03Advanced_Autoscaling_and_Cost_Optimization

Author: Ameen-Alam

06_daca_deployment_guide/03_Planetary-Scale-Deployment/03_Advanced_Autoscaling_and_Cost_Optimization/Cross-Region-AutoScaling.md

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+# Cross-Region AutoScaling
+
+## Overview
+This guide provides detailed instructions for implementing cross-region autoscaling in Kubernetes deployments, ensuring optimal resource utilization and cost efficiency across multiple regions.
+
+## Prerequisites
+- Multi-region Kubernetes clusters
+- kubectl configured
+- Helm installed
+- Basic understanding of autoscaling concepts
+- Access to create and modify resources
+
+## Cluster Autoscaler Setup
+
+### 1. Install Cluster Autoscaler
+```bash
+# Add Helm repository
+helm repo add autoscaler https://kubernetes.github.io/autoscaler
+helm repo update
+
+# Install Cluster Autoscaler
+helm install cluster-autoscaler autoscaler/cluster-autoscaler \
+  --namespace kube-system \
+  --set autoDiscovery.clusterName=my-cluster \
+  --set awsRegion=us-east-1 \
+  --set rbac.create=true \
+  --set extraArgs.balance-similar-node-groups=true \
+  --set extraArgs.skip-nodes-with-system-pods=false \
+  --set extraArgs.scale-down-unneeded-time=10m \
+  --set extraArgs.scale-down-delay-after-add=10m
+```
+
+### 2. Configure Cross-Region Scaling
+```yaml
+# cross-region-autoscaler.yaml
+apiVersion: autoscaling.openshift.io/v1
+kind: ClusterAutoscaler
+metadata:
+  name: cross-region-autoscaler
+spec:
+  resourceLimits:
+    maxNodesTotal: 100
+    cores:
+      min: 8
+      max: 128
+    memory:
+      min: 32
+      max: 512
+  scaleDown:
+    enabled: true
+    delayAfterAdd: 10m
+    delayAfterDelete: 10m
+    delayAfterFailure: 3m
+    unneededTime: 10m
+```
+
+## Horizontal Pod Autoscaling
+
+### 1. Configure HPA
+```yaml
+# cross-region-hpa.yaml
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: cross-region-hpa
+  namespace: my-app
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: my-app
+  minReplicas: 2
+  maxReplicas: 10
+  metrics:
+  - type: Resource
+    resource:
+      name: cpu
+      target:
+        type: Utilization
+        averageUtilization: 70
+  - type: Resource
+    resource:
+      name: memory
+      target:
+        type: Utilization
+        averageUtilization: 80
+  behavior:
+    scaleUp:
+      stabilizationWindowSeconds: 60
+      policies:
+      - type: Pods
+        value: 4
+        periodSeconds: 60
+      - type: Percent
+        value: 100
+        periodSeconds: 60
+    scaleDown:
+      stabilizationWindowSeconds: 300
+      policies:
+      - type: Pods
+        value: 4
+        periodSeconds: 60
+      - type: Percent
+        value: 50
+        periodSeconds: 60
+```
+
+### 2. Configure Custom Metrics
+```yaml
+# custom-metrics.yaml
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: custom-metrics-config
+  namespace: kube-system
+data:
+  config.yaml: |
+    rules:
+    - seriesQuery: 'http_requests_total{namespace!="",pod!=""}'
+      resources:
+        overrides:
+          namespace:
+            resource: "namespace"
+          pod:
+            resource: "pod"
+      name:
+        matches: "http_requests_total"
+        as: "http_requests_per_second"
+      metricsQuery: 'sum(rate(http_requests_total{<<.LabelMatchers>>}[2m])) by (<<.GroupBy>>)'
+```
+
+## Vertical Pod Autoscaling
+
+### 1. Install VPA
+```bash
+# Add VPA Helm repository
+helm repo add fairwinds-stable https://charts.fairwinds.com/stable
+helm repo update
+
+# Install VPA
+helm install vpa fairwinds-stable/vpa \
