eks-recon

name

eks-recon

description

EKS cluster reconnaissance and environment discovery. Detects compute strategy (Karpenter, MNG, Auto Mode, Fargate), IaC tooling (Terraform, CloudFormation, CDK, eksctl), CI/CD pipelines (GitHub Actions, GitLab, ArgoCD, Flux), add-on inventory, networking, security posture, and observability. Use this skill whenever someone asks about their EKS cluster, wants to understand their setup, is planning an upgrade or migration, needs cluster context for any reason, asks what version am I running, mentions wanting to review or document their cluster, or is about to make any EKS-related decision - even if they don't explicitly say reconnaissance or discovery. When in doubt about cluster state, run recon first. Skip for upgrade readiness scoring or deprecated API checks (eks-upgrade-check), operational audits with GREEN/AMBER/RED ratings (eks-operation-review), and architecture design documents or Mermaid diagrams (eks-design).

EKS Reconnaissance

Discover everything about an EKS cluster environment. Run this skill to gather comprehensive cluster context before making any decisions, changes, or recommendations.

When to Use This Skill

Run this skill when the user:

• Asks about their EKS cluster ("what's my cluster running?", "tell me about my setup")
• Plans an upgrade, migration, or architecture change
• Needs cluster context before any EKS-related decision
• Wants to document or review their cluster state
• Asks questions like "what version am I on?" or "am I using Karpenter?"
• Is about to modify their cluster (recon first to understand current state)

Also trigger this skill when:

• User mentions an EKS cluster name and seems to need context
• Another workflow needs cluster information as input
• You need to understand the cluster before giving recommendations

Do NOT use this skill for:

• Upgrade readiness scoring or deprecated API checks — questions like "score my upgrade readiness", "are there deprecated APIs blocking my upgrade", "can I safely upgrade to 1.33", "readiness score", or "breaking changes that would block a version bump" belong to eks-upgrade-check. Recon discovers what version you're on; it does NOT assess whether you're ready to move to the next version.
• Operational audits with maturity ratings — questions like "run an operational excellence audit", "rate each area GREEN/AMBER/RED", or "audit my cluster's operational posture" belong to eks-operation-review. Recon inventories what exists; it does NOT score operational maturity or produce rated assessments.
• Architecture design documents or Mermaid diagrams — questions like "create a security architecture document", "generate Mermaid diagrams for our EKS cluster", or "design document" belong to eks-design. Recon discovers current state; it does NOT produce design artifacts or architectural diagrams.
• Creating or modifying cluster resources (this is read-only)
• Troubleshooting specific issues (use eks-best-practices)
• Learning about EKS concepts (use eks-best-practices)

Prerequisites

MCP Server (Preferred)

This skill works best with the EKS MCP Server configured. Check if MCP tools are available:

If tools like `list_eks_resources`, `describe_eks_resource`, `list_k8s_resources` are available:
  -> MCP Mode: Use MCP tools (pre-authorized, richer output)
  
If MCP tools are NOT available:
  -> CLI Mode: Fall back to AWS CLI + kubectl (requires explicit permission)

MCP Mode benefits:

• Pre-authorized read-only operations (no permission prompts)
• Richer output with better formatting
• Single tool call instead of piped commands

CLI Mode limitations:

• Requires user permission for each command
• May need kubeconfig setup
• Some detection patterns are less reliable

Required for CLI Mode

Tool	Required For
aws CLI	Cluster-level detection (describe-cluster, list-nodegroups, list-addons)
kubectl	K8s resource detection (deployments, CRDs, service accounts)
helm	Helm release inventory (optional)

MCP Troubleshooting

401 Unauthorized on K8s API calls (list_k8s_resources, read_k8s_resource):

The MCP server can access EKS APIs (clusters, nodegroups, addons) but may lack Kubernetes API access. This happens when the MCP server's IAM role doesn't have an EKS access entry.

