Eks Upgrade Readiness logo

Eks Upgrade Readiness

Organization
aws
eks-upgrade-readiness

Use this skill when a user asks to assess, plan, or validate an Amazon EKS cluster upgrade. Activate on requests mentioning "EKS upgrade", "Kubernetes version upgrade", "upgrade readiness", "upgrade plan", "pre-upgrade check", "version skew", "deprecated API", "addon compatibility", "node group upgrade", "control plane upgrade", "EKS end of support", "EKS extended support", "Karpenter drift", "kubelet version skew", or "blue-green cluster migration". It runs a pre-upgrade assessment per the AWS EKS Best Practices Guide, covering infrastructure prerequisites, EKS Upgrade Insights, API deprecations, addon compatibility, full data plane inventory (managed/self-managed nodes, Karpenter, Auto Mode, Fargate), AL2 to AL2023 migration, PDB/topology and StatefulSet safety, capacity planning, and pre/post-upgrade validation, then produces a scored readiness verdict with prioritized remediation. Do NOT use for ECS, general EKS troubleshooting unrelated to version upgrades, or EKS Anywhere/Outpost clusters.

Overview

Publisheraws
Repositorytools-for-devops-agent
Skill nameeks-upgrade-readiness
Stars
120
Forks
97
Bundled files
14
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 14 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by aws on GitHub. Read the source before you install it.

Installation

Install the Eks Upgrade Readiness AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/aws/tools-for-devops-agent/tree/main/skills/eks-upgrade-readiness
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/aws/tools-for-devops-agent.git /tmp/tools-for-devops-agent
mkdir -p .claude/skills
cp -r /tmp/tools-for-devops-agent/skills/eks-upgrade-readiness .claude/skills/eks-upgrade-readiness
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Eks Upgrade Readiness in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Eks Upgrade Readiness on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Eks Upgrade Readiness is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

EKS Upgrade Readiness

Assess and plan Amazon EKS cluster upgrades with comprehensive pre-upgrade validation aligned with the EKS Best Practices Guide.

When to Use

Activate this skill when the user asks to:

  • Check if an EKS cluster is ready to upgrade
  • Plan an EKS version upgrade (control plane, node groups, or both)
  • Identify deprecated Kubernetes APIs before upgrading
  • Validate addon compatibility with a target version
  • Assess node group upgrade strategy and capacity requirements
  • Review Pod Disruption Budgets or topology spread for upgrade safety
  • Understand EKS end-of-support, extended support, or auto-upgrade implications
  • Evaluate Karpenter Drift or node expiry upgrade behavior
  • Compare in-place vs blue-green upgrade strategies
  • Create an upgrade runbook or checklist
  • Detect GitOps/IaC version ownership before upgrading

Safety First

Before doing anything, load references/safety-invariants.md. It defines the knowledge hierarchy, hard rules, operation classification, and uncertainty handling. Keep it in context for the entire assessment.

Critical Warnings

  • This skill is read-only. All commands are describe*, list*, get*. The agent does NOT execute mutating APIs. Mutations are in Step 14 and require explicit operator approval.
  • One minor version at a time. EKS control plane upgrades proceed one minor version per operation (e.g., 1.30 → 1.31).
  • Version skew policy. Before planning an upgrade, no kubelet may be newer than the current control plane. For the target version, kubelet may be no more than N-3 on 1.28+ (N-2 below 1.28).
  • Addons must be upgraded AFTER the control plane (exceptions in Step 8).
  • Auto-upgrade policy. Clusters past the 26-month lifecycle will be auto-upgraded. Proactive upgrade avoids disruption.
  • Control plane rollback (July 2026+). 7-day rollback window after upgrade. Conditional, not guaranteed — skill checks eligibility.
  • UNKNOWN ≠ PASS. Any gate that cannot be assessed MUST be UNKNOWN, never PASS. Overall verdict cannot be READY while any gate is UNKNOWN.

Evidence Completeness

Uses references/required-check-registry.yaml to track checks performed, skipped, or blocked. EC = checks_performed / total_applicable × 100%. EC < 50% produces a mandatory warning.

