Conflicts were in the helm chart's auth config, where master's permissions
refactor (fcceed23) reordered the AUTH_* config-map keys and replaced the
inline tap.auth.roles tree with roles/rolesClaim/defaultRole/groupMapping —
directly alongside gated-auth's new CLI ServiceAccount-token auth. Neither
side removed the other's work, so both are kept.
Also promote tap.auth.cli to a real config field. It had been hand-written
into helm-chart/values.yaml, which is generated by `make generate-helm-values`
(bin/kubeshark__ config > helm-chart/values.yaml). The next regeneration would
have silently dropped the key, leaving 22-cli-auth.yaml unable to render the
ServiceAccount. Add CliAuthConfig/CliAuthSubject to AuthConfig and regenerate
values.yaml from source, so the block now round-trips.
Subject fields carry omitempty so User/Group entries don't emit an empty
namespace and ServiceAccount entries don't emit an empty apiGroup, keeping
the rendered RoleBinding idiomatic.
values.yaml is generated and cannot hold comments, so the tap.auth.cli docs
live in helm-chart/README.md alongside the other tap.auth.* rows. Drop the
internal plan phase labels from the CLI and utils comments; phases exist only
in local planning docs.
Network Observability for SREs & AI Agents
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.
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
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.
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.
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 reference → · Traffic indexing →
Workload Dependency Map
A visual map of how workloads communicate, showing dependencies, traffic volume, and protocol usage across the cluster.
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.
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 |
Contributing
We welcome contributions. See CONTRIBUTING.md.




