Eliminate Spark Application Waste with Real-Time Cost Optimization

As organizations rely on big data workloads with Apache Spark, many see waste and cost overruns as unavoidable. However, this blog argues that Spark application waste isn't a sunk cost. It explores cost control methods at the cluster and application levels, like observability, monitoring, autoscaling, rightsizing, manual tuning, and Spark Dynamic Allocation. These methods often address only part of the problem. The root cause is overprovisioning for peak usage. The blog introduces Real-Time Cost Optimization (RTCO) to dynamically reallocate resources, reducing costs by up to 47%. A case study shows Autodesk cutting Amazon EC2 costs by over 50% using RTCO.

Vendor:: Pepperdata
Posted:: Oct 24, 2024
Published:: Oct 25, 2024
Format:: HTML
Type:: Blog

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