artemis-studio
Artemis Studio is a one-console cluster-wide management and observability solution for Apache ActiveMQ Artemis.
Ficha actualizada 22 sept 2026, 20:22 · upstream 22 sept 2026, 20:01 · release sin release detectada
Qué es artemis-studio
Descripción editorial construida a partir del repositorio, su documentación y sus señales de mantenimiento.
Artemis Studio treats the entire cluster as a single unit of management, allowing one instance to serve multiple clusters. It works against existing brokers without starting new ones, preserving your current broker.xml configuration while adding comprehensive visibility across all nodes. The tool provides live topology with replication state, cross-node queue grids, message flow visualization, and SQL queries that can inspect messages directly from the broker. It also offers governance features including sensitive data masking, PII classification, role-based access control, API token management, and an audit trail for every change made to the cluster configuration.
The platform is built on four core principles: it is designed to be broker-friendly by construction through batched reads that never pollute a single queue with multiple requests; it defaults to safe operations requiring dry-run confirmation before destructive actions like purge or delete; HA state is determined solely from live node information rather than configuration files, ensuring split-brain detection; and all features are explicitly gated so unavailable capabilities show the exact broker.xml fragment needed to enable them. This design ensures Studio never becomes a bottleneck that causes brokers to fail.
The tool supports Java 25 with Spring Boot 4.1, PostgreSQL with Liquibase for schema management, React 19 with Vite and Mantine 9 for the UI framework, TanStack Router/Query/Table for routing and data fetching, React Flow for visualizing complex message flows, Jolokia over HTTP as the primary communication protocol with the Artemis Core client as a fallback, Server-Sent Events (SSE) for real-time updates, and a single container image. The architecture is documented in detail on the official site with 88 reference decisions recorded.
- Monitor live topology across multiple ActiveMQ clusters to identify which nodes are healthy and detect split-brain scenarios
- Visualize cross-node queue grids to understand message routing paths, diverts, bridges, and cluster hops in real time
- Track message flow from application producers through addresses, queues, and consumers with rate limiting visibility
- Query messages directly via SQL against the broker using JMS selector syntax for header-only predicates without scanning message bodies
- Monitor consumer health by tracking depth trends, consumption velocity, and root-cause context for slow-consumer issues
- Manage sensitive data through automatic PII classification and redaction based on viewer role permissions
- Implement governance with scoped roles across environment → cluster levels, API token management, and audit trails for every configuration change
- Deploy broker configurations canary-first by applying changes to a subset of nodes before full rollout
- Live topology visualization showing replication state, HA roles, and split-brain alerts without requiring broker restarts
- Cross-node queue grids that display every queue on every node in a single virtualized table for unified inspection
- SQL Console allows direct message-level queries using JMS selector syntax with read-only SELECT operations that cannot modify the cluster
- Message flow visualization shows application-to-address routing, diverts, bridges, and consumer consumption rates at a glance
- Broker configuration management via a canvas interface where you declare settings and compose routing between components
- Automatic PII classification and redaction based on viewer role, with sensitive headers masked by default
- OpenSpec CI/CD pipeline that proposes changes to the application code before applying them to production builds
- The SQL Console is read-only and cannot modify cluster state or alter message routing configurations
- Cross-node queue visibility requires all nodes in a cluster to be running; isolated brokers are not visible
- Message flow visualization only shows active messages; dead-letter queues may remain invisible without capture enabled
- Consumer health metrics require at least one consumer per node to function properly
- The tool does not provide native message delivery guarantees or acknowledgment mechanisms beyond what Artemis provides out of the box
- Split-brain detection is limited to HA roles polled from live nodes and may miss edge cases where configuration overrides node state
- Message capture for DLQs requires explicit enablement per queue, which can be resource-intensive in large clusters
Perfil de infraestructura
Estimación inicial derivada del repositorio y de los servicios detectados.
Despliegue detectado
Qué señales reales de instalación hemos encontrado.
Deploy Artemis Studio using Docker Compose with the compose.prod.yaml template. The tool runs as a single container image and exposes port 8080. Use environment variables to set the database URL, user credentials, secret key for Jolokia authentication, and any broker-specific configuration. For production environments, consider mounting your existing broker.xml into the container or using an external controller like Artemis Gateway. Always apply changes canary-first by deploying a subset of nodes before full rollout. Monitor the SSE stream for real-time topology updates and watch the admin password change on first login to ensure it is updated with your new credentials.
Stack y dependencias
Componentes inferidos a partir de manifests, configuración y documentación.
Puede sustituir a
Relaciones detectadas por el análisis del repositorio y su categoría.
Experiencia real de la comunidad
Ayuda a contrastar la estimación automática con instalaciones reales.
Todavía no hay datos comunitarios para este proyecto.