Progressive Delivery with Argo Rollouts & Flagger

Manage progressive deployments using kubectl-mcp-server's rollout tools (11 tools).

When to Apply

Use this skill when:

• User mentions: "canary", "blue-green", "progressive delivery", "Argo Rollouts", "Flagger"

• Operations: rolling out new versions, traffic splitting, automated rollbacks

• Keywords: "gradual rollout", "traffic shift", "analysis run", "promote", "abort"

Priority Rules

Priority Rule Impact Tools

1 Detect Argo Rollouts installation first CRITICAL rollouts_detect_tool

2 Check rollout status before promoting HIGH rollout_status_tool

3 Monitor analysis runs for failures HIGH analysis_runs_list_tool

4 Abort immediately on critical failures CRITICAL rollout_abort_tool

Quick Reference

Task Tool Example

Detect Argo Rollouts rollouts_detect_tool

rollouts_detect_tool()

List rollouts rollouts_list_tool

rollouts_list_tool(namespace)

Get rollout status rollout_status_tool

rollout_status_tool(name, namespace)

Promote rollout rollout_promote_tool

rollout_promote_tool(name, namespace)

Check Installation

rollouts_detect_tool()

Argo Rollouts

List Rollouts

rollouts_list_tool(namespace="default")

Shows:

- Rollout name

- Strategy (canary/blueGreen)

- Status

- Desired/Ready replicas

Get Rollout Details

rollout_get_tool(name="my-rollout", namespace="default")

Shows:

- Spec (strategy, steps)

- Status (phase, conditions)

- Current step

Check Rollout Status

rollout_status_tool(name="my-rollout", namespace="default")

Returns detailed status with:

- Current step index

- Canary weight

- Stable/canary replicasets

Promote Rollout

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)

Abort Rollout

rollout_abort_tool(name="my-rollout", namespace="default")

Reverts to stable version

Retry Rollout

rollout_retry_tool(name="my-rollout", namespace="default")

Retry failed rollout

Restart Rollout

rollout_restart_tool(name="my-rollout", namespace="default")

Triggers new rollout with same spec

Analysis Runs

List analysis runs

analysis_runs_list_tool(namespace="default")

Analysis runs verify rollout health:

- Prometheus metrics

- Web hooks

- Custom jobs

Create Canary Rollout

kubectl_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 """)

Create Blue-Green Rollout

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

List Canaries

flagger_canaries_list_tool(namespace="default")

Shows:

- Canary name

- Status (Initialized, Progressing, Succeeded, Failed)

- Weight

Get Canary Details

flagger_canary_get_tool(name="my-canary", namespace="default")

Create Flagger Canary

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 """)

Progressive Delivery Workflows

Canary Deployment

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 issues

Blue-Green Deployment

1. 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 traffic

Troubleshooting

Rollout Stuck

1. 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)

Canary Failing Analysis

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

Related Skills

• k8s-deploy - Standard deployments

• k8s-service-mesh - Traffic management with Istio