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Progressive delivery with Argo Rollouts and Flagger. Use when implementing canary deployments, blue-green deployments, or traffic shifting strategies.
npx skill4agent add rohitg00/kubectl-mcp-server k8s-rollouts| Priority | Rule | Impact | Tools |
|---|---|---|---|
| 1 | Detect Argo Rollouts installation first | CRITICAL | |
| 2 | Check rollout status before promoting | HIGH | |
| 3 | Monitor analysis runs for failures | HIGH | |
| 4 | Abort immediately on critical failures | CRITICAL | |
| Task | Tool | Example |
|---|---|---|
| Detect Argo Rollouts | | |
| List rollouts | | |
| Get rollout status | | |
| Promote rollout | | |
rollouts_detect_tool()rollouts_list_tool(namespace="default")
# Shows:
# - Rollout name
# - Strategy (canary/blueGreen)
# - Status
# - Desired/Ready replicasrollout_get_tool(name="my-rollout", namespace="default")
# Shows:
# - Spec (strategy, steps)
# - Status (phase, conditions)
# - Current steprollout_status_tool(name="my-rollout", namespace="default")
# Returns detailed status with:
# - Current step index
# - Canary weight
# - Stable/canary replicasets# Promote to next step
rollout_promote_tool(name="my-rollout", namespace="default")
# Full promote (skip remaining steps)
rollout_promote_tool(name="my-rollout", namespace="default", full=True)rollout_abort_tool(name="my-rollout", namespace="default")
# Reverts to stable versionrollout_retry_tool(name="my-rollout", namespace="default")
# Retry failed rolloutrollout_restart_tool(name="my-rollout", namespace="default")
# Triggers new rollout with same spec# List analysis runs
analysis_runs_list_tool(namespace="default")
# Analysis runs verify rollout health:
# - Prometheus metrics
# - Web hooks
# - Custom jobskubectl_apply(manifest="""
apiVersion: argoproj.io/v1alpha1
kind: Rollout
metadata:
name: my-rollout
namespace: default
spec:
replicas: 5
strategy:
canary:
steps:
- setWeight: 20
- pause: {duration: 1m}
- setWeight: 40
- pause: {duration: 1m}
- setWeight: 60
- pause: {duration: 1m}
- setWeight: 80
- pause: {duration: 1m}
selector:
matchLabels:
app: my-app
template:
metadata:
labels:
app: my-app
spec:
containers:
- name: app
image: my-app:v2
ports:
- containerPort: 8080
""")kubectl_apply(manifest="""
apiVersion: argoproj.io/v1alpha1
kind: Rollout
metadata:
name: my-rollout
namespace: default
spec:
replicas: 3
strategy:
blueGreen:
activeService: my-app-active
previewService: my-app-preview
autoPromotionEnabled: false
selector:
matchLabels:
app: my-app
template:
metadata:
labels:
app: my-app
spec:
containers:
- name: app
image: my-app:v2
""")flagger_canaries_list_tool(namespace="default")
# Shows:
# - Canary name
# - Status (Initialized, Progressing, Succeeded, Failed)
# - Weightflagger_canary_get_tool(name="my-canary", namespace="default")kubectl_apply(manifest="""
apiVersion: flagger.app/v1beta1
kind: Canary
metadata:
name: my-canary
namespace: default
spec:
targetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app
service:
port: 80
analysis:
interval: 30s
threshold: 5
maxWeight: 50
stepWeight: 10
metrics:
- name: request-success-rate
threshold: 99
interval: 1m
- name: request-duration
threshold: 500
interval: 1m
""")1. rollouts_list_tool(namespace)
2. # Update image in rollout
3. rollout_status_tool(name, namespace) # Monitor progress
4. rollout_promote_tool(name, namespace) # Promote when ready
5. # Or: rollout_abort_tool(name, namespace) if issues1. rollout_get_tool(name, namespace) # Check current state
2. # Update image
3. rollout_status_tool(name, namespace) # Wait for preview ready
4. # Test preview service
5. rollout_promote_tool(name, namespace) # Switch traffic1. rollout_status_tool(name, namespace) # Check current step
2. analysis_runs_list_tool(namespace) # Check analysis
3. get_events(namespace) # Check events
4. # If analysis failing:
rollout_abort_tool(name, namespace)1. analysis_runs_list_tool(namespace)
2. # Check metrics source (Prometheus, etc.)
3. # Verify threshold configuration
4. rollout_retry_tool(name, namespace) # Retry if transient