+  --namespace kube-system \
+  --set recommender.enabled=true \
+  --set updater.enabled=true \
+  --set admissionController.enabled=true
+```
+
+### 2. Configure VPA
+```yaml
+# vpa-config.yaml
+apiVersion: autoscaling.k8s.io/v1
+kind: VerticalPodAutoscaler
+metadata:
+  name: my-app-vpa
+  namespace: my-app
+spec:
+  targetRef:
+    apiVersion: "apps/v1"
+    kind: Deployment
+    name: my-app
+  updatePolicy:
+    updateMode: "Auto"
+  resourcePolicy:
+    containerPolicies:
+    - containerName: "*"
+      minAllowed:
+        cpu: 100m
+        memory: 50Mi
+      maxAllowed:
+        cpu: 1
+        memory: 500Mi
+      controlledResources: ["cpu", "memory"]
+```
+
+## Monitoring and Alerts
+
+### 1. Configure Prometheus Rules
+```yaml
+# autoscaling-alerts.yaml
+apiVersion: monitoring.coreos.com/v1
+kind: PrometheusRule
+metadata:
+  name: autoscaling-alerts
+  namespace: monitoring
+spec:
+  groups:
+  - name: autoscaling
+    rules:
+    - alert: HighScalingActivity
+      expr: rate(hpa_scaling_events_total[5m]) > 0.1
+      for: 5m
+      labels:
+        severity: warning
+      annotations:
+        summary: High scaling activity detected
+        description: More than 0.1 scaling events per minute for 5 minutes
+    - alert: FailedScaling
+      expr: hpa_scaling_errors_total > 0
+      for: 1m
+      labels:
+        severity: critical
+      annotations:
+        summary: Scaling failures detected
+        description: HPA has failed to scale the deployment
+```
+
+### 2. Create Monitoring Dashboard
+```yaml
+# autoscaling-dashboard.yaml
+apiVersion: integreatly.org/v1alpha1
+kind: GrafanaDashboard
+metadata:
+  name: autoscaling-monitoring
+  namespace: monitoring
+spec:
+  json: |
+    {
+      "dashboard": {
+        "title": "Cross-Region Autoscaling",
+        "panels": [
+          {
+            "title": "Cluster Node Count",
+            "type": "graph",
+            "datasource": "Prometheus",
+            "targets": [
+              {
+                "expr": "kube_node_status_capacity",
+                "legendFormat": "{{node}}"
+              }
+            ]
+          },
+          {
+            "title": "Pod Count",
+            "type": "graph",
+            "datasource": "Prometheus",
+            "targets": [
+              {
+                "expr": "kube_pod_info",
+                "legendFormat": "{{namespace}}"
+              }
+            ]
+          },
+          {
+            "title": "Resource Utilization",
+            "type": "graph",
+            "datasource": "Prometheus",
+            "targets": [
+              {
+                "expr": "sum(rate(container_cpu_usage_seconds_total[5m])) by (namespace)",
+                "legendFormat": "CPU {{namespace}}"
+              },
+              {
+                "expr": "sum(container_memory_usage_bytes) by (namespace)",
+                "legendFormat": "Memory {{namespace}}"
+              }
+            ]
+          }
+        ]
+      }
+    }
+```
+
+## Best Practices
+
+### 1. Autoscaling Configuration
+- Set appropriate thresholds
+- Configure stabilization windows
+- Monitor scaling events
+- Regular review
+- Document changes
+
+### 2. Resource Management
+- Right-size resources
+- Monitor utilization
+- Set limits and requests
+- Regular optimization
+- Document policies
+
+### 3. Cost Optimization
+- Use spot instances
+- Implement scaling policies
+- Monitor costs
+- Regular review
+- Document savings
+
+## Next Steps
+1. Monitor scaling behavior
+2. Optimize thresholds
+3. Implement cost controls
+4. Regular reviews
+5. Documentation