Volodymyr Stoiko 793e5d1efa 🔒 apply tap.auth.defaultRole when authentication is disabled
An ungated deployment had no authorization at all: every caller was
admin, and the only way to restrict anyone was to stand up an identity
provider. So a read-only dashboard needed a login it had no use for.

defaultRole now answers 'what may an unidentified caller do' as well as
'what may an authenticated caller with no recognized group do'. Setting
it to kubeshark-viewer gives a read-only deployment with no login and no
auth backend.

Its default becomes kubeshark-admin, so an ungated install behaves as it
always has, and the hub falls back to admin when the value is unset or
unrecognized rather than to strict-deny — nobody configuring a role must
not brick an install.

Adds install-notes coverage, since the notes are where an operator
learns which of the two ungated postures they got, and fills the
remaining gaps in the auth suites: dex and descope validation, incomplete
settings while auth is off, and worker token projection under licensing
and demo mode.
2026-08-17 07:38:14 +00:00
2026-05-19 02:00:17 -07:00
2022-11-30 04:50:12 +03:00
2025-03-01 22:23:24 +02:00

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

S
Description
The API traffic analyzer for Kubernetes providing real-time K8s protocol-level visibility, capturing and monitoring all traffic and payloads going in, out and across containers, pods, nodes and clusters.. Think TCPDump and Wireshark re-invented for Kubernetes
Readme
168 MiB
Languages
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Makefile 5.1%
Go Template 1.6%
Shell 1.3%