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Cloud Native Maturity: Where Organizations Stand in 2022

Cloud Native Kubernetes DevOps Architecture Maturity

Cloud native adoption has progressed significantly in 2022. Let’s assess where organizations stand and what mature cloud native practices look like.

Cloud Native Maturity Model

Level 1: Cloud Hosted

  • Lift and shift migrations
  • VMs in the cloud
  • Traditional architectures

Level 2: Cloud Optimized

  • Using managed services
  • Basic automation
  • Some containerization

Level 3: Cloud Native

  • Microservices architecture
  • Kubernetes orchestration
  • CI/CD pipelines
  • Infrastructure as code

Level 4: Cloud Native Advanced

  • Service mesh
  • GitOps
  • Observability stack
  • Platform engineering

Level 5: Cloud Native Mastery

  • Developer self-service
  • Full automation
  • Chaos engineering
  • FinOps optimization

Assessment Framework

from enum import IntEnum
from dataclasses import dataclass
from typing import Dict, List

class MaturityLevel(IntEnum):
    CLOUD_HOSTED = 1
    CLOUD_OPTIMIZED = 2
    CLOUD_NATIVE = 3
    CLOUD_NATIVE_ADVANCED = 4
    CLOUD_NATIVE_MASTERY = 5

@dataclass
class MaturityDimension:
    name: str
    current_level: MaturityLevel
    practices: Dict[MaturityLevel, str]

def assess_cloud_native_maturity() -> Dict[str, MaturityDimension]:
    dimensions = {
        "infrastructure": MaturityDimension(
            name="Infrastructure",
            current_level=MaturityLevel.CLOUD_HOSTED,
            practices={
                MaturityLevel.CLOUD_HOSTED: "Manual provisioning, VMs",
                MaturityLevel.CLOUD_OPTIMIZED: "Some IaC, managed services",
                MaturityLevel.CLOUD_NATIVE: "Full IaC, containers, Kubernetes",
                MaturityLevel.CLOUD_NATIVE_ADVANCED: "GitOps, policy as code",
                MaturityLevel.CLOUD_NATIVE_MASTERY: "Self-healing, auto-scaling"
            }
        ),
        "application_architecture": MaturityDimension(
            name="Application Architecture",
            current_level=MaturityLevel.CLOUD_HOSTED,
            practices={
                MaturityLevel.CLOUD_HOSTED: "Monoliths",
                MaturityLevel.CLOUD_OPTIMIZED: "Modular monoliths",
                MaturityLevel.CLOUD_NATIVE: "Microservices",
                MaturityLevel.CLOUD_NATIVE_ADVANCED: "Event-driven, serverless",
                MaturityLevel.CLOUD_NATIVE_MASTERY: "Adaptive architectures"
            }
        ),
        "deployment": MaturityDimension(
            name="Deployment",
            current_level=MaturityLevel.CLOUD_HOSTED,
            practices={
                MaturityLevel.CLOUD_HOSTED: "Manual deployments",
                MaturityLevel.CLOUD_OPTIMIZED: "Basic CI/CD",
                MaturityLevel.CLOUD_NATIVE: "Automated pipelines",
                MaturityLevel.CLOUD_NATIVE_ADVANCED: "Progressive delivery",
                MaturityLevel.CLOUD_NATIVE_MASTERY: "Continuous deployment"
            }
        ),
        "observability": MaturityDimension(
            name="Observability",
            current_level=MaturityLevel.CLOUD_HOSTED,
            practices={
                MaturityLevel.CLOUD_HOSTED: "Basic monitoring",
                MaturityLevel.CLOUD_OPTIMIZED: "Centralized logging",
                MaturityLevel.CLOUD_NATIVE: "Metrics, traces, logs",
                MaturityLevel.CLOUD_NATIVE_ADVANCED: "Distributed tracing, SLOs",
                MaturityLevel.CLOUD_NATIVE_MASTERY: "AIOps, predictive"
            }
        ),
        "security": MaturityDimension(
            name="Security",
            current_level=MaturityLevel.CLOUD_HOSTED,
            practices={
                MaturityLevel.CLOUD_HOSTED: "Perimeter security",
                MaturityLevel.CLOUD_OPTIMIZED: "Basic cloud security",
                MaturityLevel.CLOUD_NATIVE: "DevSecOps, scanning",
                MaturityLevel.CLOUD_NATIVE_ADVANCED: "Zero trust, policy enforcement",
                MaturityLevel.CLOUD_NATIVE_MASTERY: "Security as code, auto-remediation"
            }
        )
    }
    return dimensions

Mature Cloud Native Practices

Infrastructure as Code

# Terraform - Mature IaC pattern
module "aks_cluster" {
  source = "./modules/aks"

  cluster_name        = var.cluster_name
  resource_group_name = azurerm_resource_group.main.name
  location            = var.location

  # GitOps configuration
  flux_enabled = true
  flux_repo    = "https://github.com/company/k8s-config"

  # Network configuration
  vnet_subnet_id = module.network.aks_subnet_id
  pod_cidr       = "10.244.0.0/16"
  service_cidr   = "10.0.0.0/16"

