-Network Observability for SREs & AI Agents
+面向 SRE 与 AI Agent 的网络可观测性
--- -Kubeshark indexes cluster-wide network traffic at the kernel level using eBPF — delivering instant answers to any query using network, API, and Kubernetes semantics. +Kubeshark 使用 eBPF 在内核层面对集群范围内的网络流量进行索引 — 借助网络、API 与 Kubernetes 语义，为任意查询提供即时答案。 -**What you can do:** +**你可以做什么：** -- **Download Retrospective PCAPs** — cluster-wide packet captures filtered by nodes, time, workloads, and IPs. Store PCAPs for long-term retention and later investigation. -- **Visualize Network Data** — explore traffic matching queries with API, Kubernetes, or network semantics through a real-time dashboard. -- **See Encrypted Traffic in Plain Text** — automatically decrypt TLS/mTLS traffic using eBPF, with no key management or sidecars required. -- **Integrate with AI** — connect your favorite AI assistant (e.g. Claude, Copilot) to include network data in AI-driven workflows like incident response and root cause analysis. +- **下载回顾性 PCAP** — 按节点、时间、工作负载和 IP 筛选的集群范围数据包捕获。可长期保留 PCAP，供后续调查使用。 +- **可视化网络数据** — 通过实时仪表板，以 API、Kubernetes 或网络语义探索符合查询的流量。 +- **以明文查看加密流量** — 使用 eBPF 自动解密 TLS/mTLS 流量，无需密钥管理或 sidecar。 +- **与 AI 集成** — 将你偏好的 AI 助手（如 Claude、Copilot）接入，将网络数据纳入事件响应与根因分析（Root Cause Analysis, RCA）等 AI 驱动的工作流。  --- -## Get Started +## 快速开始 ```bash helm repo add kubeshark https://helm.kubeshark.com @@ -38,114 +44,114 @@ helm install kubeshark kubeshark/kubeshark kubectl port-forward svc/kubeshark-front 8899:80 ``` -Open `http://localhost:8899` in your browser. You're capturing traffic. +在浏览器中打开 `http://localhost:8899`。你已开始捕获流量。 -> For production use, we recommend using an [ingress controller](https://docs.kubeshark.com/en/ingress) instead of port-forward. +> 生产环境建议通过 [ingress controller](https://docs.kubeshark.com/en/ingress) 替代 port-forward。 -**Connect an AI agent** via MCP: +**通过 MCP 连接 AI agent**： ```bash brew install kubeshark claude mcp add kubeshark -- kubeshark mcp ``` -[MCP setup guide →](https://docs.kubeshark.com/en/mcp) +[MCP 配置指南 →](https://docs.kubeshark.com/en/mcp) --- -### Network Data for AI Agents +### 面向 AI Agent 的网络数据 -Kubeshark exposes cluster-wide network data via [MCP](https://docs.kubeshark.com/en/mcp) — enabling AI agents to query traffic, investigate API calls, and perform root cause analysis through natural language. +Kubeshark 通过 [MCP](https://docs.kubeshark.com/en/mcp) 暴露集群范围内的网络数据 — 使 AI agent 能够以自然语言查询流量、调查 API 调用并执行根因分析。 -> *"Why did checkout fail at 2:15 PM?"* -> *"Which services have error rates above 1%?"* -> *"Show TCP retransmission rates across all node-to-node paths"* -> *"Trace request abc123 through all services"* +> *"为什么 checkout 在下午 2:15 失败了？"* +> *"哪些服务的错误率超过 1%？"* +> *"显示所有节点间路径的 TCP 重传率"* +> *"追踪请求 abc123 在所有服务中的流转"* -Works with Claude Code, Cursor, and any MCP-compatible AI. +可与 Claude Code、Cursor 及任何兼容 MCP 的 AI 配合使用。  -[MCP setup guide →](https://docs.kubeshark.com/en/mcp) +[MCP 配置指南 →](https://docs.kubeshark.com/en/mcp) -### AI Skills +### AI 技能 -Open-source, reusable skills that teach AI agents domain-specific workflows on top of Kubeshark's MCP tools: +开源、可复用的技能，用于在 Kubeshark 的 MCP 工具之上，教会 AI agent 领域特定的工作流： -| Skill | Description | +| 技能 | 描述 | |-------|-------------| -| **[Network RCA](skills/network-rca/)** | Retrospective root cause analysis — snapshots, dissection, PCAP extraction, trend comparison | -| **[KFL](skills/kfl/)** | KFL (Kubeshark Filter Language) expert — writes, debugs, and optimizes traffic filters | +| **[Network RCA](skills/network-rca/)** | 回顾性根因分析 — 快照、解析、PCAP 提取、趋势对比 | +| **[KFL](skills/kfl/)** | KFL（Kubeshark Filter Language）专家 — 编写、调试并优化流量过滤器 | -Install as a Claude Code plugin: +作为 Claude Code 插件安装： ``` /plugin marketplace add kubeshark/kubeshark /plugin install kubeshark ``` -Or clone and use directly — skills trigger automatically based on conversation context. +或直接克隆使用 — 技能会根据对话上下文自动触发。 -[AI Skills docs →](https://docs.kubeshark.com/en/mcp/skills) +[AI 技能文档 →](https://docs.kubeshark.com/en/mcp/skills) --- -### Query with API, Kubernetes, and Network Semantics +### 使用 API、Kubernetes 与网络语义进行查询 -Kubeshark indexes cluster-wide network traffic by parsing it according to protocol specifications, with support for HTTP, gRPC, Redis, Kafka, DNS, and more. A single [KFL query](https://docs.kubeshark.com/en/v2/kfl2) can combine all three semantic layers — Kubernetes identity, API context, and network attributes — to pinpoint exactly the traffic you need. No code instrumentation required. +Kubeshark 依据协议规范解析流量，对集群范围内的网络流量进行索引，支持 HTTP、gRPC、Redis、Kafka、DNS 等。