Solutions (choose one):

1. Grant MCP access: Create an EKS access entry for the MCP server's IAM role.

   Surface these commands to the user — do NOT execute them. These are persistent IAM writes and violate the read-only contract of this skill.

   aws eks create-access-entry \
     --cluster-name <cluster> \
     --region <region> \
     --principal-arn <mcp-server-role-arn> \
     --type STANDARD
   aws eks associate-access-policy \
     --cluster-name <cluster> \
     --region <region> \
     --principal-arn <mcp-server-role-arn> \
     --policy-arn arn:aws:eks::aws:cluster-access-policy/AmazonEKSViewPolicy \
     --access-scope type=cluster
   

   If the user confirms and has permission, they can run these themselves out-of-band.

2. Fall back to kubectl: If user has local kubectl access, use CLI commands instead:

   "MCP K8s access returned 401. I'll use kubectl instead if you have it configured locally."

Empty results from EKS API calls:

• Verify cluster name and region are correct
• Check if the cluster exists: aws eks list-clusters --region <region>

---

Reconnaissance Modes

Mode	When to Use	What Happens
Full Recon	First engagement with cluster	Runs all modules, generates complete report
Selective Recon	Know what you need	Run specific modules (e.g., compute + iac)
Targeted Query	Quick answer	"Is this cluster using Karpenter?"

How to Invoke

Full reconnaissance:

"Run EKS reconnaissance on cluster my-cluster in us-west-2"

Selective reconnaissance:

"Run EKS recon but only check compute and IaC"

Targeted query:

"What IaC tool manages cluster my-cluster?"

---

Modules and Reference Loading

Load only the references needed for the user's request — this keeps context focused. references/cluster-basics.md is always loaded first by every module; it provides the shared cluster context all other modules depend on. For targeted queries, load only the matching row(s); for full recon, load all references in parallel. When uncertain, ask the user or default to full recon.

Module	Intent / when to use	Reference file	Agent file
Cluster Basics	Always loaded first by every module (name, region, version, platform version, endpoint)	cluster-basics.md	—
Compute	Karpenter, nodes, scaling, Auto Mode, node groups, Fargate, self-managed	compute.md	compute-recon.md
Networking	VPC, ingress, CNI, service mesh, load balancer, connectivity	networking.md	networking-recon.md
Security	IAM, IRSA, Pod Identity, RBAC, policies, encryption, secrets, webhooks	security.md	security-recon.md
Add-ons	EKS-managed add-ons, Helm releases, plugins, "what's installed?"	addons.md	addons-recon.md
Observability	Logging, metrics, monitoring, Container Insights, Prometheus	observability.md	observability-recon.md
Workloads	Deployments, pods, services, ingresses, "what's running?"	workloads.md	workloads-recon.md
Storage	PVCs, EBS, EFS, StorageClasses, CSI drivers, volumes, snapshots	storage.md	storage-recon.md
IaC	Terraform, CloudFormation, CDK, eksctl, Pulumi, "how is it managed?"	iac.md	iac-recon.md
CI/CD	GitHub Actions, GitLab CI, Jenkins, ArgoCD, Flux, GitOps, pipelines	cicd.md	cicd-recon.md

---

Quick Detection Reference

MCP Commands (Preferred)

Detection	MCP Tool
Cluster info	describe_eks_resource(resource_type="cluster", cluster_name="<name>")
Node groups	list_eks_resources(resource_type="nodegroup", cluster_name="<name>")
EKS add-ons	list_eks_resources(resource_type="addon", cluster_name="<name>")
Karpenter	list_k8s_resources(cluster_name="<name>", kind="NodePool", api_version="karpenter.sh/v1")
Deployments	list_k8s_resources(cluster_name="<name>", kind="Deployment", api_version="apps/v1")
VPC config	get_eks_vpc_config(cluster_name="<name>")
Insights	get_eks_insights(cluster_name="<name>")

CLI Fallbacks

Detection	CLI Command
Cluster info	aws eks describe-cluster --name <name> --region <region>
Node groups	aws eks list-nodegroups --cluster-name <name> --region <region>
EKS add-ons	aws eks list-addons --cluster-name <name> --region <region>
Fargate profiles	aws eks list-fargate-profiles --cluster-name <name> --region <region>
Auto Mode	aws eks describe-cluster --name <name> --region <region> --query 'cluster.computeConfig'
Karpenter	kubectl get nodepools.karpenter.sh 2>/dev/null
Helm releases	helm list -A

---

Running Reconnaissance

IMPORTANT: Load Reference Files

Before running each module, you MUST read its reference file (e.g., references/compute.md). References contain:

• Detection order and rationale (why check Auto Mode before Karpenter)
• Edge cases and how to handle them
• CLI fallback commands when MCP fails
• Output schema for structured reporting

Skipping references produces shallow results. The main skill provides orchestration; the references provide detection intelligence.

