mckinsey/agents-at-scale-ark

multi-branch-cluster-setup

Set up N isolated minikube clusters, one per Git worktree, for parallel Ark branch development.

First seen Jun 12, 2026

Installation

$ npx skills add mckinsey/agents-at-scale-ark --skill multi-branch-cluster-setup

Summary

  • Set up N isolated minikube clusters, one per Git worktree, for parallel Ark branch development.
  • Use when the user wants to run multiple branches simultaneously, set up isolated Kubernetes environments per branch, create git worktrees with dedicated clusters, or configure devspace contexts for multi-branch development.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 419
License LICENSE
Default branch main
Open issues 343
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 6,646 B
  • docs SUMMARY.md 353 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 4 installs

SKILL.md

Multi-Branch Cluster Setup

Provisions one minikube cluster per branch supplied by the user. The number of clusters matches the number of branches — 2 branches = 2 clusters, 4 branches = 4 clusters, etc.

Cluster naming and port assignment (dynamic, based on branches provided):

# Cluster name Worktree Branch Dashboard API Gateway
1 ark-cluster-1 $ARK_REPO (main repo, no worktree needed if branch 1 = current) branch 1 :3274 :8080 :8090
2 ark-cluster-2 /tmp/ark-worktree-<branch2-slug> branch 2 :3275 :8081 :8091
3 ark-cluster-3 /tmp/ark-worktree-<branch3-slug> branch 3 :3276 :8082 :8092
N ark-cluster-N /tmp/ark-worktree-<branchN-slug> branch N :3273+N :8079+N :8089+N

Port formula: Dashboard = 3273+N, API = 8079+N, Gateway = 8089+N

Prerequisites check

Run before starting:

minikube version && kubectl version --client && helm version --short && devspace version && docker info | grep "Total Memory"

Set your repo path (replace with your actual checkout location):

export ARK_REPO=~/agents-at-scale-ark  # adjust if cloned elsewhere

Docker Desktop memory requirement: ~0.7 GB base + (N × 2.2 GB). For 3 clusters: ~7 GB minimum. Set via Docker Desktop → Settings → Resources → Memory.

Step 1 — Extract branches from the user's request

If the user's message contains branch names (e.g. "create clusters with branch1 branch2 branch3"), extract all of them directly — do NOT ask for confirmation.

  • The number of clusters = the number of branches provided
  • Assign each branch to ark-cluster-N (N = 1, 2, 3...)
  • Branch slug = branch name with / replaced by -
  • Branch 1 uses $ARK_REPO directly if it matches the current checkout; otherwise also gets a worktree
  • Branches 2..N each get a worktree at /tmp/ark-worktree-<branchN-slug>

If no branches are provided in the message, ask how many clusters and which branches.

Step 2 — Create Git worktrees

For each branch beyond the first (or all branches if branch 1 differs from current checkout):

cd $ARK_REPO

# Repeat for each branch N >= 2:
git worktree add /tmp/ark-worktree-<branchN-slug> <BRANCHN>

# Verify
git worktree list

Step 3 — Clean up and create clusters

Pass the branch names directly to the setup script — it handles cleanup, cluster creation, and devspace binding automatically:

bash .claude/skills/multi-branch-cluster-setup/scripts/setup-clusters.sh <branch1> <branch2> [branchN...]

The script:

  1. Kills all running devspace/port-forward processes
  2. Deletes all existing minikube profiles
  3. Creates ark-cluster-N per branch (cluster-1: 3 GB / 3 CPUs, others: 2.2 GB / 2 CPUs)
  4. Binds devspace context in each worktree
  5. Writes /tmp/ark-cluster-state.conf — used by all subsequent scripts

Step 4 — Deploy Ark to cluster-1

Deploy cluster-1 first. The first build takes 30–45 min (Go toolchain download + compilation). Subsequent clusters use image transfer to skip rebuilding.

cd $ARK_REPO

DOCKER_BUILDKIT=0 devspace deploy \
  --kube-context ark-cluster-1 \
  --namespace default \
  --skip-push-local-kube

If ark-broker or ark-dashboard fail with context canceled (buildx issue), deploy them manually:

# Build dashboard with legacy builder
cd $ARK_REPO/services/ark-dashboard
docker build -t ark-dashboard:main-local .
minikube image load ark-dashboard:main-local -p ark-cluster-1

helm upgrade --install ark-dashboard ./chart \
  --kube-context ark-cluster-1 --namespace default \
  --set image.repository=ark-dashboard \
  --set image.tag=main-local \
  --set image.pullPolicy=Never

# Deploy ark-api
docker tag ark-api:latest ark-api:main-local
minikube image load ark-api:main-local -p ark-cluster-1

helm upgrade --install ark-api ./services/ark-api/chart \
  --kube-context ark-cluster-1 --namespace default \
  --set image.repository=ark-api \
  --set image.tag=main-local \
  --set image.pullPolicy=Never \
  --set rbac.clusterWide=true

Step 5 — Transfer images to other clusters (skip rebuilding)

Once cluster-1 is deployed, export its images and load into all remaining clusters:

bash .claude/skills/multi-branch-cluster-setup/scripts/transfer-images.sh

Then deploy remaining services via helm to each cluster 2..N:

# Repeat for each cluster beyond the first:
for CLUSTER in ark-cluster-2 ark-cluster-3 ...; do
  bash .claude/skills/multi-branch-cluster-setup/scripts/deploy-helm.sh $CLUSTER
done

Step 6 — Start port forwarding

bash .claude/skills/multi-branch-cluster-setup/scripts/port-forward.sh start

Access dashboards at (ports increment per cluster):

Common operations

# Check all cluster states
minikube profile list

# Check pods across all clusters
for c in $(minikube profile list -o json | jq -r '.[].Name'); do
  echo "=== $c ==="; kubectl get pods --context=$c -A --no-headers | grep -v kube-system
done

# Stop a specific cluster to free memory
minikube stop -p ark-cluster-2

# Port forward management
bash .claude/skills/multi-branch-cluster-setup/scripts/port-forward.sh status
bash .claude/skills/multi-branch-cluster-setup/scripts/port-forward.sh stop

# Run devspace dev on a specific worktree
cd /tmp/ark-worktree-<branch-slug> && devspace dev

Troubleshooting

CRD not found error after deploy: The kubectl wait in the devspace pipeline uses the current context. Run kubectl config use-context <cluster> before re-running devspace deploy.

context canceled on ark-broker/ark-dashboard: Always caused by BuildKit. Set DOCKER_BUILDKIT=0 or use the manual helm approach in Step 4.

Memory pressure: If pods are OOMKilled, stop clusters you aren't actively using (minikube stop -p ark-cluster-N). Each cluster uses ~2.2 GB.

Stale devspace context: Each worktree stores its context in .devspace/generated.yaml. If a cluster was deleted and recreated, re-run devspace use context <cluster> from that worktree.