TODO

Lists 40+ planned features and improvements for a database proxy, organized into categories like security, monitoring, and deployment.

jonaylor89

May 2, 2026

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ai rag

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What this file does

Lists 40+ planned features and improvements for a database proxy, organized into categories like security, monitoring, and deployment.

When to use it

Brainstorming feature roadmap for a database proxy or middleware
Evaluating what production-readiness enhancements to add to a database tool
Planning monitoring and observability for a database proxy
Designing security hardening features for database access

Assumes this stack

PostgreSQLPrometheusDockerHelm

Core Functionality

Dry-run mode: Add --dry-run flag to preview queries without execution
Query preview: Show first 5 rows that would be affected by DELETE/UPDATE
Enhanced SQL parsing: Support more complex queries (JOINs, subqueries, CTEs)
Transaction support: Handle multi-statement transactions properly
Connection pooling: Optimize database connections for better performance

Enhanced Security

Multiple honeytokens: Support configurable canary table names
IP-based restrictions: Block/allow specific IP ranges
Rate limiting: Prevent query spam from clients
User authentication: Proxy-level user validation before DB access
Query signature detection: Block known dangerous query patterns

Configuration & Flexibility

Per-table row limits: Configure different thresholds per table
```
[table_limits]
users = 100
products = 1000
logs = 10000
```
Regex-based table matching: sensitive_* tables with stricter limits

Monitoring & Observability

Structured JSON logging: Machine-readable log format
Metrics endpoint: Prometheus metrics on /metrics?
Query history: Store and review blocked/allowed queries

Backup Integration

Real snapshot support: Integration with pg_dump or cloud backups
Backup verification: Ensure backups are valid before destructive queries
Point-in-time recovery: Automatic backup before major operations
Configurable backup storage: S3, GCS, local filesystem support

Query Analysis

Query cost estimation: Use EXPLAIN to predict query performance
Execution plan analysis: Block queries with expensive operations
Index usage detection: Warn about queries not using indexes
Query optimization suggestions: Recommend better query patterns

Integration & APIs

REST API: Control proxy settings via HTTP endpoints
Webhook notifications: Send alerts to Slack/Discord on blocks
Database migration support: Safe handling of schema changes
Multiple database support: MySQL, SQLite proxy variants

Testing & Development

Query simulation: Test mode with fake data responses
Fuzzing support: Automated testing with random queries
Benchmark suite: Performance testing framework
Integration tests: Full end-to-end testing setup

Production Readiness

Performance

Async query processing: Non-blocking query analysis
Connection reuse: Pool management for database connections
Query caching: Cache COUNT query results for similar patterns
Batch query analysis: Process multiple queries efficiently

Security Hardening

TLS support: Encrypted connections between client/proxy/database
Certificate validation: Proper SSL/TLS certificate handling

Deployment

Helm chart: kinda OD but why not
Multi-architecture builds: ARM64 and AMD64 Docker images
Health checks: Proper liveness/readiness probes

Documentation

Architecture docs: System design and component overview
Configuration reference: Complete settings documentation
Troubleshooting guide: Common issues and solutions
Performance tuning: Optimization recommendations

Quality of Life

Analytics

Usage statistics: Track query patterns and blocked attempts
Alerting rules: Custom alert conditions for suspicious activity
Report generation: Automated security and usage reports

What's inside

9 feature categories with 40+ bullet points, 1 code example, and 1 table snippet

Change this for your project

Replace jonaylor89/pg_guard with your own repository name
Replace example table names like users, products, logs with your own
Replace sensitive_* regex pattern with your own table matching rules

Where it goes

Save in docs/ or the repository root. Gives agents and new contributors a map of the codebase.

Worth borrowing

Organizing a wishlist by maturity stages (core, production, quality of life)
Using TOML for per-table configuration limits
Including concrete metrics endpoints like /metrics for Prometheus