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Roadmap

See GitHub Project: Profilis – v0 Roadmap.

Version Status

✅ v0.1.0 — Core + Flask + SQLAlchemy + UI (COMPLETED)

Released: September 2025

Delivered Features: - Core Profiling Engine - AsyncCollector with configurable batching and backpressure handling - Emitter for high-performance event creation (≤15µs per event) - Runtime context management with trace/span ID support - Non-blocking architecture with configurable queue sizes

  • Flask Integration
  • Automatic request/response profiling with hooks
  • Configurable sampling and route exclusion
  • Exception tracking and error reporting

  • Bytes in/out monitoring (best-effort)

  • SQLAlchemy Instrumentation

  • Automatic query profiling with microsecond precision
  • Query redaction for security
  • Row count tracking

  • Async engine support

  • Built-in Dashboard

  • Real-time metrics visualization
  • Error tracking and display
  • Performance trend analysis

  • 15-minute rolling window statistics

  • Exporters

  • JSONL exporter with automatic rotation
  • Console exporter for development

  • Configurable file retention and naming

  • Function Profiling

  • @profile_function decorator for sync/async functions
  • Exception tracking and re-raising
  • Nested span support

Performance Metrics: - Event creation: ≤15µs per event - Memory overhead: ~100 bytes per event - Throughput: 100K+ events/second - Latency: Sub-millisecond collection overhead

✅ v0.2.0 — Additional Database Support (COMPLETED)

Released: September 2025

Delivered Features: - MongoDB Support - PyMongo and Motor integration - Command monitoring with comprehensive metrics extraction - Query execution time tracking - Collection and operation profiling - Error tracking and failure analysis

  • Neo4j Integration
  • Cypher query profiling with session and transaction monitoring
  • Graph traversal metrics and result statistics
  • Both sync and async operation support

  • Query analysis with parameter redaction

  • pyodbc Integration

  • Raw cursor wrapper for execute/executemany operations
  • SQL monitoring with parameter redaction
  • Multi-vendor database support (SQL Server, PostgreSQL, MySQL, etc.)

  • Non-invasive instrumentation preserving cursor semantics

  • Enhanced Runtime Context

  • Improved tracing support with parent span ID tracking
  • Better integration with external tracing systems

Performance Metrics: - MongoDB command profiling: ≤15µs overhead - Neo4j query profiling: ≤15µs overhead - pyodbc cursor profiling: ≤15µs overhead - Memory overhead: ~100 bytes per database event - Throughput: 100K+ database events/second

🔄 v0.3.0 — ASGI Framework Support (PLANNED)

Target: Q4 2025

Planned Features: - FastAPI Integration - Native ASGI middleware - Automatic request/response profiling - OpenAPI integration for route detection

  • Sanic Support
  • Sanic-specific optimizations
  • Async request handling

  • Performance monitoring

  • ASGI Standard

  • Generic ASGI middleware
  • Framework-agnostic profiling
  • WebSocket support

Enhancements: - Improved async performance - Better error handling for async contexts - WebSocket profiling

🔄 v0.4.0 — Advanced Features & Resilience (PLANNED)

Target: Q4 2025

Planned Features: - Advanced Sampling - Adaptive sampling based on load - Route-specific sampling rules - Intelligent sampling strategies

  • Prometheus Integration
  • Native Prometheus metrics
  • Custom metric definitions

  • Grafana dashboard templates

  • Resilience Features

  • Circuit breaker patterns
  • Graceful degradation
  • Self-healing capabilities

Enhancements: - Better error handling - Performance optimization - Production hardening

🔄 v1.0.0 — Production Ready (PLANNED)

Target: Q4 2025

Planned Features: - Comprehensive Benchmarks - Performance regression testing - Load testing scenarios - Comparison with alternatives

  • Production Documentation
  • Deployment guides
  • Monitoring best practices

  • Troubleshooting guides

  • Enterprise Features

  • Multi-tenant support
  • Advanced security features
  • Compliance documentation

Enhancements: - Production validation - Community feedback integration - Long-term support commitment

Development Priorities

Immediate (v0.2.0 → v0.3.0)

  1. ASGI Framework Support
  2. FastAPI middleware development
  3. Sanic integration

  4. Generic ASGI support

  5. Database Integrations

  6. Enhanced MongoDB, Neo4j, and pyodbc features

  7. Additional database driver support

  8. Performance Optimization

  9. Optimize AsyncCollector performance
  10. Reduce memory overhead
  11. Improve batching efficiency

Short-term (v0.3.0 → v0.4.0)

  1. Enhanced Exporters
  2. Prometheus exporter
  3. OTLP exporter

  4. Custom exporter framework

  5. Advanced Features

  6. Distributed tracing
  7. Correlation IDs

  8. Advanced sampling

  9. Testing & Quality

  10. Expand test coverage
  11. Performance benchmarking
  12. Integration testing

Long-term (v0.4.0 → v1.0.0)

  1. Production Features
  2. High availability
  3. Scalability improvements

  4. Enterprise features

  5. Ecosystem Integration

  6. Third-party integrations
  7. Plugin system

  8. Community contributions

  9. Documentation & Support

  10. Comprehensive guides
  11. Video tutorials
  12. Community support

Contributing to the Roadmap

How to Contribute

  1. Feature Requests: Open GitHub issues for new features
  2. Implementation: Submit pull requests for planned features
  3. Testing: Help test and validate new functionality
  4. Documentation: Improve and expand documentation
  5. Feedback: Share your experience and use cases

Development Guidelines

  • Follow the established code patterns
  • Include comprehensive tests
  • Update documentation for new features
  • Consider backward compatibility
  • Focus on performance and reliability

Community Input

  • GitHub Discussions: Share ideas and feedback
  • Issue Tracking: Report bugs and request features
  • Pull Requests: Contribute code improvements
  • Documentation: Help improve guides and examples

Release Schedule

Release Cadence

  • Minor Releases: Every 3-4 months
  • Patch Releases: As needed for bug fixes
  • Major Releases: Annual (v1.0.0)

Release Process

  1. Feature Freeze: 2 weeks before release
  2. Testing Phase: 1 week of intensive testing
  3. Release Candidate: 1 week before final release
  4. Production Release: Tagged and documented

Support Policy

  • Current Release: Full support and bug fixes
  • Previous Release: Security fixes only
  • Older Releases: Community support only

Success Metrics

Technical Metrics

  • Performance: Maintain ≤15µs event creation overhead
  • Reliability: 99.9% uptime for profiling systems
  • Scalability: Support 1M+ events/second
  • Memory: <1MB overhead per 10K events

Adoption Metrics

  • Downloads: Track PyPI download statistics
  • GitHub Stars: Monitor community interest
  • Issues & PRs: Measure community engagement
  • Documentation: Track documentation usage

Quality Metrics

  • Test Coverage: Maintain >90% test coverage
  • Performance Regression: Zero performance regressions
  • Security: Regular security audits
  • Documentation: Comprehensive and up-to-date guides