docs: make Chinese README the default
This commit is contained in:
wehub-resource-sync
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<!-- WEHUB_ZH_README -->
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> [!NOTE]
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> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。
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> [English](./README.en.md) · [原始项目](https://github.com/kubeshark/kubeshark) · [上游 README](https://github.com/kubeshark/kubeshark/blob/HEAD/README.md)
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> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
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<p align="center">
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<img src="https://raw.githubusercontent.com/kubeshark/assets/master/svg/kubeshark-logo.svg" alt="Kubeshark" height="120px"/>
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</p>
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@@ -9,28 +15,28 @@
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<a href="https://join.slack.com/t/kubeshark/shared_invite/zt-3jdcdgxdv-1qNkhBh9c6CFoE7bSPkpBQ"><img alt="Slack" src="https://img.shields.io/badge/slack-join_chat-green?logo=Slack&style=flat-square"></a>
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</p>
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<p align="center"><b>Network Observability for SREs & AI Agents</b></p>
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<p align="center"><b>面向 SRE 与 AI Agent 的网络可观测性</b></p>
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<p align="center">
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<a href="https://demo.kubeshark.com/">Live Demo</a> · <a href="https://docs.kubeshark.com">Docs</a>
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<a href="https://demo.kubeshark.com/">在线演示</a> · <a href="https://docs.kubeshark.com">文档</a>
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</p>
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---
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Kubeshark indexes cluster-wide network traffic at the kernel level using eBPF — delivering instant answers to any query using network, API, and Kubernetes semantics.
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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。
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**What you can do:**
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**你可以做什么：**
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- **Download Retrospective PCAPs** — cluster-wide packet captures filtered by nodes, time, workloads, and IPs. Store PCAPs for long-term retention and later investigation.
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- **Visualize Network Data** — explore traffic matching queries with API, Kubernetes, or network semantics through a real-time dashboard.
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- **See Encrypted Traffic in Plain Text** — automatically decrypt TLS/mTLS traffic using eBPF, with no key management or sidecars required.
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- **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.
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- **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。
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- **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。
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- **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。
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- **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。
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---
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## Get Started
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## 快速开始
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```bash
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helm repo add kubeshark https://helm.kubeshark.com
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@@ -38,114 +44,114 @@ helm install kubeshark kubeshark/kubeshark
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kubectl port-forward svc/kubeshark-front 8899:80
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```
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Open `http://localhost:8899` in your browser. You're capturing traffic.
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在浏览器中打开 `http://localhost:8899`。你已开始捕获流量。
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> For production use, we recommend using an [ingress controller](https://docs.kubeshark.com/en/ingress) instead of port-forward.
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> 生产环境建议通过 [ingress controller](https://docs.kubeshark.com/en/ingress) 替代 port-forward。
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**Connect an AI agent** via MCP:
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**通过 MCP 连接 AI agent**：
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```bash
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brew install kubeshark
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claude mcp add kubeshark -- kubeshark mcp
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```
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[MCP setup guide →](https://docs.kubeshark.com/en/mcp)
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[MCP 配置指南 →](https://docs.kubeshark.com/en/mcp)
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---
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### Network Data for AI Agents
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### 面向 AI Agent 的网络数据
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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.
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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。
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> *"Why did checkout fail at 2:15 PM?"*
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> *"Which services have error rates above 1%?"*
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> *"Show TCP retransmission rates across all node-to-node paths"*
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> *"Trace request abc123 through all services"*
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> *"为什么 checkout 在下午 2:15 失败了？"*
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> *"哪些服务的错误率超过 1%？"*
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> *"显示所有节点间路径的 TCP 重传率"*
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> *"追踪请求 abc123 在所有服务中的流转"*
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Works with Claude Code, Cursor, and any MCP-compatible AI.
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可与 Claude Code、Cursor 及任何兼容 MCP 的 AI 配合使用。
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[MCP setup guide →](https://docs.kubeshark.com/en/mcp)
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[MCP 配置指南 →](https://docs.kubeshark.com/en/mcp)
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### AI Skills
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### AI 技能
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Open-source, reusable skills that teach AI agents domain-specific workflows on top of Kubeshark's MCP tools:
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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：
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| Skill | Description |
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| 技能 | 描述 |
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|-------|-------------|
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| **[Network RCA](skills/network-rca/)** | Retrospective root cause analysis — snapshots, dissection, PCAP extraction, trend comparison |
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| **[KFL](skills/kfl/)** | KFL (Kubeshark Filter Language) expert — writes, debugs, and optimizes traffic filters |
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| **[Network RCA](skills/network-rca/)** | 回顾性根因分析 — 快照、解析、PCAP 提取、趋势对比 |
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| **[KFL](skills/kfl/)** | KFL（Kubeshark Filter Language）专家 — 编写、调试并优化流量过滤器 |
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Install as a Claude Code plugin:
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作为 Claude Code 插件安装：
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```
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/plugin marketplace add kubeshark/kubeshark
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/plugin install kubeshark
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```
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Or clone and use directly — skills trigger automatically based on conversation context.
