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Cost Optimizer (Cloud Data Platforms)

DevOps & Security
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Analyzes and optimizes costs for cloud data platforms

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How to use this skill

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Source SKILL.md: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/data-engineering-analytics/skills/cost-optimizer/SKILL.md

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Cost Optimizer (Cloud Data Platforms)

Overview

Analyzes and optimizes costs for cloud data platforms. This skill provides deep expertise in platform-specific cost structures and optimization strategies.

Capabilities

  • Snowflake credit analysis and optimization
  • BigQuery slot and on-demand optimization
  • Redshift node sizing
  • Storage cost optimization
  • Query cost estimation
  • Warehouse scheduling recommendations
  • Data lifecycle policy recommendations
  • Reserved capacity planning

Input Schema

{
  "platform": "snowflake|bigquery|redshift|databricks",
  "usageMetrics": "object",
  "billingData": "object",
  "queryHistory": "object"
}

Output Schema

{
  "currentCost": "number",
  "optimizedCost": "number",
  "savings": "percentage",
  "recommendations": [{
    "category": "string",
    "action": "string",
    "impact": "number",
    "effort": "low|medium|high"
  }]
}

Target Processes

  • Data Warehouse Setup
  • Query Optimization
  • Pipeline Migration

Usage Guidelines

  1. Provide platform-specific usage metrics
  2. Include billing data for cost baseline
  3. Share query history for optimization analysis
  4. Prioritize recommendations by impact and effort

Best Practices

  • Regularly review and optimize warehouse sizes
  • Implement auto-suspend and auto-resume policies
  • Use clustering and partitioning to reduce scan costs
  • Consider reserved capacity for predictable workloads
  • Monitor and alert on cost anomalies