Cost optimization

The cost optimization pillar includes the continual process of refinement and improvement of a system over its entire lifecycle to optimize cost. Cost optimization is a key effort, from the initial design of your first proof of concept, to the ongoing operation of production workloads. It’s a years-long, continual process. Choose the right solution and pricing model. Build cost-aware systems that allow you to achieve business outcomes and minimize costs. To perform cost optimization over time, you should identify data, infrastructure resources, and analytics jobs that can be removed or downsized.

Determine the analytics workflow costs at each individual data processing step or individual pipeline branch. The benefit of understanding analytics workflow costs at this granular level will help you decide where to focus engineering resources for development, and to perform a return on investment (ROI) estimation for the analytics portfolio as a whole.

Best practices

• 11 – Choose cost-effective compute and storage solutions based on workload usage patterns
• 12 – Build financial accountability models for data and workload usage
• 13 – Manage cost over time
• 14 – Use optimal pricing models based on infrastructure usage patterns