Step 1: Gather Prerequisites

Required:
- Cluster name (or auto-discover — see below)
- AWS region (or detect from context/kubeconfig/CLI)

Optional:
- Specific modules to run (default: all)
- Output file path (default: .eks-recon-report.yaml)

Auto-discovery when cluster name is not explicit:

When the user says "my cluster", "current cluster", or does not name a specific cluster, discover it:

1. kubectl config current-context — if set, extract cluster name from the context ARN
2. If no kubeconfig context, try AWS CLI directly (credentials may come from ~/.aws/ config files, instance profile, or env vars — don't assume env vars are the only source):

   aws sts get-caller-identity  # verify we have working AWS access
   aws eks list-clusters --region ${AWS_DEFAULT_REGION:-us-west-2}
   

3. If exactly one cluster is found, use it. If multiple clusters across regions, try common regions (us-west-2, us-east-1, the region in any ARN visible in kubeconfig).
4. Only ask the user to specify a cluster if discovery yields multiple candidates and the prompt is ambiguous.

IMPORTANT: Never give up after checking only environment variables. AWS credentials can come from ~/.aws/credentials, ~/.aws/config, instance metadata, or ECS task roles — none of which appear in env | grep AWS_. Always try aws sts get-caller-identity before concluding credentials are unavailable.

Step 2: Check MCP Availability

If MCP tools are available, use them. Otherwise, inform the user:

"EKS MCP Server not detected. I'll use CLI commands instead, which will require your permission for each command. For a smoother experience, consider setting up the EKS MCP Server."

Step 3: Run Selected Modules

Determine which modules to run based on user intent (see Modules and Reference Loading).

For each selected module:

1. Load the reference file (e.g., references/compute.md) - REQUIRED
   • For targeted queries: load only the required reference(s) per decision matrix
   • For full recon: load all references in parallel
2. Run detection commands following the reference's guidance:
   • Try MCP tool first
   • If MCP returns error (401, empty), fall back to CLI from reference
   • If CLI unavailable, note the limitation in report
3. Collect output into report section using the reference's output schema

Step 4: Generate Report

Write report to .eks-recon-report.yaml and present summary:

# EKS Reconnaissance Report
# Generated: 2026-04-22T14:30:00Z
# Cluster: my-cluster
# Region: us-west-2
# Modules: cluster-basics, compute, iac, cicd, addons

cluster:
  name: my-cluster
  region: us-west-2
  version: "1.31"
  platform_version: eks.5
  endpoint: https://<cluster-id>.gr7.us-west-2.eks.amazonaws.com
  arn: arn:aws:eks:us-west-2:<account-id>:cluster/my-cluster
  status: ACTIVE
  created_at: "2024-09-10T12:00:00Z"

compute:
  strategy: Karpenter
  auto_mode:
    enabled: false
  karpenter:
    detected: true
    version: "1.0.5"
    nodepools: 2
    nodepool_names: [default, gpu]
  mng:
    detected: true
    count: 1
    groups:
      - name: system
        status: ACTIVE
        instance_types: [m6i.large]
        desired_size: 2
  fargate:
    detected: false
    profiles: 0
  self_managed:
    detected: false
    node_count: 0

iac:
  tool: Terraform
  confidence: high
  evidence:
    type: workspace_files
    details: "./infrastructure/eks/main.tf contains aws_eks_cluster"

cicd:
  workspace:
    github_actions:
      detected: true
      workflows: [.github/workflows/deploy.yml]
    gitlab_ci:
      detected: false
    jenkins:
      detected: false
      jenkinsfile: false
    other: null
  gitops:
    argocd:
      detected: true
      namespace: argocd
      applications: 12
      app_projects: 3
    flux:
      detected: false
      namespace: null
      kustomizations: 0
      helm_releases: 0
      git_repositories: 0

addons:
  eks_managed:
    count: 2
    list:
      - name: vpc-cni
        version: v1.18.1-eksbuild.1
        status: ACTIVE
        configuration: null
      - name: coredns
        version: v1.11.1-eksbuild.8
        status: ACTIVE
        configuration: null
  helm_releases:
    count: 1
    list:
      - name: karpenter
        namespace: kube-system
        chart: karpenter
        version: 1.0.5
        status: deployed

---

Subagent Mode

When running full reconnaissance, delegate each module to a specialized subagent. This keeps each module's context isolated and enables true parallel execution.

