Pinterest developed the Hadoop Control Center (HCC) to automate the scaling and migration of its Hadoop clusters, remedying operational challenges faced in managing extensive YARN clusters on AWS. Previously, fixed-size Auto Scaling Groups impeded autoscaling capabilities, leading to labor-intensive adjustments and potential inefficiencies. HCC now streamlines this process by enabling real-time scaling actions through a unified command-line interface. It utilizes a manager-worker architecture distributed across Virtual Private Clouds to handle node management safely, maintaining data integrity and service continuity during operations.
Pinterest's Hadoop Control Center (HCC) automates the management of Hadoop clusters, transforming manual workflows into a fully automated system that enhances efficiency and scalability.
The previous manual process for managing Hadoop infrastructure was time-consuming and error-prone, requiring significant human intervention for scaling operations which often led to resource waste.
HCC utilizes a manager-worker architecture to ensure real-time management of Hadoop clusters, coordinating between various AWS services and Hadoop components for efficiency.
Scaling actions can now be requested through a unified command-line interface, enabling safe decommissioning and maintaining service continuity without disruption to batch workloads.
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