BetterDB-inc/monitor

Real-time monitoring, slowlog analysis, and audit trails for Valkey and Redis

What it solves

BetterDB Monitor is a monitoring layer for Valkey and Redis databases. It solves the problem of volatile monitoring data—such as slowlogs, command patterns, and client activity—that typically disappears after log rotations or restarts, by persisting this data for historical analysis and debugging.

How it works

The tool connects to a Valkey or Redis instance and captures metrics, logs, and activity. It provides a a variety of storage backends (PostgreSQL, SQLite, Turso, or in-memory) to ensure data persistence. It features native support for Valkey 8.x specific features like COMMANDLOG and CLUSTER SLOT-STATS and offers a Web UI, REST API, and Prometheus endpoint for data access.

Who it’s for

It is designed for database administrators and developers who need deep visibility into their Valkey/Redis clusters, especially for debugging "3am" incidents, auditing ACL access, and managing vector search performance in AI applications.

Highlights

  • Historical Analytics: Persists slowlogs and command patterns across any time range.
  • Valkey 8.x Native: Support for COMMANDLOG and per-thread I/O metrics.
  • AI Observability: Dedicated tools for vector search latency, semantic cache hit-rates, and OTLP AI traces.
  • Cluster Visibility: Topology graphs and SLOT-STATS heatmaps for cluster distribution.
  • Extensibility: Includes an MCP server for AI agents (Claude Code, Cursor) and a Prometheus endpoint.
  • Anomaly Detection: Automatic baseline learning with plain-English diagnoses.

Related

  • Project
    redis/redis

    Redis is a high-performance, in-memory data structure server and vector query engine used for caching, real-time analytics, and GenAI memory.

  • Project
    redis/redis-vl-python

    An AI-native Python client for Redis that provides tools for vector search, hybrid search, and production-ready extensions for LLM memory and semantic caching.

  • Project
    tickernelz/opencode-mem

    A persistent memory system for AI coding agents that uses a local vector database to retain long-term technical context and user preferences across sessions.

  • Project
    QoderAI/better-harness

    Better Harness is an open‑source tool that analyses the whole workflow of AI coding agents (Claude Code, Codex, Qoder, Cursor, GitHub Copilot, etc.). It gathers project and session evidence, evaluates five dimensions of the *Agent Work Loop* (task understanding, controlled execution, change validation, reliable delivery, learning capture), and produces a visual HTML report with prioritized, evidence‑backed findings and repair suggestions. Missing evidence is shown explicitly, helping teams improve repeatability, validation, and learning while still benefiting from AI‑generated code.

  • Project
    icey1287/SuperMew

    SuperMew is a self‑hosted, audit‑first RAG/agent platform. It persists threads, runs, events and document versions, offers hybrid Milvus+BM25 retrieval, supports HITL checkpoints, versioned skills/tools, a frozen model control plane, and a built‑in evaluation framework. The stack uses FastAPI, PostgreSQL, Redis, Milvus, and a Vue 3 frontend, and can be run locally with Docker‑Compose or deployed in production with systemd/K8s.