Grading and Confidence

LevelMeaningWhen to Use
HIGH (90%+)Confirmed from authoritative sourceEKS Insights API, direct kubectl query, AWS API response
MEDIUM (60-89%)Inferred from available dataPartial kubectl access, version matching heuristics
LOW (30-59%)Limited data, possible gapsNo kubectl, no logging enabled, partial API access
UNKNOWNCannot determineTool unavailable, no data, access denied

False-positive guards:

  • Empty query result ≠ PASS (mark UNKNOWN)
  • No kubectl ≠ N/A for everything (AWS APIs still work)
  • EKS Insights PASSING ≠ skip other checks (covers a subset only)
  • Addon "compatible" ≠ "recommended"
  • Pagination not exhausted → confidence LOW

Verdict rules (evaluate applicable gates only; N/A gates are excluded):

  1. NOT READY: one or more applicable gates are FAIL. A known blocker wins over uncertainty because proceeding is unsafe.
  2. CANNOT DETERMINE: no gate is FAIL, but one or more applicable gates are UNKNOWN (including inaccessible, incomplete, stale, or unpaginated data).
  3. READY WITH WARNINGS: all applicable gates are assessed, none FAIL or UNKNOWN, and one or more are WARN.
  4. READY: every applicable gate is PASS.

Format: [PASS|FAIL|WARN|UNKNOWN|N/A] (confidence: HIGH) — <evidence>

Cost Awareness

  • EKS Insights API (Step 3) is free — always use first.
  • CloudWatch Logs Insights cost ~$0.0076/GB scanned. Default to 60-min windows.
  • Extended support costs $0.60/cluster/hour — upgrading saves money.
  • Surge nodes incur temporary EC2 cost during overlap period.

Required Permissions

AWS IAM — see README.md "Prerequisites → IAM Permissions" for the full read-only action list (eks:Describe*, eks:List*, ec2:Describe*, autoscaling:Describe*, iam:GetRole, servicequotas:GetServiceQuota).

Kubernetes RBAC (only if kubectl access is available — the assessment still runs on AWS APIs alone without it, at lower confidence for CRD/Helm/PDB checks). Read-only ClusterRole covering every kubectl get/describe used in this skill:

yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: eks-upgrade-readiness-readonly
rules:
  - apiGroups: [""]
    resources:
      - nodes
      - pods
      - configmaps
      - secrets
      - events
      - persistentvolumeclaims
      - certificatesigningrequests
    verbs: ["get", "list", "watch"]
  - apiGroups: ["apps"]
    resources: ["deployments", "statefulsets", "daemonsets", "replicasets"]
    verbs: ["get", "list", "watch"]
  - apiGroups: ["policy"]
    resources: ["poddisruptionbudgets"]
    verbs: ["get", "list", "watch"]
  - apiGroups: ["apiextensions.k8s.io"]
    resources: ["customresourcedefinitions"]
    verbs: ["get", "list", "watch"]
  - apiGroups: ["admissionregistration.k8s.io"]
    resources:
      - validatingwebhookconfigurations
      - mutatingwebhookconfigurations
    verbs: ["get", "list", "watch"]
  - apiGroups: ["karpenter.sh"]
    resources: ["nodepools", "nodeclaims"]
    verbs: ["get", "list", "watch"]
  - apiGroups: ["karpenter.k8s.aws"]
    resources: ["ec2nodeclasses"]
    verbs: ["get", "list", "watch"]
  - apiGroups: ["crd.k8s.amazonaws.com"]
    resources: ["eniconfigs"]
    verbs: ["get", "list", "watch"]
  - apiGroups: ["storage.k8s.io"]
    resources: ["storageclasses", "csinodes"]
    verbs: ["get", "list", "watch"]

Bind with a ClusterRoleBinding to the identity the agent assumes (e.g. via IRSA/Pod Identity or an EKS access entry). secrets read access is required only for the Helm stored-manifest scan (Step 4) — omit that rule and accept UNKNOWN on Helm checks if a customer's security policy disallows it.


