While autoscaling provides the elasticity that customers require for their big data workloads, it can lead to exorbitant runaway waste and cost and management complexity. Estimating the right number of cluster nodes for a workload is difficult; user-initiated cluster scaling requires manual intervention, and mistakes are often costly and disruptive. Join Pepperdata Field Engineer Alex Pierce for this discussion about operational challenges associated with maintaining optimal big data performance in the cloud, what milestones to set, and recommendations on how to create a successful cloud migration framework.
Learn More About How to Drive Cloud Performance on Amazon EMR with Autoscaling
If you enjoyed the webinar and would like to learn more about how Pepperdata can help you improve cloud performance with Amazon EMR autoscaling, try one of the following resources:
- Get the Pepperdata TPC-DS Benchmark Report: A Better Way to Scale Your Cloud Service Providers
- Learn More about Pepperdata for Amazon EMR
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