单个 [KFL 查询](https://docs.kubeshark.com/en/v2/kfl2) 可组合全部三层语义 — Kubernetes 身份、API 上下文与网络属性 — 精确定位所需流量。无需代码插桩。  -[KFL reference →](https://docs.kubeshark.com/en/v2/kfl2) · [Traffic indexing →](https://docs.kubeshark.com/en/v2/l7_api_dissection) +[KFL 参考 →](https://docs.kubeshark.com/en/v2/kfl2) · [流量索引 →](https://docs.kubeshark.com/en/v2/l7_api_dissection) -### Workload Dependency Map +### 工作负载依赖图 -A visual map of how workloads communicate, showing dependencies, traffic volume, and protocol usage across the cluster. +可视化展示工作负载之间的通信方式，呈现集群内的依赖关系、流量规模与协议使用情况。  -[Learn more →](https://docs.kubeshark.com/en/v2/service_map) +[了解更多 →](https://docs.kubeshark.com/en/v2/service_map) -### Traffic Retention & PCAP Export +### 流量保留与 PCAP 导出 -Capture and retain raw network traffic cluster-wide, including decrypted TLS. Download PCAPs scoped by time range, nodes, workloads, and IPs — ready for Wireshark or any PCAP-compatible tool. Store snapshots in cloud storage (S3, Azure Blob, GCS) for long-term retention and cross-cluster sharing. +在集群范围内捕获并保留原始网络流量，包括已解密的 TLS。可按时间范围、节点、工作负载和 IP 下载 PCAP — 可直接用于 Wireshark 或任何兼容 PCAP 的工具。将快照存储到云存储（S3、Azure Blob、GCS）以实现长期保留与跨集群共享。  -[Snapshots guide →](https://docs.kubeshark.com/en/v2/traffic_snapshots) · [Cloud storage →](https://docs.kubeshark.com/en/snapshots_cloud_storage) +[快照指南 →](https://docs.kubeshark.com/en/v2/traffic_snapshots) · [云存储 →](https://docs.kubeshark.com/en/snapshots_cloud_storage) --- -## Features +## 功能特性 -| Feature | Description | +| 功能 | 描述 | |---------|-------------| -| [**Traffic Snapshots**](https://docs.kubeshark.com/en/v2/traffic_snapshots) | Point-in-time snapshots with cloud storage (S3, Azure Blob, GCS), PCAP export for Wireshark | -| [**Traffic Indexing**](https://docs.kubeshark.com/en/v2/l7_api_dissection) | Real-time and delayed L7 indexing with request/response matching and full payloads | -| [**Protocol Support**](https://docs.kubeshark.com/en/protocols) | HTTP, gRPC, GraphQL, Redis, Kafka, DNS, and more | -| [**TLS Decryption**](https://docs.kubeshark.com/en/encrypted_traffic) | eBPF-based decryption without key management, included in snapshots | -| [**AI Integration**](https://docs.kubeshark.com/en/mcp) | MCP server + open-source AI skills for network RCA and traffic filtering | -| [**KFL Query Language**](https://docs.kubeshark.com/en/v2/kfl2) | CEL-based query language with Kubernetes, API, and network semantics | -| [**100% On-Premises**](https://docs.kubeshark.com/en/air_gapped) | Air-gapped support, no external dependencies | +| [**流量快照**](https://docs.kubeshark.com/en/v2/traffic_snapshots) | 时间点快照，支持云存储（S3、Azure Blob、GCS），可导出 PCAP 供 Wireshark 使用 | +| [**流量索引**](https://docs.kubeshark.com/en/v2/l7_api_dissection) | 实时与延迟 L7 索引，支持请求/响应匹配与完整载荷 | +| [**协议支持**](https://docs.kubeshark.com/en/protocols) | HTTP、gRPC、GraphQL、Redis、Kafka、DNS 等 | +| [**TLS 解密**](https://docs.kubeshark.com/en/encrypted_traffic) | 基于 eBPF 的解密，无需密钥管理，包含在快照中 | +| [**AI 集成**](https://docs.kubeshark.com/en/mcp) | MCP 服务器 + 开源 AI 技能，用于网络 RCA 与流量过滤 | +| [**KFL 查询语言**](https://docs.kubeshark.com/en/v2/kfl2) | 基于 CEL 的查询语言，支持 Kubernetes、API 与网络语义 | +| [**100% 本地部署**](https://docs.kubeshark.com/en/air_gapped) | 支持气隙（air-gapped）环境，无外部依赖 | --- -## Install +## 安装 -| Method | Command | +| 方式 | 命令 | |--------|---------| | Helm | `helm repo add kubeshark https://helm.kubeshark.com && helm install kubeshark kubeshark/kubeshark` | | Homebrew | `brew install kubeshark && kubeshark tap` | -| Binary | [Download](https://github.com/kubeshark/kubeshark/releases/latest) | +| Binary | [下载](https://github.com/kubeshark/kubeshark/releases/latest) | -[Installation guide →](https://docs.kubeshark.com/en/install) +[安装指南 →](https://docs.kubeshark.com/en/install) --- -## Contributing +## 贡献 -We welcome contributions. See [CONTRIBUTING.md](CONTRIBUTING.md). +欢迎贡献。请参阅 [CONTRIBUTING.md](CONTRIBUTING.md)。 -## License +## 许可证 [Apache-2.0](LICENSE)