Step 1: Gather Cluster Context

bash
aws eks describe-cluster --name <cluster-name> --region <region>

Extract: cluster.version, platformVersion, status (must be ACTIVE), kubernetesNetworkConfig, logging.clusterLogging (audit log must be enabled), resourcesVpcConfig.subnetIds, tags (IaC ownership detection).

Determine target version: ask user or default to current + 1 minor. Confirm target is in standard support via the EKS release calendar.

Step 2: Verify Infrastructure Prerequisites

Check these — failures are BLOCKERs:

  1. Subnet IP availability — need ≥5 IPs per cluster subnet. Mode-aware: standard IPv4, prefix delegation, custom networking, IPv6, SGP. Use aws ec2 describe-subnets with cluster subnet IDs.
  2. EKS IAM role — verify role exists with eks.amazonaws.com trust.
  3. KMS key (if encryption enabled) — verify cluster role has key access.
  4. Service quota headroom — EC2 vCPU (L-1216C47A) and EBS gp3 (L-7A658000) must have room for surge nodes. Use aws service-quotas get-service-quota.

VPC CNI mode and capacity-input detection:

bash
kubectl get ds aws-node -n kube-system -o json | jq '
  .spec.template.spec.containers[0].env[]
  | select(.name | test("ENABLE_PREFIX_DELEGATION|AWS_VPC_K8S_CNI_CUSTOM_NETWORK_CFG|ENABLE_POD_ENI|WARM_IP_TARGET|MINIMUM_IP_TARGET|WARM_ENI_TARGET|WARM_PREFIX_TARGET"))
  | {name, value}'

VPC CNI Surge-Capacity Gate

Do not treat "mode detected" as capacity validated. First calculate the managed-node-group surge using references/capacity-planning.md, distribute it by the node group's AZ placement, then verify the relevant subnet/ENI resource for the selected mode. Record the inputs and calculations as evidence; a missing mode-specific input is UNKNOWN, not PASS.

ModeRequired assessment before a node surgePass condition
Standard IPv4Inspect WARM_IP_TARGET, MINIMUM_IP_TARGET, and WARM_ENI_TARGET on aws-node; use node status.allocatable.pods and current pod count to calculate the additional secondary-IP demand for every surge node.Every node subnet has enough free IPv4 addresses for its share of surge nodes, their primary ENIs, and configured warm/allocatable pod-IP demand.
Prefix delegationConfirm ENABLE_PREFIX_DELEGATION=true; each IPv4 prefix consumes a /28 (16 addresses). Calculate required additional prefixes as ceil(additional_pod_ips / 16) per affected subnet/AZ.floor(availableIpAddressCount / 16) covers the needed prefixes after allowing for node primary addresses and the configured warm-prefix target.
Custom networkingConfirm AWS_VPC_K8S_CNI_CUSTOM_NETWORK_CFG=true, enumerate ENIConfig resources, and map each node AZ to its spec.subnet and security groups.The ENIConfig pod subnet, not only the cluster/node subnet, has capacity for the surge pod-IP demand in every used AZ.
Security Groups for PodsConfirm ENABLE_POD_ENI=true, inspect trunk ENIs and the instance-type-specific branch-ENI limit for each node type.Required branch ENIs/pod slots for surge workloads with pod SGs do not exceed the published limit for any instance type. Do not use generic ENI limits as a substitute.
IPv6Confirm IPv6 family and Nitro-compatible node/Fargate support. IPv6 pod addressing does not consume IPv4 pod IPs, but nodes still need valid ENI/subnet capacity.Node ENI and subnet capacity cover surge nodes; custom networking is not assumed because it is unsupported with IPv6.
bash
# Custom networking: inspect every AZ-to-pod-subnet mapping
kubectl get eniconfig -o json | jq '.items[] | {name: .metadata.name, subnet: .spec.subnet, securityGroups: .spec.securityGroups}'

# Security Groups for Pods: inspect trunk/branch interfaces after mode detection
aws ec2 describe-network-interfaces \
  --filters Name=interface-type,Values=trunk,branch \
  --query 'NetworkInterfaces[].{type:InterfaceType,subnet:SubnetId,instance:Attachment.InstanceId,status:Status}'

