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    <title>topic Re: What is overwatch ? in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/what-is-overwatch/m-p/22831#M15711</link>
    <description>&lt;P&gt;Overwatch is a different kind of tool - &lt;I&gt;right now&lt;/I&gt; it couldn't be used for real-time monitoring, like, Ganglia. Overwatch collects data from the multiple data sources (audit logs, APIs, cluster logs, etc.), process, enrich and aggregate them following traditional Bronze/Silver/Gold approach. The data that is provided by Overwatch could be used for different purposes:&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;Cost estimation - it may provide more granular analysis, like, attributing costs to specific notebooks and users, and also overcome the limits for clusters acquired from the instance pools&lt;/LI&gt;&lt;LI&gt;Governance and monitoring with much longer periods of time and much cheaper compared to Azure Log Analytics or other solutions&lt;/LI&gt;&lt;LI&gt;Identifying the problematic workloads &amp;amp; optimizing them&lt;/LI&gt;&lt;LI&gt;...&lt;/LI&gt;&lt;/UL&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="https://github.com/databrickslabs/overwatch" alt="https://github.com/databrickslabs/overwatch" target="_blank"&gt;Overwatch&lt;/A&gt; is available to Databricks customers as part of the Databricks Labs. Follow the &lt;A href="https://databrickslabs.github.io/overwatch/" alt="https://databrickslabs.github.io/overwatch/" target="_blank"&gt;documentation&lt;/A&gt; for installation instructions.&lt;/P&gt;</description>
    <pubDate>Fri, 18 Jun 2021 11:33:16 GMT</pubDate>
    <dc:creator>alexott</dc:creator>
    <dc:date>2021-06-18T11:33:16Z</dc:date>
    <item>
      <title>What is overwatch ?</title>
      <link>https://community.databricks.com/t5/data-engineering/what-is-overwatch/m-p/22830#M15710</link>
      <description>&lt;P&gt;I heard Databricks recommend overwatch for monitoring Clusters, Can  anybody help like what all metrics it will provide that , how it is helpful in monitoring or better than ganglia ?&lt;/P&gt;</description>
      <pubDate>Fri, 18 Jun 2021 10:57:19 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/what-is-overwatch/m-p/22830#M15710</guid>
      <dc:creator>User16826994223</dc:creator>
      <dc:date>2021-06-18T10:57:19Z</dc:date>
    </item>
    <item>
      <title>Re: What is overwatch ?</title>
      <link>https://community.databricks.com/t5/data-engineering/what-is-overwatch/m-p/22831#M15711</link>
      <description>&lt;P&gt;Overwatch is a different kind of tool - &lt;I&gt;right now&lt;/I&gt; it couldn't be used for real-time monitoring, like, Ganglia. Overwatch collects data from the multiple data sources (audit logs, APIs, cluster logs, etc.), process, enrich and aggregate them following traditional Bronze/Silver/Gold approach. The data that is provided by Overwatch could be used for different purposes:&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;Cost estimation - it may provide more granular analysis, like, attributing costs to specific notebooks and users, and also overcome the limits for clusters acquired from the instance pools&lt;/LI&gt;&lt;LI&gt;Governance and monitoring with much longer periods of time and much cheaper compared to Azure Log Analytics or other solutions&lt;/LI&gt;&lt;LI&gt;Identifying the problematic workloads &amp;amp; optimizing them&lt;/LI&gt;&lt;LI&gt;...&lt;/LI&gt;&lt;/UL&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="https://github.com/databrickslabs/overwatch" alt="https://github.com/databrickslabs/overwatch" target="_blank"&gt;Overwatch&lt;/A&gt; is available to Databricks customers as part of the Databricks Labs. Follow the &lt;A href="https://databrickslabs.github.io/overwatch/" alt="https://databrickslabs.github.io/overwatch/" target="_blank"&gt;documentation&lt;/A&gt; for installation instructions.&lt;/P&gt;</description>
      <pubDate>Fri, 18 Jun 2021 11:33:16 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/what-is-overwatch/m-p/22831#M15711</guid>
      <dc:creator>alexott</dc:creator>
      <dc:date>2021-06-18T11:33:16Z</dc:date>
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