When to Use Subagents

Scenario	Mode	Reason
Any recon (1+ modules)	USE subagents	Isolated context, cleaner main conversation
No Agent tool available	Inline	Subagents not supported

IMPORTANT: If the Agent tool is available, you MUST use subagent mode for ALL reconnaissance — even single-module targeted queries. Subagents keep detection context isolated from the main conversation. Do not fall back to inline mode just because "it's only one module" or "MCP tools work" — always delegate to subagents.

Subagent Files

Each module has a corresponding subagent prompt in agents/:

Subagent	File	Purpose
Compute	agents/compute-recon.md	Detect compute strategy
Networking	agents/networking-recon.md	Detect network config
Security	agents/security-recon.md	Detect security posture, secrets, webhooks
Add-ons	agents/addons-recon.md	Detect installed components
Observability	agents/observability-recon.md	Detect monitoring/logging
Storage	agents/storage-recon.md	Detect CSI, StorageClasses, PVCs
Workloads	agents/workloads-recon.md	Detect running workloads
IaC	agents/iac-recon.md	Detect IaC tooling
CI/CD	agents/cicd-recon.md	Detect deployment pipelines

Orchestration Steps

Step 1: Check subagent availability

If Agent tool is available:
  → MUST use subagent mode for ALL recon (full or targeted)
  → Even single-module queries use subagents to isolate context
Else:
  → Use inline mode (load references directly)

Step 2: Spawn module subagents in parallel

Spawn ALL module subagents in a SINGLE message for parallel execution:

Agent(
  description: "EKS compute recon",
  prompt: "Recon compute for cluster {cluster_name} in {region}. 
           Read agents/compute-recon.md and references/compute.md.
           Return YAML output only.",
  subagent_type: "general-purpose"
)

Agent(
  description: "EKS networking recon",
  prompt: "Recon networking for cluster {cluster_name} in {region}.
           Read agents/networking-recon.md and references/networking.md.
           Return YAML output only.",
  subagent_type: "general-purpose"
)

... (spawn all 9 in parallel)

Step 3: Aggregate results

When all subagents complete:

1. Collect each subagent's YAML output
2. Merge into single report structure, applying these normalization rules:
   • Every subagent emits its own top-level cluster: block. Merge into a single top-level cluster: by deduplicating exact-match blocks (all subagents report the same cluster); if any field mismatches across subagents, flag it rather than silently picking one.
   • Module outputs are already in their canonical agent-defined shapes. Preserve them verbatim under the matching top-level key: compute:, iac:, cicd:, addons:, networking:, observability:, security:, storage:, workloads:. Do not reshape, flatten, or rename keys.
   • If a subagent fails to respond or errors out, set its key to unavailable: true with a short reason: string; do not omit the key.
3. Add cross-module insights (e.g., "Karpenter detected but no IRSA for controller")
4. Generate recommendations based on combined findings
5. Write final report to .eks-recon-report.yaml
6. Present summary to user

---

Integration with Other Workflows

Upgrade Workflow

The upgrade workflow can invoke eks-recon to gather Phase 1 context:

1. Run eks-recon modules: cluster-basics, compute, iac, addons
2. Extract:
   - cluster.version -> Current version
   - compute.strategy -> Determines upgrade approach
   - iac.tool -> Terraform vs CLI upgrade path
   - addons -> Compatibility matrix input

Design Workflow

The design workflow can use eks-recon for existing clusters:

1. Run eks-recon modules: all
2. Pre-populate questionnaire from detected values
3. Ask user: "I detected Karpenter + Terraform + ArgoCD. Correct?"
4. Only ask questions for undetected values