Files
kubeshark/README.md
Alon Girmonsky 1ba6ed94e0 💄 Improve README with AI skills, KFL semantics, and cloud storage (#1892)
* 💄 Improve README with AI skills, KFL semantics image, and cloud storage

- Add AI Skills section with Network RCA and KFL skills, Claude Code plugin install
- Rename "Network Traffic Indexing" to "Query with API, Kubernetes, and Network Semantics" with new KFL semantics image showing how a single query combines all three layers
- Add cloud storage providers (S3, Azure Blob, GCS) and decrypted TLS to Traffic Retention section
- Update Features table: add AI Skills, KFL query language, cloud storage, delayed indexing

* 🔒 Add encrypted traffic visibility to README "What you can do" section

* 🎨 Update snapshots image in README

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Co-authored-by: Alon Girmonsky <alongir@Alons-Mac-Studio.local>
2026-04-02 18:38:13 -07:00

6.9 KiB

Kubeshark

Release Docker pulls Discord Slack

Network Observability for SREs & AI Agents

Live Demo · Docs


Kubeshark indexes cluster-wide network traffic at the kernel level using eBPF — delivering instant answers to any query using network, API, and Kubernetes semantics.

What you can do:

  • 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.

Kubeshark


Get Started

helm repo add kubeshark https://helm.kubeshark.com
helm install kubeshark kubeshark/kubeshark
kubectl port-forward svc/kubeshark-front 8899:80

Open http://localhost:8899 in your browser. You're capturing traffic.

For production use, we recommend using an ingress controller instead of port-forward.

Connect an AI agent via MCP:

brew install kubeshark
claude mcp add kubeshark -- kubeshark mcp

MCP setup guide →


Network Data for AI Agents

Kubeshark exposes cluster-wide network data via MCP — enabling AI agents to query traffic, investigate API calls, and perform root cause analysis through natural language.

"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"

Works with Claude Code, Cursor, and any MCP-compatible AI.

MCP Demo

MCP setup guide →

AI Skills

Open-source, reusable skills that teach AI agents domain-specific workflows on top of Kubeshark's MCP tools:

Skill Description
Network RCA Retrospective root cause analysis — snapshots, dissection, PCAP extraction, trend comparison
KFL KFL (Kubeshark Filter Language) expert — writes, debugs, and optimizes traffic filters

Install as a Claude Code plugin:

/plugin marketplace add kubeshark/kubeshark
/plugin install kubeshark

Or clone and use directly — skills trigger automatically based on conversation context.

AI Skills docs →


Query with API, Kubernetes, and Network Semantics

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 can combine all three semantic layers — Kubernetes identity, API context, and network attributes — to pinpoint exactly the traffic you need. No code instrumentation required.

KFL query combining API, Kubernetes, and network semantics

KFL reference → · Traffic indexing →

Workload Dependency Map

A visual map of how workloads communicate, showing dependencies, traffic volume, and protocol usage across the cluster.

Service Map

Learn more →

Traffic Retention & PCAP Export

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.

Traffic Retention

Snapshots guide → · Cloud storage →


Features

Feature Description
Traffic Snapshots Point-in-time snapshots with cloud storage (S3, Azure Blob, GCS), PCAP export for Wireshark
Traffic Indexing Real-time and delayed L7 indexing with request/response matching and full payloads
Protocol Support HTTP, gRPC, GraphQL, Redis, Kafka, DNS, and more
TLS Decryption eBPF-based decryption without key management, included in snapshots
AI Integration MCP server + open-source AI skills for network RCA and traffic filtering
KFL Query Language CEL-based query language with Kubernetes, API, and network semantics
100% On-Premises Air-gapped support, no external dependencies

Install

Method Command
Helm helm repo add kubeshark https://helm.kubeshark.com && helm install kubeshark kubeshark/kubeshark
Homebrew brew install kubeshark && kubeshark tap
Binary Download

Installation guide →


Contributing

We welcome contributions. See CONTRIBUTING.md.

License

Apache-2.0