Apache StarRocks on EKS: Scaling for Big Data OLAP

Enterprise teams are running into scaling challenges with Apache StarRocks on Kubernetes. TLDR DevOps shares how to optimize using KEDA and Karpenter for auto-scaling OLAP workloads.\n\nKey insights: KEDA handles horizontal scaling based on query load, while Karpenter manages vertical scaling by allocating dedicated nodes. This combination reduces cold start latency and improves query performance for large datasets.\n\nWhy this matters for us: Big data teams will save costs by scaling StarRocks clusters more efficiently — no more over-provisioned clusters or underutilized nodes.