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      <title>Article: The Mathematics of Backlogs: Capacity Planning for Queue Recovery</title>
      <link>https://www.infoq.com/articles/capacity-planning-queue-recovery/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Load+Testing-articles</link>
      <description>&lt;img src="https://res.infoq.com/articles/capacity-planning-queue-recovery/en/headerimage/The-Mathematics-of-Backlogs-Capacity-Planning-for-Queue-Recovery-header-1778227922596.jpg"/&gt;&lt;p&gt;Backlogs in distributed systems are arithmetic problems, not mysteries. This article provides practical formulas for calculating backlog drain time, sizing consumer headroom, and setting auto-scaling triggers. It covers key failure modes — retry amplification, metastable states, and cascading pipeline bottlenecks — plus when to shed load instead of draining.&lt;/p&gt; &lt;i&gt;By Rajesh Kumar Pandey&lt;/i&gt;</description>
      <category>Queue</category>
      <category>Load Testing</category>
      <category>Failure</category>
      <category>Capacity Planning</category>
      <category>DevOps</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Wed, 13 May 2026 09:00:00 GMT</pubDate>
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      <dc:creator>Rajesh Kumar Pandey</dc:creator>
      <dc:date>2026-05-13T09:00:00Z</dc:date>
      <dc:identifier>/articles/capacity-planning-queue-recovery/en</dc:identifier>
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