Client and CI Tooling Skew (WARN-level, not a blocker)

Operator/CI tooling that is too far behind the target version causes confusing failures during and after the upgrade. Check installed versions where available:

bash
kubectl version --client -o json   # client minor version
eksctl version                      # if eksctl-managed
helm version --short                # if Helm-managed workloads
ToolSkew RuleRisk if Violated
kubectlMust be within ±1 minor of the target kube-apiserver version (upstream Kubernetes version skew policy)Unrecognized fields, API calls silently rejected or misinterpreted
eksctlMust support the target EKS version (check release notes for the version that added support)eksctl upgrade commands fail or use stale defaults
Helm3.8+ recommended for OCI registry support; otherwise not EKS-version-gatedChart operations may fail independent of the cluster upgrade
Terraform AWS providerMust be new enough to support any target-version-specific attributes in use (e.g. upgrade_policy, compute_config for Auto Mode) — check the provider changelog for the attributeterraform apply fails validation or silently ignores the new attribute

Do not hardcode exact version floors here — they shift every EKS release. Report the installed version, the rule, and a WARN if it cannot be confirmed current; never treat "tool not detected" as PASS.

Step 3: Check EKS Upgrade Insights

Primary authoritative signal. Always query first.

bash
aws eks list-insights --cluster-name <cluster> \
  --filter '{"categories":["UPGRADE_READINESS"],"kubernetesVersions":["<target>"]}'
aws eks describe-insight --cluster-name <cluster> --id <insight-id>
StatusGateAction
ERRORFAILMust fix before upgrade
WARNINGWARNRecommended fix
PASSINGPASSNo action
UNKNOWNUNKNOWNEKS could not evaluate the check; investigate and refresh
None returnedUNKNOWNContinue other checks

Freshness gate: For every returned summary, capture lastRefreshTime and lastTransitionTime, then call DescribeInsight to collect the status, affected resources, and recommendation. Treat data as stale when lastRefreshTime is more than 24 hours old at assessment time, or predates a known relevant workload/addon change. A stale, missing, inaccessible, or unpaginated insight set is UNKNOWN; never reuse it as PASS. The assessment must not call StartInsightsRefresh because this skill is read-only. Instead, ask the operator to refresh insights through an approved workflow and rerun the assessment after the refresh completes.

Critical: Insights does NOT cover Helm stored manifests, CRD deprecations, StatefulSets, Karpenter, service quotas, PDBs, or capacity planning.

Step 4: API Deprecation Analysis

Check version-specific removal gates relevant to user's target:

  • ≥1.33: AL2 AMI unavailable (Critical)
  • ≥1.35: kube-proxy IPVS deprecated; ≥1.36: removed
  • ≥1.25: Dockershim and PodSecurityPolicy removed
  • ≥1.23: In-tree EBS provisioner deprecated

Helm stored manifests — the #1 missed blocker. Scan latest deployed release secrets for deprecated apiVersion lines:

bash
kubectl get secrets -A -l owner=helm,status=deployed
# Decode: base64 -d | base64 -d | gunzip | jq -r '.manifest'

Third-party CRD deprecations — check Istio, cert-manager, Karpenter, Flux, Argo, Prometheus Operator versions against known deprecation timelines.

Tools: kubent, pluto detect-all-in-cluster, helm mapkubeapis --dry-run. See references/api-deprecations.md for full removal schedule.

Step 5: Addon Compatibility Check

Managed addons: Use live API to build compatibility matrix:

bash
aws eks list-addons --cluster-name <cluster>
aws eks describe-addon --cluster-name <cluster> --addon-name <name>
aws eks describe-addon-versions --addon-name <name> --kubernetes-version <target>

Self-managed addons: First compare ListAddons with the actual kube-system workloads. Explicitly detect the three core addons: aws-node (VPC CNI), coredns, and kube-proxy. If a core component is absent from the managed-addon inventory but present in-cluster, mark it self-managed/custom and inspect its image, args, and configuration before assessing target support:

bash
kubectl -n kube-system get daemonset aws-node kube-proxy -o json | \
  jq '.items[] | {name: .metadata.name, images: [.spec.template.spec.containers[].image], args: [.spec.template.spec.containers[].args]}'
kubectl -n kube-system get deployment coredns -o json | \
  jq '.items[] | {name: .metadata.name, images: [.spec.template.spec.containers[].image], args: [.spec.template.spec.containers[].args]}'
kubectl -n kube-system get configmap coredns aws-node -o yaml

