<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Backpressured</title><link>https://backpressured.dev/</link><description>Recent content on Backpressured</description><generator>Hugo</generator><language>ko</language><lastBuildDate>Thu, 11 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://backpressured.dev/index.xml" rel="self" type="application/rss+xml"/><item><title>CDC 파이프라인의 숨겨진 비용: Small File이 만드는 S3 Request 폭탄</title><link>https://backpressured.dev/posts/cdc-small-file-hidden-cost/</link><pubDate>Thu, 11 Jun 2026 00:00:00 +0000</pubDate><guid>https://backpressured.dev/posts/cdc-small-file-hidden-cost/</guid><description>Athena 비용은 스캔량이 전부가 아닙니다. CDC 파이프라인이 만든 수백만 개의 Small File이 S3 Request 비용과 쿼리 성능을 어떻게 잠식하는지, 그리고 어떻게 해결했는지를 공유합니다.</description></item><item><title>About</title><link>https://backpressured.dev/about/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://backpressured.dev/about/</guid><description>&lt;p>안녕하세요, 장재혁입니다.&lt;/p>
&lt;p>인도 핀테크 회사에서 데이터 플랫폼을 만들고 운영하고 있습니다. Spark, Flink, Debezium, Airflow, Iceberg 같은 것들을 주로 다루고, 요즘은 데이터 스택 모던화와 AI-ready 데이터 플랫폼 설계에 관심이 많습니다.&lt;/p>
&lt;p>운영하면서 배운 것들을 틈틈이 기록해보려 합니다.&lt;/p>
&lt;h2 id="tech-stack">Tech Stack&lt;/h2>
&lt;ul>
&lt;li>&lt;strong>Processing:&lt;/strong> Spark, Flink, dbt&lt;/li>
&lt;li>&lt;strong>Streaming &amp;amp; CDC:&lt;/strong> Debezium, Kafka, Kinesis, NiFi&lt;/li>
&lt;li>&lt;strong>Storage &amp;amp; DW:&lt;/strong> S3, Athena, Iceberg, DynamoDB&lt;/li>
&lt;li>&lt;strong>Orchestration:&lt;/strong> Airflow&lt;/li>
&lt;li>&lt;strong>DevOps &amp;amp; Infra:&lt;/strong> Docker, Jenkins, SAM, CloudFormation, Lake Formation&lt;/li>
&lt;li>&lt;strong>Monitoring:&lt;/strong> Prometheus, Grafana, CloudWatch, Kibana&lt;/li>
&lt;li>&lt;strong>Cloud:&lt;/strong> AWS&lt;/li>
&lt;li>&lt;strong>Languages:&lt;/strong> Python, SQL&lt;/li>
&lt;/ul>
&lt;h2 id="writing">Writing&lt;/h2>
&lt;ul>
&lt;li>&lt;a href="https://blog.afinit.com/cdc-incremental-replication">CDC가 데이터 플랫폼을 바꾸는 방식: CDC-based Incremental Replication&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://blog.afinit.com/cdc-pipeline-debezium-flink">CDC 파이프라인을 Debezium과 Flink로 재설계한 이유&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://blog.afinit.com/nifi-apache-flink-sms-pipeline">NiFi에서 Apache Flink로, 실시간 SMS 파이프라인 개선기&lt;/a>&lt;/li>
&lt;/ul>
&lt;h2 id="contact">Contact&lt;/h2>
&lt;ul>
&lt;li>&lt;a href="https://linkedin.com/in/jaehyuk-jang-bab185178">LinkedIn&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://github.com/jaehyukjang">GitHub&lt;/a>&lt;/li>
&lt;li>Email: &lt;a href="mailto:jjhyuk92@gmail.com">jjhyuk92@gmail.com&lt;/a>&lt;/li>
&lt;/ul></description></item></channel></rss>