apache/rocketmq-dashboard

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# RocketMQ Studio **English** | [中文](README_zh.md) > Cross-cluster · Cross-architecture unified RocketMQ management platform RocketMQ Studio is a unified management platform for RocketMQ, supporting multi-cluster and multi-architecture environments. It provides instance management, cluster operations, Topic / Consumer Group CRUD, ACL permission control, message query and tracing, dead letter queue handling, monitoring alerts, audit logs, and an AI assistant. ## Start with AI You can use an AI coding agent (Claude Code, Qoder, Cursor, etc.) to set up and launch Studio. Open the agent at the repository root and paste the prompt below: ```text Set up and run RocketMQ Studio locally from this repository: 1. Check that Docker and Docker Compose are installed. If not, tell me how to install them and stop. 2. Create the shared network if it does not exist: `docker network inspect rocketmq_net >/dev/null 2>&1 || docker network create rocketmq_net`. 3. Build and start Studio: `docker compose -f deploy/docker-compose.yml up -d --build`. 4. Wait for the backend to become healthy, then open http://127.0.0.1:6789 and confirm the page loads. Report the running containers and any errors. Do not modify source code or create commits. ``` To also start the optional bundled RocketMQ demo cluster, insert `docker compose -f deploy/rocketmq/docker-compose.yml up -d` before step 3 and wait until its `ps` output is healthy. ## Quick Start Run from the repository root: ```bash # 1. Create the shared Docker network (the compose files attach to it as external) docker network inspect rocketmq_net >/dev/null 2>&1 || docker network create rocketmq_net # 2. Build and start RocketMQ Studio (mysql + rocketmq-server + rocketmq-web) docker compose -f deploy/docker-compose.yml up -d --build ``` Then visit **http://127.0.0.1:6789**. This starts only Studio and its own MySQL database — enough to open the console, log in, and explore the UI. No RocketMQ cluster is bundled here; register an instance pointing at your own RocketMQ to manage real resources, or start the optional demo cluster in [Bundled RocketMQ Cluster](#bundled-rocketmq-cluster-optional) below. The default schema creates only Studio tables. It does not seed instances, topics, consumer groups, or ACL records. Development-only sample data can be imported explicitly from `deploy/mysql/`; it is not part of the default deployment. Import `upgrade-demo-instance.sql` first and then `upgrade-demo-acl.sql`; both scripts target the current numeric-ID schema and are idempotent. They are sample-data loaders, not upgrade migrations, and should never be imported into a production database. **Studio ports:** Frontend 6789 (Nginx, also proxies `/api`), Backend 8888 (Spring Boot, container-internal — published only when the backend runs outside compose) To enable login protection for a shared environment, copy `deploy/.env.example` to `deploy/.env`, set `STUDIO_AUTH_LOGIN_REQUIRED=true`, and configure `STUDIO_AUTH_ADMIN_USERNAME` / `STUDIO_AUTH_ADMIN_PASSWORD`. These configured credentials are a bootstrap seed: on the first login against an empty database Studio creates the configured users in the `rmq_studio_user` table, and the database becomes the source of truth afterwards. Administrators manage accounts (create users, enable/disable, reset passwords) on the user-management page; browsers authenticate with an `HttpOnly` session cookie, and API clients can request a bearer token explicitly. Disabling login protection only skips API interception for local development. ## Bundled RocketMQ Cluster (Optional) The Quick Start above runs only Studio and its database. To try it against a ready-made RocketMQ, start the bundled demo cluster — nameserver, two brokers, proxy, a producer/consumer load generator, and Prometheus — on the same `rocketmq_net` network: ```bash docker compose -f deploy/rocketmq/docker-compose.yml up -d ``` Confirm it is healthy with `docker compose -f deploy/rocketmq/docker-compose.yml ps`. Studio reaches the cluster at `nameserver:9876` over the shared network (the backend default). **RocketMQ ports:** NameServer 9876, Broker 10911, Proxy Remoting 8080, Proxy gRPC 8081 ## Screenshots **Dashboard · AI chat** — a single entry point that switches between AI chat, cluster diagnosis, resource management, and message query, with model selection and MCP tool calls. ![Dashboard AI chat](docs/pics/home-ai-chat.png) **Consumer group management** — the group list shows subscription mode, online clients, total lag, and consumption delay; expanding a row reveals per-Topic subscription consistency and filter expressions, alongside offset reset and config import/export. ![Consumer group management](docs/pics/group-list.png) **Message query** — search messages by Topic / Message Key / Message ID within a time range, then inspect details, trace, verification, or download a single message. ![Message query](docs/pics/message-query.png) ## Features | Module | Capabilities | |--------|--------------| | **Dashboard** | Global statistics for clusters, brokers, topics, and consumer groups with TPS trends | | **Instances** | Multi-instance access (Proxy / Direct mode), instance CRUD | | **Clusters** | Cluster details, Broker / NameServer / Proxy node operations, hot config updates, NameServer configuration drift detection | | **K8s Certs** | Studio-local TLS / mTLS / ServiceAccount certificate configuration | | **Topics** | Topic CRUD, route viewer, consumer list, multi-type support (Normal / FIFO / Delay / Transaction / Lite) | | **Consumer Groups** | Consumer group CRUD, consumption progress, subscription details, offset reset, config import/export | | **ACL** | ACL rules and user management, v1 / v2 dual version support | | **Messages** | Query by Topic / MsgId / Key / time range, message trace visualization | | **Dead Letter Queue** | DLQ message viewing and batch resend | | **Clients** | Producer / Consumer online connection list, protocol and language version stats | | **Alert Rules** | Multi-dimensional alert rules (disk / lag / TPS / node offline), DingTalk / email / SMS notifications | | **System Alerts** | System-level alert viewing, acknowledgment, and cleanup | | **Audit Logs** | Operation audit log query, filter by type / time / result, history cleanup | | **AI Assistant** | Hosted-agent chat over SSE with server-side conversation history, visible chain of thought, and RocketMQ tool calls through the `rmqctl` MCP bridge; query / diagnose / manage / general modes | | **Settings** | General preferences, LLM config, datasource management | Topic and consumer-group CSV imports accept at most 100 nonblank data records. The parser stops when the first excess record completes, before reading the remaining CSV; blank rows and newlines inside quoted cells do not count as additional records. This record limit does not impose a file-byte or cell-size limit: the browser still reads the selected file before parsing it. ## AI Assistant Studio **hosts** a general-purpose agent CLI — Claude Code or Qoder, plus a plain OpenAI-compatible HTTP engine — rather than implementing its own tool-calling loop. RocketMQ capabilities reach the agent through [`rmqctl`](rmqctl/), the Go CLI in this repository, running as an MCP stdio server that calls back into Studio's own MCP endpoint. The same signed, instance-scoped, risk-gated tool surface therefore serves the hosted agent, a developer typing `rmqctl topic list`, and any external agent pointed at the output of `rmqctl mcp config`. See [docs/ai-agent-architecture.md](docs/ai-agent-architecture.md) for the design and its trade-offs. Standalone CLI commands support `--output table`, `json`, and `yaml`. Table cells show ASCII control characters as visible escapes (`\t`, `\n`, `\r`, or `\xNN`) so a context name, header, or returned value cannot split a row or send terminal control sequences. Stored values and JSON/YAML output keep the original content. - **Conversations persist server-side** and are browsable from the history drawer. Reloading or reconnecting replays exactly what the live stream rendered, because both paths reduce to the same block model. - **Chain of thought is displayed**, with model reasoning kept separate from the optional prompt-enhancement rewrite. - **Tool calls render as cards** showing arguments, output, duration and risk level. L2/L3 mutations go through preview → confirm token → apply; L3 tools stay disabled unless `STUDIO_AI_ALLOW_L3_TOOLS=true`. - **Multi-turn context** uses the agent CLI's own session resume, so tool state and reasoning survive across turns. - **One button sends and stops.