For a custom CoreDNS Corefile, run the Corefile migration check. For VPC CNI, validate custom environment/config-map values and the mode-specific capacity gate in Step 2. For kube-proxy, validate its deployed mode and version against its upstream support policy. Then scan other self-managed components (aws-load-balancer, external-dns, metrics-server, cluster-autoscaler, cert-manager, ingress-nginx, argocd, flux); extract image tags and validate against their K8s support matrices.

Pod Identity Agent (eks-pod-identity-agent): Check like any other managed addon via DescribeAddon / DescribeAddonVersions — its version gates which association features are available (e.g. multiple associations per pod, target IAM role sessions). If not installed but kubectl get pods -A -o json shows service accounts with eks.amazonaws.com/role-arn annotations instead, the cluster is on IRSA, not Pod Identity — note this for blue-green planning (see references/upgrade-troubleshooting.md → Identity Migration Considerations).

Upgrade order: Pre-CP: Karpenter, Cluster Autoscaler, incompatible webhooks. Post-CP: kube-proxy → vpc-cni → coredns → CSI drivers → others → self-managed.

See references/addon-version-matrix.md for static fallback reference.

Step 6: Full Data Plane Inventory

Inventory ALL node populations. See references/data-plane-inventory.md for complete detection commands.

  • MNG: aws eks list-nodegroups + describe-nodegroup for each
  • Self-managed ASGs: Find by cluster tag in describe-auto-scaling-groups
  • Karpenter: NodePools, EC2NodeClasses, controller version and health
  • Auto Mode: Check cluster.computeConfig.enabled
  • Fargate: aws eks list-fargate-profiles + describe each
  • Kubelet versions: kubectl get nodes — confirm within skew window

Version skew requires two independent predicates:

  1. Current-state upper bound: no kubelet may be newer than the current control plane (kubelet_minor <= current_control_plane_minor). A node already newer than the current API server is an invalid state and must be corrected before planning the upgrade.
  2. Target lower bound: for target 1.X, kubelet must be at least 1.(X-3) when X>=28, or 1.(X-2) when X<28.

Any node violating either predicate is a FAIL.

Step 7: AL2 → AL2023 Migration Assessment

If AL2 detected and target ≥1.33: CRITICAL blocker (EKS releases AL2 AMIs only through 1.32). If AL2 is detected with a target <1.33: WARNING — upstream Amazon Linux 2 reaches end of life on June 30, 2026.

Assess: bootstrap method (bootstrap.sh vs nodeadm), custom AMIs, user data compatibility (yum→dnf, kubelet-extra-args→NodeConfig), cgroup v2 workload compatibility, IMDSv2 readiness.

See references/al2-al2023-migration.md for full detection commands and migration strategy.

Step 8: Upgrade Ordering and Pre-Upgrade Alignment

Pre-CP: Karpenter (if needed), Cluster Autoscaler (must match target), admission webhooks with failurePolicy: Fail, custom controllers using deprecated APIs.

Post-CP: Standard addon and node group upgrade order (Step 5).

Webhook check:

bash
kubectl get validatingwebhookconfigurations -o json | jq '.items[] | select(.webhooks[].failurePolicy == "Fail")'
kubectl get mutatingwebhookconfigurations -o json | jq '.items[] | select(.webhooks[].failurePolicy == "Fail")'

Step 9: PDB, Topology Spread, and Workload Safety

PDB blockers: maxUnavailable: 0, minAvailable == replicas, orphaned PDBs:

bash
kubectl get pdb -A -o json | jq '.items[] | select(.status.disruptionsAllowed == 0)'

Pre-drain safety (DRAIN-01 to DRAIN-06): Bare pods, emptyDir data loss, custom finalizers, EBS AZ-pinning, webhook deadlock, CoreDNS SPOF. See references/pre-drain-safety.md for full detection commands.

