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    <title>InfoQ - Database Replication - News</title>
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      <title>From Minutes to Seconds: Uber Boosts MySQL Cluster Uptime with Consensus Architecture</title>
      <link>https://www.infoq.com/news/2026/03/uber-mysql-uptime-consensus/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Database+Replication-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/03/uber-mysql-uptime-consensus/en/headerimage/consensus-1772309087126.jpeg"/&gt;&lt;p&gt;Uber redesigned its MySQL fleet using a consensus-driven architecture based on MySQL Group Replication, reducing cluster failover time from minutes to seconds. By moving leader election and failure detection into the database layer, Uber improved availability, simplified external orchestration, and strengthened consistency across thousands of production clusters.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>MySQL</category>
      <category>Fault Tolerance</category>
      <category>Relational Databases</category>
      <category>Protocol</category>
      <category>Scalability</category>
      <category>Cloud Architecture</category>
      <category>Infrastructure</category>
      <category>Clusters</category>
      <category>Database Replication</category>
      <category>Paxos</category>
      <category>Reliability</category>
      <category>Distributed Systems</category>
      <category>Availability</category>
      <category>Architecture &amp; Design</category>
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      <pubDate>Wed, 11 Mar 2026 14:15:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/03/uber-mysql-uptime-consensus/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Database+Replication-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-03-11T14:15:00Z</dc:date>
      <dc:identifier>/news/2026/03/uber-mysql-uptime-consensus/en</dc:identifier>
    </item>
    <item>
      <title>Hybrid Cloud Data at Uber: How Engineers Solved Extreme-Scale Replication Challenges</title>
      <link>https://www.infoq.com/news/2026/03/uber-scaled-data-replication/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Database+Replication-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/03/uber-scaled-data-replication/en/headerimage/generatedHeaderImage-1771726275349.jpg"/&gt;&lt;p&gt;Uber’s HiveSync team optimized Hadoop Distcp to handle multi-petabyte replication across hybrid cloud and on-premise data lakes. Enhancements include task parallelization, Uber jobs for small transfers, and improved observability, enabling 5x replication capacity and seamless on-premise-to-cloud migration.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Big Data</category>
      <category>Database Replication</category>
      <category>Distributed Systems</category>
      <category>Data Pipelines</category>
      <category>Observability</category>
      <category>Data Lake</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Mon, 02 Mar 2026 15:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/03/uber-scaled-data-replication/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Database+Replication-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-03-02T15:00:00Z</dc:date>
      <dc:identifier>/news/2026/03/uber-scaled-data-replication/en</dc:identifier>
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