  # Node pools
  node_pools = [
    {
      name         = "system"
      node_count   = 3
      vm_size      = "Standard_D4s_v3"
      os_disk_size = 100
      node_labels  = { "nodepool-type" = "system" }
    },
    {
      name         = "workload"
      node_count   = 5
      vm_size      = "Standard_D8s_v3"
      auto_scaling = true
      min_count    = 3
      max_count    = 10
      node_labels  = { "nodepool-type" = "workload" }
    }
  ]

  # Security
  enable_azure_policy     = true
  enable_defender         = true
  enable_workload_identity = true

  tags = var.tags
}

GitOps Deployment

# Flux Kustomization
apiVersion: kustomize.toolkit.fluxcd.io/v1beta2
kind: Kustomization
metadata:
  name: apps
  namespace: flux-system
spec:
  interval: 10m
  sourceRef:
    kind: GitRepository
    name: flux-system
  path: ./apps/production
  prune: true
  healthChecks:
    - apiVersion: apps/v1
      kind: Deployment
      name: frontend
      namespace: production
    - apiVersion: apps/v1
      kind: Deployment
      name: api
      namespace: production
  postBuild:
    substitute:
      cluster_env: production
    substituteFrom:
      - kind: ConfigMap
        name: cluster-config

Progressive Delivery

# Flagger Canary deployment
apiVersion: flagger.app/v1beta1
kind: Canary
metadata:
  name: api
  namespace: production
spec:
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: api
  progressDeadlineSeconds: 60
  service:
    port: 80
    targetPort: 8080
  analysis:
    interval: 1m
    threshold: 5
    maxWeight: 50
    stepWeight: 10
    metrics:
      - name: request-success-rate
        thresholdRange:
          min: 99
        interval: 1m
      - name: request-duration
        thresholdRange:
          max: 500
        interval: 1m
    webhooks:
      - name: load-test
        url: http://loadtester/
        timeout: 5s
        metadata:
          type: cmd
          cmd: "hey -z 1m -q 10 -c 2 http://api.production/"

Observability Stack

# OpenTelemetry Collector configuration
receivers:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318

  prometheus:
    config:
      scrape_configs:
        - job_name: 'kubernetes-pods'
          kubernetes_sd_configs:
            - role: pod

processors:
  batch:
    timeout: 1s
    send_batch_size: 1024

  memory_limiter:
    check_interval: 1s
    limit_mib: 1000

  attributes:
    actions:
      - key: environment
        value: production
        action: insert

exporters:
  azuremonitor:
    connection_string: ${APPLICATIONINSIGHTS_CONNECTION_STRING}

  prometheus:
    endpoint: 0.0.0.0:8889

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [memory_limiter, batch, attributes]
      exporters: [azuremonitor]

    metrics:
      receivers: [otlp, prometheus]
      processors: [memory_limiter, batch]
      exporters: [azuremonitor, prometheus]

Platform Engineering

The emerging discipline of building internal developer platforms:

# Backstage Software Catalog entry
apiVersion: backstage.io/v1alpha1
kind: Component
metadata:
  name: order-service
  description: Handles order processing
  annotations:
    github.com/project-slug: company/order-service
    backstage.io/techdocs-ref: dir:.
    azure.com/application-insights: order-service-prod
spec:
  type: service
  lifecycle: production
  owner: team-commerce
  system: e-commerce
  providesApis:
    - order-api
  consumesApis:
    - inventory-api
    - payment-api
  dependsOn:
    - resource:default/orders-db
    - resource:default/orders-cache
---
apiVersion: backstage.io/v1alpha1
kind: API
metadata:
  name: order-api
  description: Order management API
spec:
  type: openapi
  lifecycle: production
  owner: team-commerce
  definition:
    $text: ./openapi.yaml

Where Most Organizations Are

Based on 2022 observations:

DimensionAverage LevelLeaders
Infrastructure2.54.0
Architecture2.03.5
Deployment2.54.5
Observability2.04.0
Security2.03.5

Path Forward

roadmap = {
    "Q1_2023": [
        "Complete IaC migration",
        "Implement GitOps for core services",
        "Establish SLO framework"
    ],
    "Q2_2023": [
        "Service mesh for critical paths",
        "Progressive delivery adoption",
        "Platform engineering initiative"
    ],
    "Q3_2023": [
        "Developer self-service portal",
        "Full observability stack",
        "Chaos engineering program"
    ],
    "Q4_2023": [
        "FinOps optimization",
        "AIOps integration",
        "Continuous improvement culture"
    ]
}

Conclusion

Cloud native maturity varies widely across organizations. Most are between levels 2-3, with clear opportunities to advance. The key is incremental progress - you don’t need to reach level 5 to see benefits. Focus on the dimensions that matter most for your business.

Resources

Michael John Peña

Michael John Peña

Senior Data Engineer based in Sydney. Writing about data, cloud, and technology.