TopologySpreadConstraints: Flag multi-replica deployments without topology spread.

StatefulSet safety: Check terminationGracePeriodSeconds != 0, PVC retention policy, single-replica without PDB, update strategy.

Scaled-to-zero workloads: Detect and flag for separate validation.

Step 10: Pre-Upgrade Cluster Health Baseline

Confirm healthy steady state before upgrade. Failures compound on unhealthy clusters.

  • Node health: All nodes Ready, no MemoryPressure/DiskPressure/PIDPressure
  • Pending CSRs: Indicate node registration issues
  • Crash-looping system pods: Check kube-system, monitoring, ingress namespaces
  • Metrics and DNS baseline: Verify metrics-server and CoreDNS responding

Record baselines for post-upgrade comparison.

Step 11: Fargate Considerations

Fargate pods upgrade when redeployed after CP upgrade. All Fargate pods must be restarted post-upgrade. Restart command is in Step 14 (mutation, requires approval).

Step 12: Management Plane and IaC Ownership Detection

Detect management method to route remediation correctly:

DetectionManagement PlaneMutation Routing
ACK CRD + Cluster CRACKPatch ACK Cluster CR
ACK CR with kro.run/ownedKRO over ACKPatch kro instance
Tags: terraform:*TerraformUpdate .tf, terraform apply
Tags: aws:cloudformation:*CloudFormationUpdate template, stack update
Tags: aws:cdk:*CDKUpdate construct, cdk deploy
Tags: eksctl.cluster.k8s.io/*eksctlUpdate config, eksctl upgrade
Labels: argocd.argoproj.io/*ArgoCDUpdate Git source, sync
Labels: kustomize.toolkit.fluxcd.io/*FluxUpdate Git source, reconcile
Tags: pulumi:*PulumiUpdate program, pulumi up
None foundunknownBlock mutations until confirmed

Route ALL remediation through the owning tool — never suggest direct AWS CLI when IaC is detected (causes drift).

Step 13: Autoscaler Pause During Node Rotation

During upgrades, autoscalers can interfere with rolling replacement. Check current Karpenter consolidation config and Cluster Autoscaler scale-down state. Recommend pausing both before node rotation and re-enabling after completion.

Pause commands are in Step 14 (mutations, require operator approval).

Step 14: Remediation Playbook (Operator Approval Required)

⚠️ ALL commands in this section are MUTATIONS. The agent MUST NOT execute these — present as a playbook for operator review.

  • 14.1 Helm stored manifest fix: helm mapkubeapis + helm upgrade
  • 14.2 Addon conflict resolution: first capture DescribeAddon output and configurationValues; use --resolve-conflicts PRESERVE to retain reviewed custom configuration, or OVERWRITE only after approving replacement with EKS defaults and recording rollback steps. OVERWRITE can discard custom configuration.
  • 14.3 Fargate pod restart: kubectl rollout restart across namespaces
  • 14.4 PDB temporary adjustment: kubectl patch pdb (revert after upgrade)
  • 14.5 Karpenter pause: kubectl annotate nodepools --all "karpenter.sh/do-not-disrupt=true"
  • 14.6 CA scale-down pause: patch CA config scale-down-enabled=false
  • 14.7 Node group upgrade: MNG via update-nodegroup-version, Karpenter via EC2NodeClass patch (drift), self-managed via launch template update

Step 15: Post-Upgrade Functional Validation

Present as validation checklist for operator:

  • DNS resolution (nslookup kubernetes.default)
  • Metrics server (kubectl top nodes/pods)
  • Pod scheduling (run test pod)
  • Load balancer health (target group check)
  • IRSA / Pod Identity (sts get-caller-identity from pod)
  • CoreDNS and kube-proxy pods running
  • Compare against Step 10 baseline (node count, no new CrashLoopBackOff)

Step 16: Generate Upgrade Plan and Report

Execution Order:

