Tony

# Slow query investigation
@tony analyze slow queries on production PostgreSQL

# Specific performance target
@tony identify queries with execution time >2 seconds on orders database

# Execution plan analysis
@tony analyze execution plans for the 20 slowest queries

# Query patterns
@tony find queries that could benefit from caching

# Index recommendations
@tony analyze missing indexes that would improve performance by >10%

# Connection optimization
@tony review connection pooling configuration for high-load scenarios

# Configuration tuning
@tony optimize MySQL 8.0 configuration for high-throughput OLTP with 10k connections

# Resource analysis
@tony identify queries consuming >5% of total database CPU

# Health check
@tony check database health and performance metrics

# Replication status
@tony assess replication lag and recommend optimization

# Storage analysis
@tony analyze database growth patterns and recommend archiving strategy

# Connection analysis
@tony analyze connection usage patterns and identify connection leaks

# Backup verification
@tony verify backup status and recovery procedures for production databases

# DR planning
@tony create disaster recovery plan with RTO/RPO analysis

# Recovery testing
@tony recommend backup testing strategy for production databases

@tony #dashboard database performance metrics for production cluster
@tony #report query performance analysis with optimization plan
@tony #recommend index optimizations prioritized by impact
@tony #alert when P95 query latency exceeds 500ms

# Good
@tony analyze queries with
execution time >2 seconds
running >100 times daily

# Avoid
@tony make database faster

# Good
@tony optimize MySQL 8.0
for read-heavy workloads
with 10k concurrent connections

# Avoid
@tony check the database

# Step 1: Identify
@tony identify top 10 slowest queries in last hour

# Step 2: Analyze
@tony analyze execution plans for problematic queries

# Step 3: Optimize
@tony #recommend index changes and query rewrites

# Step 4: Monitor
@tony #dashboard real-time query performance

# Step 1: Baseline
@tony #dashboard current performance metrics

# Step 2: Analyze
@tony identify optimization opportunities across all databases

# Step 3: Prioritize
@tony #recommend optimizations ranked by impact and effort

# Step 4: Automate
@tony #schedule weekly performance review

# Step 1: Analyze growth
@tony analyze database growth patterns over last 6 months

# Step 2: Forecast
@tony predict storage and compute needs for next year

# Step 3: Plan
@tony #recommend scaling strategy with cost analysis