresses a common pain point for data engineers: managing 
complex and brittle ingestion pipelines for thousands of evolving Kafka topics. 
It introduces the **Flink Dynamic Iceberg Sink** as a solution that enables a 
self-adapting, zero-downtime ingestion layer.
   
   The post walks the reader through static pipelines using iceberg sink and 
then provides a detailed guide on building the same using dynamic iceberg sink. 
It focuses on a practical use case involving Kafka, Avro, and Confluent Schema 
Registry, and includes code examples to illustrate the key components.
   
   **Key Topics Covered:**
   
   * Building generic Kafka to iceberg ingestion pipeline and scaling to 
thousands of topics in single pipeline.
   * The challenges of static Kafka-to-Iceberg pipelines (schema evolution, new 
topics).
   *   An architectural overview of the Dynamic Iceberg Sink pattern.
   *   A step-by-step implementation guide, including:
       *   Preserving metadata with a `KafkaRecord` wrapper.
       *   Using a `DynamicRecordGenerator` for late binding of schema and 
table information.
       *   Assembling the final Flink job.
   *   Details on the feature's availability in Apache Iceberg and supported 
Flink versions.
   *   Credits to the original author of the proposal and key contributors.
   
   
   **Related Links**
   
   *   This work is based on the original proposal: [Flink Dynamic Iceberg Sink 
Proposal](https://docs.google.com/document/d/1R3NZmi65S4lwnmNjH4gLCuXZbgvZV5GNrQKJ5NYdO9s/edit?tab=t.0#heading=h.xv1r23unqyn3)


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