  1. Pre-upgrade alignment (Karpenter/CA/webhooks)
  2. Pause autoscalers
  3. Control plane upgrade (15-40 min)
  4. Wait for ACTIVE status
  5. kube-proxy → vpc-cni → coredns → other managed addons
  6. Self-managed addons
  7. Node groups (one at a time, validate between)
  8. Karpenter nodes (drift-based)
  9. Self-managed nodes (launch template update)
  10. Fargate pods (restart)
  11. Re-enable autoscalers
  12. Post-upgrade validation

Rollback Matrix:

ComponentReversibilityMethod
Control planeCONDITIONAL (7-day window)aws eks update-cluster-version --kubernetes-version <N-1>
AddonsFULLDowngrade to previous version
MNGPARTIALCan halt; completed nodes stay
Karpenter nodesFULLRevert EC2NodeClass
Self-managedFULLRevert launch template
FargateFULLRedeploy previous config

Rollback eligibility has two phases:

  • Pre-upgrade (advisory only): confirm the planned upgrade is one minor, document the 7-day window and component rollback order, but do not claim the future cluster will be eligible. Rollback readiness insights do not exist until after an eligible upgrade completes.
  • Post-upgrade (authoritative): while the cluster is ACTIVE and still inside the 7-day window, run aws eks list-insights --cluster-name <cluster> --filter '{"categories":["ROLLBACK_READINESS"]}', paginate, then describe-insight for each entry. ERROR blocks a normal rollback; UNKNOWN means EKS could not evaluate readiness and also blocks a normal rollback. Only PASSING insights support an eligible rollback.

This assessment reports the result but never performs update-cluster-version or a forced rollback.

Step 17: Report Format

## EKS Upgrade Readiness Report
**Cluster:** <name> (<region>)
**Current Version:** <current>
**Target Version:** <target>
**Assessment Date:** <date>
**Management Plane:** <detected>
**Evidence Completeness:** <X>% (<performed>/<applicable>)
**Overall Readiness:** READY / NOT READY / READY WITH WARNINGS / CANNOT DETERMINE

### Pre-Upgrade Health Baseline
- [PASS/FAIL] (confidence: HIGH) All nodes Ready
- [PASS/FAIL] (confidence: HIGH) No pending CSRs
- [PASS/FAIL] (confidence: HIGH) No crash-looping system pods
- [PASS/FAIL] (confidence: HIGH) DNS resolution working
- [PASS/FAIL] (confidence: HIGH) Metrics server responding

### Infrastructure Prerequisites
- [PASS/FAIL] (confidence: HIGH) Subnet IP availability (mode: <type>)
- [PASS/FAIL] (confidence: HIGH) EKS IAM role valid
- [PASS/FAIL/N/A] (confidence: HIGH) KMS key access
- [PASS/FAIL] (confidence: HIGH) EC2 vCPU quota headroom
- [PASS/FAIL] (confidence: HIGH) EBS volume quota headroom

### EKS Upgrade Insights
- [PASS/FAIL/UNKNOWN] (confidence: HIGH) <summary>

### Data Plane Inventory
- Managed Node Groups: <count> (versions: <list>)
- Self-Managed ASGs: <count> (versions: <list>)
- Karpenter NodePools: <count> (version: <ver>)
- Fargate Profiles: <count>
- Total Nodes: <count>

### Blockers (must fix)
1. [FAIL] (confidence: HIGH) <description> — <remediation>

### Warnings (recommended)
1. [WARN] (confidence: MEDIUM) <description> — <recommendation>

### Passing Checks
1. [PASS] (confidence: HIGH) <description>

### Unknown / Not Assessed
1. [UNKNOWN] <gate> — <reason>

### Upgrade Plan
<execution order from Step 16>

### Rollback Window
- Rollback eligibility: ELIGIBLE / NOT ELIGIBLE / CHECK AFTER UPGRADE
- Window: 7 days from CP upgrade completion
- Note: Add-ons and node groups must be rolled back BEFORE CP

### Pre-Drain Risks
- Bare pods (DRAIN-01): <count>
- EmptyDir data loss (DRAIN-02): <count>
- EBS AZ-pinning (DRAIN-04): <count>
- Webhook deadlock (DRAIN-05): <assessment>
- CoreDNS SPOF (DRAIN-06): <status>