** It is a send arrow while idle and a stop square while generating; stopping terminates the agent process *and* its `rmqctl` child rather than merely dropping the connection. - **Degrades to plain chat** when `rmqctl` is missing or `STUDIO_AI_RMQCTL_ENABLED=false`, and says so in the transcript instead of failing silently. Generation is decoupled from the HTTP connection: closing the tab does not kill a run, and reopening the conversation re-attaches to it. All AI-related environment variables are documented in [`deploy/.env.example`](deploy/.env.example). ## Tech Stack - **Frontend** — React 18 + TypeScript + Vite + Ant Design + Tailwind CSS - **Backend** — Java 21 + Spring Boot 4.1 + Spring AI MCP 2.0 + MyBatis-Plus + Hexagonal Architecture (ArchUnit enforced) - **CLI** — Go 1.27 ([`rmqctl`](rmqctl/)), both the MCP bridge the hosted agent uses and a standalone signed client for the same tool surface - **Deployment** — Docker multi-stage builds (JDK runtime plus a Go stage that compiles `rmqctl` into the image), Nginx reverse proxy, Docker Compose or `deploy.sh` for remote deployment ## Development Guidelines - **Branches** — `rocketmq-studio` is the development trunk: base your branches and pull requests on it. `master_archive` keeps the legacy dashboard history and is not used for development. See [CONTRIBUTING.md](CONTRIBUTING.md) for the full workflow - **Code Style** — ESLint + Prettier for frontend, Husky pre-commit hook for auto-check - **Commit Format** — Conventional Commits (`feat:` / `fix:` / `refactor:` / `chore:` / `docs:` / `perf:`) - **Architecture Tests** — `mvn test` runs ArchUnit hexagonal architecture constraint checks - **i18n** — New frontend text must include both Chinese and English translations (`web/src/i18n/`) - **Table Width** — Tables must not show a horizontal scrollbar by default (only allowed when the window/container is manually narrowed); use `tableScrollX(columns)` from `web/src/utils/table.ts` to compute `scroll.x` from declared column widths instead of hardcoded magic numbers; when a modal contains a wide table, adjust the modal `width` dynamically per active tab (e.g., Group detail: Overview 800 / Progress 1080) so that container width ≥ table width; long-text columns (e.g., long Topic names) should use `ellipsis: true` + `title` for hover-to-see-full-name truncation (no wrapping) - **Action Column Width** — Button-bearing action columns must be sized as "measured button row width + cell padding + right margin"; never shrink them by guesswork: `ant-flex` is a block-level container that stretches to fill the cell, so an undersized column pushes buttons against (or past) the table's right edge, causing flush edges or horizontal scrollbars; measure the actual button row width in DevTools before changing, and update the guarding test accordingly (e.g., `TopicPage.test.tsx` "keeps the action column wide enough") ## License [Apache License 2.0](LICENSE)

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deploy-rocketmq

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部署 RocketMQ Studio 与开源 RocketMQ。当用户说部署 studio、把 studio 部署到远程机器/测试机、更新远程 studio、单机部署开源 rocketmq、远程部署 rocketmq 集群、单机部署 rocketmq 测试客户端、部署 studio 测试集群、部署负载挂具、给 K8s 集群上消费负载、制造消费延迟 inflight 时触发。

2026-10-29

regression-rocketmq

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RocketMQ Studio 真实环境回归。当用户说回归 studio、跑 studio 全功能测试、验证死信/收发/轨迹、studio 发版前验证、regression-rocketmq 时触发。流程：环境体检 → 用 deploy-rocketmq 起或校验开源集群（本地有 k8s 证书则再用 deploy-rocketmq-k8s.sh 拉起/校验一套 k8s 开源集群）→ 清遗留资源 → 跑 e2e 套件 → 死信全链路 → 收发与轨迹抽查 → 出报告。

2026-10-29

已展示 2 / 2 个已收集 Skill。