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Data Performance Optimization

Optimize data pipeline and query performance including indexing, partitioning, caching, query tuning, and infrastructure scaling.

Complexity: Complex | Duration: 30m+ | Category: Devops

Tags: data-engineering performance optimization database

Workflow Diagram​

Steps​

Step 1: Performance profiling​

Agent: database

architect - Identify slow queries, bottlenecks

Step 2: Query analysis​

Agent: database

architect - Analyze execution plans (EXPLAIN)

Step 3: Index optimization​

Agent: database

architect - Create, modify, or remove indexes

Step 4: Partitioning​

Agent: database

architect - Partition large tables by date/range

Step 5: Materialized views​

Agent: database

architect - Pre-compute expensive aggregations

Step 6: Caching layer​

Agent: data

engineer - Implement Redis/Memcached for hot data

Step 7: Query tuning​

Agent: database

architect - Rewrite inefficient queries

Step 8: Infrastructure scaling​

Agent: devops

engineer - Vertical/horizontal scaling if needed

Usage​

To execute this workflow:

/workflow devops/data-performance-optimization.workflow

See other workflows in this category for related automation patterns.