### Estimated Timeline
- Control plane: ~30 min
- Addons: ~5 min each
- Node groups: ~<X> min per group
- Total: ~<Y> min

Machine-Readable Output

When the operator asks for a structured result (CI/CD gating, scripted polling, dashboards), emit this JSON alongside — never instead of — the markdown report. Every gate in the markdown report must have a matching entry; the JSON is a serialization of the same evidence, not a summary.

json
{
  "cluster": "<name>",
  "region": "<region>",
  "assessmentTimestamp": "<ISO-8601>",
  "currentVersion": "<current>",
  "targetVersion": "<target>",
  "overallVerdict": "READY | READY_WITH_WARNINGS | NOT_READY | CANNOT_DETERMINE",
  "evidenceCompletenessPct": 0,
  "gates": [
    {
      "id": "<check-id from required-check-registry.yaml, e.g. NODE-04, ADDON-02, INFRA-01>",
      "name": "<human-readable check name>",
      "status": "PASS | FAIL | WARN | UNKNOWN | N_A",
      "confidence": "HIGH | MEDIUM | LOW",
      "evidence": "<short evidence string, same as markdown bullet>",
      "remediation": "<remediation text, or null if PASS>",
      "checkedAt": "<ISO-8601>"
    }
  ],
  "rollback": {
    "eligible": true,
    "windowExpiresAt": "<ISO-8601 or null>"
  }
}

gates[].id maps 1:1 to the IDs in references/required-check-registry.yaml (prefixes: PF- pre-flight, INFRA- infrastructure, NODE- node assessment, ADDON- addon assessment, WKLD- workload assessment, KARP- Karpenter, DRAIN- pre-drain safety, ROLL- rollback), so a CI pipeline can gate on specific check categories (e.g. fail only on NODE-* or ADDON-* FAILs, warn-only on others) instead of just the overall verdict. overallVerdict follows the same rules as the markdown report — it is never READY while any gate is UNKNOWN.

References

See references/ directory for:

  • safety-invariants.md — Hard safety rules, knowledge hierarchy, operation classification
  • required-check-registry.yaml — All 60+ checks with IDs, categories, and severity
  • pre-flight-checks.yaml — Blocking vs warning checks, timeouts, soak periods, rollback conditions
  • api-deprecations.md — Full K8s API removal schedule by version
  • addon-version-matrix.md — EKS addon compatibility per version (static fallback)
  • capacity-planning.md — FDCR/ODCR and surge capacity guidance
  • upgrade-troubleshooting.md — Common failures, feature removals, and tools
  • karpenter-checks.md — Full 14-check Karpenter registry (KARP-01 to KARP-14)
  • pre-drain-safety.md — DRAIN-01 to DRAIN-06 detection and remediation
  • al2-al2023-migration.md — AL2→AL2023 migration assessment details
  • data-plane-inventory.md — MNG, self-managed, Karpenter, Auto Mode, Fargate inventory commands

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Eks Upgrade Readiness AI skill do?

Use this skill when a user asks to assess, plan, or validate an Amazon EKS cluster upgrade. Activate on requests mentioning "EKS upgrade", "Kubernetes version upgrade", "upgrade readiness", "upgrade plan", "pre-upgrade check", "version skew", "deprecated API", "addon compatibility", "node group upgrade", "control plane upgrade", "EKS end of support", "EKS extended support", "Karpenter drift", "kubelet version skew", or "blue-green cluster migration". It runs a pre-upgrade assessment per the AWS EKS Best Practices Guide, covering infrastructure prerequisites, EKS Upgrade Insights, API deprec...

Why use Eks Upgrade Readiness on TypingMind?

Because you install it once and use it with any model. Eks Upgrade Readiness is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Eks Upgrade Readiness in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aws/tools-for-devops-agent/tree/main/skills/eks-upgrade-readiness. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Eks Upgrade Readiness?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Eks Upgrade Readiness?

As many as you like. As long as a model supports skills, you can use Eks Upgrade Readiness with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Eks Upgrade Readiness AI skill free?

Yes. It is published on GitHub by aws under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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