deployment-knowledge
Deployment knowledge base. Provides zero-downtime strategies, blue-green deployment, canary releases, rolling updates, rollback procedures, feature flags, and health check patterns.
Works with
---
name: deployment-knowledge
description: Deployment knowledge base. Provides zero-downtime strategies, blue-green deployment, canary releases, rolling updates, rollback procedures, feature flags, and health check patterns.
license: MIT
---
# Deployment Knowledge Base
Quick reference for deployment strategies, zero-downtime patterns, and release management.
## Deployment Strategies
### Strategy Comparison
| Strategy | Downtime | Rollback Speed | Risk | Resource Usage |
|----------|----------|----------------|------|----------------|
| **Recreate** | Yes | Slow | High | 1x |
| **Rolling** | No | Medium | Medium | 1.25x |
| **Blue-Green** | No | Instant | Low | 2x |
| **Canary** | No | Fast | Very Low | 1.1x |
| **A/B Testing** | No | Fast | Low | Variable |
```
┌─────────────────────────────────────────────────────────────────┐
│ DEPLOYMENT STRATEGIES │
├─────────────────────────────────────────────────────────────────┤
│ │
│ RECREATE ROLLING BLUE-GREEN CANARY │
│ ┌───┐ ┌───┬───┐ ┌───┐ ┌───┐ ┌───┐ │
│ │ v1│ │v1 │v1 │ │ v1│ │ v2│ │v1 │ 90% │
│ └───┘ └───┴───┘ └───┘ └───┘ └───┘ │
│ ↓ ↓ ↓ ↕ ┌───┐ │
│ ┌───┐ ┌───┬───┐ Traffic │v2 │ 10% │
│ │ v2│ │v2 │v1 │ Switch └───┘ │
│ └───┘ └───┴───┘ │
│ ↓ ↓ │
│ ┌───┬───┐ │
│ │v2 │v2 │ │
│ └───┴───┘ │
└─────────────────────────────────────────────────────────────────┘
```
## Blue-Green Deployment
### Overview
Two identical environments (Blue = current, Green = new). Traffic switches instantly.
```yaml
# Environment structure
environments:
blue:
url: blue.example.com
version: v1.2.3
active: true
green:
url: green.example.com
version: v1.2.4
active: false
# Load balancer config
upstream backend {
server blue.example.com weight=100;
server green.example.com weight=0;
}
```
### Deployment Steps
```bash
#!/bin/bash
# blue-green-deploy.sh
ACTIVE=$(get_active_environment)
INACTIVE=$(get_inactive_environment)
# 1. Deploy to inactive environment
deploy_to_environment $INACTIVE $VERSION
# 2. Run health checks
if ! health_check $INACTIVE; then
echo "Health check failed, aborting"
exit 1
fi
# 3. Run smoke tests
if ! smoke_tests $INACTIVE; then
echo "Smoke tests failed, aborting"
exit 1
fi
# 4. Switch traffic
switch_traffic_to $INACTIVE
# 5. Verify
if ! verify_deployment $INACTIVE; then
echo "Verification failed, rolling back"
switch_traffic_to $ACTIVE
exit 1
fi
# 6. Mark as active
set_active_environment $INACTIVE
```
### Rollback
```bash
# Instant rollback - just switch traffic back
switch_traffic_to $PREVIOUS_ACTIVE
```
## Canary Deployment
### Traffic Distribution
```yaml
# Canary stages
stages:
- name: canary-5
traffic: 5%
duration: 10m
- name: canary-25
traffic: 25%
duration: 30m
- name: canary-50
traffic: 50%
duration: 1h
- name: full-rollout
traffic: 100%
```
### Implementation
```yaml
# nginx canary config
upstream backend {
server stable.example.com weight=95;
server canary.example.com weight=5;
}
# Or with cookie-based routing
map $cookie_canary $backend {
"true" canary.example.com;
default stable.example.com;
}
```
### Canary Analysis
```yaml
# Automated canary analysis
analysis:
metrics:
- name: error_rate
threshold: 1%
comparison: less_than
- name: latency_p99
threshold: 500ms
comparison: less_than
- name: success_rate
threshold: 99%
comparison: greater_than
duration: 10m
interval: 1m
on_failure: rollback
on_success: promote
```
## Rolling Deployment
### Configuration
```yaml
# Kubernetes-style rolling update
deployment:
replicas: 4
strategy:
type: RollingUpdate
rollingUpdate:
maxUnavailable: 1
maxSurge: 1
```
### Sequence
```
Time →
Pod 1: [v1][v1][v1][v2][v2][v2][v2]
Pod 2: [v1][v1][v1][v1][v2][v2][v2]
Pod 3: [v1][v1][v1][v1][v1][v2][v2]
Pod 4: [v1][v1][v1][v1][v1][v1][v2]
```
## Zero-Downtime Checklist
### Database Migrations
```php
// WRONG: Destructive migration
Schema::dropColumn('users', 'old_field');
// RIGHT: Backward-compatible migration
// Step 1: Add new column (deploy #1)
Schema::addColumn('users', 'new_field');
// Step 2: Migrate data (deploy #2)
DB::statement('UPDATE users SET new_field = old_field');
// Step 3: Switch code to use new_field (deploy #3)
// Step 4: Drop old column (deploy #4, weeks later)
Schema::dropColumn('users', 'old_field');
```
### Migration Strategies
| Change | Strategy |
|--------|----------|
| Add column | Add with default, deploy, backfill |
| Remove column | Stop using, deploy, wait, remove |
| Rename column | Add new, migrate, switch, remove old |
| Change type | Add new column, migrate, switch |
| Add index | Online DDL, low-traffic window |
### Health Checks
```php
// Readiness probe - can accept traffic?
