Handling High Data Volumes in Cloud Environments: Lessons from the Field

As data continues to grow exponentially, handling high-volume workloads in the cloud is no longer just about scaling up—it’s about smart pre-planning, efficient resource management, and continuous cost optimization.

🔹 Pre-Planning is Critical Before ingesting terabytes or petabytes of data, define data patterns, peak loads, retention policies, and SLAs. Designing the right architecture early helps avoid expensive rework later.

🔹 Right-Sizing & Resource Management Auto-scaling, workload isolation, and choosing the right compute and storage tiers make a huge difference. Over-provisioning wastes money, while under-provisioning impacts performance—balance is key.

🔹 Data-Aware Architecture Partitioning strategies,…

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