<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <channel>
    <title>DEV Community: Soumya Ranjan Nanda</title>
    <description>The latest articles on DEV Community by Soumya Ranjan Nanda (@soumya_ranjannanda_168b9).</description>
    <link>https://dev.to/soumya_ranjannanda_168b9</link>
    <image>
      <url>https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3871120%2F35f212dd-1482-4665-8246-430c06ed9bfd.png</url>
      <title>DEV Community: Soumya Ranjan Nanda</title>
      <link>https://dev.to/soumya_ranjannanda_168b9</link>
    </image>
    <atom:link rel="self" type="application/rss+xml" href="https://dev.to/feed/soumya_ranjannanda_168b9"/>
    <language>en</language>
    <item>
      <title>How I Scaled Bulk Search in Spring Boot with Parallel Batch Jobs and Controlled Concurrency</title>
      <dc:creator>Soumya Ranjan Nanda</dc:creator>
      <pubDate>Mon, 13 Apr 2026 10:57:38 +0000</pubDate>
      <link>https://dev.to/soumya_ranjannanda_168b9/how-i-scaled-bulk-search-in-spring-boot-with-parallel-batch-jobs-and-controlled-concurrency-21j</link>
      <guid>https://dev.to/soumya_ranjannanda_168b9/how-i-scaled-bulk-search-in-spring-boot-with-parallel-batch-jobs-and-controlled-concurrency-21j</guid>
      <description>&lt;p&gt;I recently wrote about a backend problem that looked simple at first but became a real architecture and reliability challenge under load:&lt;/p&gt;

&lt;p&gt;scaling bulk search in Spring Boot with parallel batch jobs and controlled concurrency&lt;/p&gt;

&lt;p&gt;A few lessons stood out for me:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;parallelism helps, but only until it starts hurting upstream systems&lt;/li&gt;
&lt;li&gt;chunking is not just a batch setting, it becomes a stability boundary&lt;/li&gt;
&lt;li&gt;partial failure handling matters as much as throughput&lt;/li&gt;
&lt;li&gt;caching repeated enrichment work can remove a surprising amount of unnecessary load&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;One of the biggest shifts for me was moving away from a more limited blocking flow into parallel batch jobs while still keeping pressure on downstream systems under control.&lt;/p&gt;

&lt;p&gt;I wrote the full breakdown here:&lt;br&gt;
&lt;a href="https://medium.com/p/6a742ad7af9d" rel="noopener noreferrer"&gt;https://medium.com/p/6a742ad7af9d&lt;/a&gt;&lt;/p&gt;

</description>
      <category>java</category>
      <category>distributedsystems</category>
      <category>systemdesign</category>
      <category>architecture</category>
    </item>
    <item>
      <title>What I learned building bulk search for large datasets in React + Spring Boot</title>
      <dc:creator>Soumya Ranjan Nanda</dc:creator>
      <pubDate>Mon, 13 Apr 2026 05:43:30 +0000</pubDate>
      <link>https://dev.to/soumya_ranjannanda_168b9/what-i-learned-building-bulk-search-for-large-datasets-in-react-spring-boot-4id1</link>
      <guid>https://dev.to/soumya_ranjannanda_168b9/what-i-learned-building-bulk-search-for-large-datasets-in-react-spring-boot-4id1</guid>
      <description>&lt;p&gt;Bulk search sounds easy until real users start pasting spreadsheet data, uploading messy CSVs, and expecting clear results for thousands of records.&lt;/p&gt;

&lt;p&gt;I recently built a bulk search workflow in React + Spring Boot, and this article is a practical breakdown of what actually mattered: normalization, validation, chunking, frontend performance, and partial-failure reporting.&lt;/p&gt;

&lt;p&gt;Read the full article here: &lt;a href="https://medium.com/p/ea69f155054a" rel="noopener noreferrer"&gt;https://medium.com/p/ea69f155054a&lt;/a&gt;&lt;/p&gt;

</description>
      <category>react</category>
      <category>aws</category>
      <category>java</category>
      <category>springboot</category>
    </item>
  </channel>
</rss>