public function ready(): JsonResponse
{
return response()->json([
'database' => $this->checkDatabase(),
'cache' => $this->checkCache(),
'queue' => $this->checkQueue(),
]);
}
// Liveness probe - is the app running?
public function live(): JsonResponse
{
return response()->json(['status' => 'ok']);
}
```
## Feature Flags
### Implementation Patterns
```php
// Simple feature flag
if (Feature::enabled('new-checkout')) {
return $this->newCheckout();
}
return $this->oldCheckout();
// User-based rollout
if (Feature::enabledForUser('new-checkout', $user)) {
return $this->newCheckout();
}
// Percentage rollout
if (Feature::enabledForPercentage('new-checkout', 10)) {
return $this->newCheckout();
}
```
### Feature Flag Service
```php
interface FeatureFlagService
{
public function isEnabled(string $feature): bool;
public function isEnabledForUser(string $feature, User $user): bool;
public function isEnabledForPercentage(string $feature, int $percent): bool;
public function getVariant(string $feature): string;
}
```
### Configuration
```yaml
# features.yaml
features:
new-checkout:
enabled: true
rollout:
type: percentage
value: 25
users:
- user-123 # Beta testers
- user-456
dark-mode:
enabled: true
rollout:
type: user_attribute
attribute: plan
values: [premium, enterprise]
```
### Best Practices
```
Feature Flag Lifecycle:
┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐
│ Create │───▶│ Rollout │───▶│ Full On │───▶│ Remove │
│ Flag │ │ 0-100% │ │ 100% │ │ Flag │
└──────────┘ └──────────┘ └──────────┘ └──────────┘
1 day 1-2 weeks 2 weeks Sprint
```
## Rollback Procedures
### Automated Rollback Triggers
```yaml
rollback:
triggers:
- metric: error_rate
threshold: 5%
window: 5m
- metric: latency_p95
threshold: 2s
window: 5m
- metric: health_check_failures
threshold: 3
window: 1m
actions:
- switch_traffic_to_previous
- notify_oncall
- create_incident
```
### Manual Rollback
```bash
#!/bin/bash
# rollback.sh
# 1. Get previous version
PREVIOUS=$(get_previous_version)
# 2. Switch traffic immediately (blue-green)
switch_traffic_to $PREVIOUS_ENV
# Or redeploy previous version (rolling)
deploy_version $PREVIOUS
# 3. Verify
health_check_all
# 4. Notify
notify_team "Rolled back to $PREVIOUS"
```
### Database Rollback
```php
// Always have down() migration
public function down(): void
{
Schema::table('users', function (Blueprint $table) {
$table->dropColumn('new_field');
});
}
```
## Environment Configuration
### Environment Matrix
```yaml
environments:
development:
replicas: 1
resources: minimal
auto_deploy: true
staging:
replicas: 2
resources: medium
auto_deploy: true
feature_flags: all_enabled
production:
replicas: 4+
resources: full
auto_deploy: false
requires_approval: true
deployment_window: "Mon-Thu 09:00-16:00"
```
### Secrets Management
```yaml
# DO NOT: Hardcode secrets
database_password: "secret123"
# DO: Use environment variables
database_password: ${DATABASE_PASSWORD}
# DO: Use secret managers
database_password:
vault: production/database
key: password
```
## Deployment Checklist
### Pre-Deployment
- [ ] All tests passing
- [ ] Code review approved
- [ ] Database migrations tested
- [ ] Rollback plan documented
- [ ] Monitoring alerts configured
- [ ] Stakeholders notified
### During Deployment
- [ ] Health checks passing
- [ ] No error spike in metrics
- [ ] Latency within SLA
- [ ] Smoke tests passing
- [ ] Feature flags working
### Post-Deployment
- [ ] Verify functionality
- [ ] Check error rates
- [ ] Monitor performance
- [ ] Update documentation
- [ ] Clean up old versions
## References
For detailed information, load these reference files:
- `references/blue-green.md` — Blue-green implementation details
- `references/canary.md` — Canary release patterns
- `references/feature-flags.md` — Feature flag best practicesMore Deployment & CI/CD skills
azure-enterprise-infra-planner
microsoft/azure-skills
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
azure-kubernetes-app-deploy
microsoft/azure-skills
Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
finetuning
microsoft/azure-skills
Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