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或直接克隆使用 — 技能会根据对话上下文自动触发。
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[AI Skills docs →](https://docs.kubeshark.com/en/mcp/skills)
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[AI 技能文档 →](https://docs.kubeshark.com/en/mcp/skills)
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---
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### Query with API, Kubernetes, and Network Semantics
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### 使用 API、Kubernetes 与网络语义进行查询
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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.
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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。
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[KFL reference →](https://docs.kubeshark.com/en/v2/kfl2) · [Traffic indexing →](https://docs.kubeshark.com/en/v2/l7_api_dissection)
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[KFL 参考 →](https://docs.kubeshark.com/en/v2/kfl2) · [流量索引 →](https://docs.kubeshark.com/en/v2/l7_api_dissection)
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### Workload Dependency Map
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### 工作负载依赖图
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A visual map of how workloads communicate, showing dependencies, traffic volume, and protocol usage across the cluster.
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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。
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[Learn more →](https://docs.kubeshark.com/en/v2/service_map)
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[了解更多 →](https://docs.kubeshark.com/en/v2/service_map)
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### Traffic Retention & PCAP Export
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### 流量保留与 PCAP 导出
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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.
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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。
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[Snapshots guide →](https://docs.kubeshark.com/en/v2/traffic_snapshots) · [Cloud storage →](https://docs.kubeshark.com/en/snapshots_cloud_storage)
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[快照指南 →](https://docs.kubeshark.com/en/v2/traffic_snapshots) · [云存储 →](https://docs.kubeshark.com/en/snapshots_cloud_storage)
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---
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## Features
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## 功能特性
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| Feature | Description |
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| 功能 | 描述 |
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|---------|-------------|
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| [**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 |
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| [**Traffic Indexing**](https://docs.kubeshark.com/en/v2/l7_api_dissection) | Real-time and delayed L7 indexing with request/response matching and full payloads |
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| [**Protocol Support**](https://docs.kubeshark.com/en/protocols) | HTTP, gRPC, GraphQL, Redis, Kafka, DNS, and more |
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| [**TLS Decryption**](https://docs.kubeshark.com/en/encrypted_traffic) | eBPF-based decryption without key management, included in snapshots |
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| [**AI Integration**](https://docs.kubeshark.com/en/mcp) | MCP server + open-source AI skills for network RCA and traffic filtering |
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| [**KFL Query Language**](https://docs.kubeshark.com/en/v2/kfl2) | CEL-based query language with Kubernetes, API, and network semantics |
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| [**100% On-Premises**](https://docs.kubeshark.com/en/air_gapped) | Air-gapped support, no external dependencies |
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| [**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 |
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| [**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 |
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| [**协议支持**](https://docs.kubeshark.com/en/protocols) | HTTP、gRPC、GraphQL、Redis、Kafka、DNS 等 |
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| [**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 |
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| [**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 |
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| [**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 |
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| [**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 |
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---
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## Install
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## 安装
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| Method | Command |
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| 方式 | 命令 |
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|--------|---------|
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| Helm | `helm repo add kubeshark https://helm.kubeshark.com && helm install kubeshark kubeshark/kubeshark` |
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| Homebrew | `brew install kubeshark && kubeshark tap` |
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| Binary | [Download](https://github.com/kubeshark/kubeshark/releases/latest) |
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| Binary | [下载](https://github.com/kubeshark/kubeshark/releases/latest) |
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[Installation guide →](https://docs.kubeshark.com/en/install)
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[安装指南 →](https://docs.kubeshark.com/en/install)
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---
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## Contributing
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## 贡献
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We welcome contributions. See [CONTRIBUTING.md](CONTRIBUTING.md).
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欢迎贡献。请参阅 [CONTRIBUTING.md](CONTRIBUTING.md)。
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## License
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## 许可证
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[Apache-2.0](LICENSE)
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