Session
Hands-Off Rightsizing: How We Tuned Spark Resource Requests Automatically
Rokt automated resource optimization across 1,000+ daily Spark jobs running on Amazon EKS. The talk covers the JVM visibility gap that makes Spark uniquely difficult to rightsize, Rokt's graduated rollout approach using ScaleOps, and the real-world results: 30–35% reduction in CPU and memory requests. Hear from a hands-on experience our practical gotchas around policy segmentation, data skew, and Spot instance compounding.
Slide Deck: https://docs.google.com/presentation/d/1xYAY9T7roBzejfxc9bbGVz6QBRggguCvOypwFzPaJX0
Meetup Link: https://luma.com/p18cq1vz
Bruno Chauvet
Compute Platform Lead at Rokt
New York City, New York, United States
Links
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