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MySQLTuner-perl Roadmap

This document outlines the strategic direction and future development plans for MySQLTuner-perl. Our mission is to provide the most stable, portable, and reliable performance tuning advisor for MySQL-compatible databases.

👤 Governance

To ensure consistency and high-density development, the following roles are defined for roadmap orchestration:

  • Owner: Jean-Marie Renouard (@jmrenouard) - Ultimate authority on the project, constitution, and core mission.
  • Product Manager: Antigravity (AI Agent) - Responsible for backlog management, specification design, and execution tracking of the roadmap items.
  • Release Manager: Antigravity (AI Agent) - Responsible for technical validation, testing orchestration, and unified release cycle execution.

🌟 Strategic Pillars

  1. Production Stability & Safety: All recommendations must be verified and safe for production.
  2. SQL Modeling & Schema Design: Beyond operational tuning, provide deep insights into database architecture.
  3. Zero-Dependency Portability: Maintain single-file architecture with core-only dependencies.
  4. Modern Ecosystem Support: Seamless integration with Containers (Docker/K8s) and Cloud providers.

🚀 Development Phases

Phase 1: Stabilization & Observability (v2.8.31 - v2.8.33) [COMPLETED]

  • Metadata-Driven CLI Options: Refactored option parsing to centralize defaults, validation, and documentation.
  • Enhanced SQL Modeling: Expanded diagnostic checks for Foreign Key type mismatches, missing indexes, and schema sanitization.
  • Structured Error Log Ingestion: Supported performance_schema.error_log for diagnostic ingestion (MySQL 8.0+).
  • Refined Reporting: Improved data richness in the "Modeling Analysis" tab.

Phase 2: Advanced Diagnostics [IN PROGRESS]

  • Plugin & Hook Stability: Formalize the custom hook mechanism (verified for MySQL and SSL) to enable scalable third-party integrations.
  • Compliance Awareness Framework: Specialized audit profiles (--audit-pci, --audit-hipaa, --audit-gdpr) to verify regulatory configuration requirements.
  • Index Audit 2.0: Integrate performance_schema to detect redundant and unused indexes.
  • Transactional Contention Analysis: Detect patterns leading to deadlocks and high lock wait times.
  • Buffer Pool Advisory: More granular analysis of InnoDB Buffer Pool usage and resizing recommendations.
  • Kernel & Architecture Health: Implement io_uring support detection and kernel setting verification.

Phase 3: Automation & Ecosystem

  • Infrastructure-Aware Tuning: Detect storage types (NVMe/SSD) and hardware architectures (ARM64/Graviton).
  • Sysbench Metrics Integration: Automated baseline capture and performance comparison within the report.
  • Multi-Cloud Autodiscovery: Automated detection of RDS, GCP, and Azure specific performance flags and optimizations.
  • Query Anti-Pattern Detection: Use performance_schema to identify non-SARGable queries and SELECT * abuse.
  • Modular Reporting Engine: Refactor Jinja2 templates for dynamic section injection.
  • Historical Trend Analysis: (Experimental) Allow the script to ingest previous run data to identify performance regressions.

Phase 4: Advanced Intelligence & Ecosystem

  • Smart Migration LTS Advisor: Provide risk reports for upgrading between major versions.
  • Weighted Health Score: Implement a unified KPI (0-100) based on Security, Performance, and Resilience.

🤝 Contribution & Feedback

We welcome community feedback on this roadmap. If you have specific feature requests or want to contribute to a specific phase, please open an issue on our GitHub repository.