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FlowMQ Public Roadmap ​

This document outlines the planned features and development direction for FlowMQ. Our goal is to be transparent with our community about our priorities and where the project is headed. Please note that timelines are estimates and subject to change based on development progress and community feedback.

Guiding Principles ​

Our development is guided by these core principles:

  • Performance & Efficiency: Strive for best-in-class latency and throughput with a minimal resource footprint.
  • Reliability & Durability: Data safety is non-negotiable. FlowMQ is built to be a system of record you can trust.
  • Developer Experience: Provide simple, powerful, and intuitive APIs, client SDKs, and documentation.
  • Operational Simplicity: Make it easy to deploy, manage, monitor, and scale FlowMQ clusters.

Q3 2024: Foundational Enhancements ​

  • ✅ SDKs for Core Languages: Launch stable, well-documented SDKs for Go, Java, and Rust.
  • 🚧 TLS Encryption: Implement end-to-end TLS encryption for all client-broker communication, securing data in transit.
  • 🚧 Python SDK: Develop and release an officially supported, feature-complete Python SDK to serve one of the largest developer communities.
  • ▶️ Schema Registry (Alpha): Launch an initial version of a central service for managing and validating message schemas (e.g., Protobuf, Avro), helping to maintain data quality and compatibility.

Q4 2024: Scaling and Management ​

  • ▶️ High Availability (HA) Clustering: Introduce a multi-broker, fault-tolerant deployment mode. This will include automated leader election, data replication, and seamless failover to ensure the broker remains available during node failures.
  • ▶️ Broker Web Dashboard: Create an administrative UI for monitoring broker health, inspecting topics and queues, visualizing message throughput, and tracking consumer lag.
  • ▶️ C++ SDK: Release a high-performance C++ SDK for native applications where low-level control and efficiency are critical.
  • ▶️ Message Time-to-Live (TTL): Implement functionality to automatically expire messages from queues and streams after a configured duration.

H1 2025 and Beyond: Ecosystem and Advanced Features ​

  • Tiered Storage: Investigate and implement a tiered storage system that can automatically move older stream data from fast, expensive storage (like SSDs) to cheaper, long-term object storage (like S3 or GCS). This will enable infinite, cost-effective stream retention.
  • Edge-Optimized Deployments: Design a lightweight, low-footprint version of the FlowMQ broker specifically for IoT and edge computing use cases.
  • Plugin Architecture: Develop an extensibility framework that allows users to create and load custom plugins for authentication, authorization, and message transformation logic.
  • Official Kubernetes Operator: Build and support a Kubernetes Operator to simplify the deployment, scaling, and management of FlowMQ clusters in cloud-native environments.

Legend ​

  • ✅ Done: Completed and released.
  • 🚧 In Progress: Actively in development.
  • ▶️ Planned: Scoped and prioritized for the upcoming quarter.
  • Research: Exploring feasibility and design.

We Want Your Feedback! ​

This roadmap is a living document. If you have a feature request or want to contribute, please open an issue on our GitHub repository.

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