Databricks Summit ’23 Talk: “How we built Gradient to optimize Databricks clusters at scale”
Databricks Summit ’23 Talk: “How we built Gradient to optimize Databricks clusters at scale”
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Summary In this blog post, we’ll explore how you can integrate Sync’s Gradient with Airflow. We’ll walk through the steps to create a DAG that will submit a run to Databricks, and then make a call through Sync’s library to generate a recommendation for an optimized cluster for that task. This DAG example can be
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Introduction: Using Gradient in a Workflow Gradient, the latest product release from Sync Computing, helps customers manage the infrastructure behind their recurring Apache Spark applications. Gradient gives infrastructure recommendations for each job to lower the cost of their Production jobs while hitting their target SLA’s. We’ve been hard at work on this project for a
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Introduction Sync recently introduced Gradient, a tool that helps data engineers manage and optimize their compute infrastructure. The primary facet of Gradient is a Project which groups a sequence of runs of a Databricks job. After each run, the Spark eventlog and cluster information is sent to Sync. That accumulated project data is then fed
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Wow the day is finally here! It’s been a long journey, but we’re so excited to announce our newest product: Gradient for Databricks. Checkout our promo video here! The quick pitch Gradient is a new tool to help data engineers know when and how to optimize and lower their Databricks costs – without sacrificing performance.
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Insider’s engineering blog discusses how they integrated the Sync Gradient API into their Airflow pipelines to continuously monitor and reduce costs.
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