Modern Platform Engineering Tools - The Essential DevOps Stack for 2024

Platform engineering has emerged as a critical discipline that bridges development and operations, focusing on building internal developer platforms (IDPs) that enable teams to ship software faster and more reliably. In this comprehensive guide, we'll explore the cutting-edge tools and practices that define modern platform engineering in 2024.

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Disclaimer: Kubernetes®, Docker®, Terraform®, AWS®, Azure®, Google Cloud®, ArgoCD™, and other product names mentioned in this article are trademarks of their respective owners. All logos and trademarks are used for representation purposes only. No prior copyright or trademark authorization has been obtained. This content is for educational purposes only.

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What is Platform Engineering?

Platform engineering is the discipline of designing and building toolchains and workflows that enable self-service capabilities for software engineering organizations in the cloud-native era. It's about creating "golden paths" that reduce cognitive load while maintaining flexibility.

Core Principles

🎯 Developer Experience First - Reduce friction and complexity
🔄 Self-Service - Enable teams to be autonomous
🔧 Automation - Eliminate manual toil
📊 Observability - Make systems transparent
🔒 Security by Default - Shift left on security

1. Infrastructure as Code (IaC)

Terraform: The Industry Standard

Terraform has become the de facto standard for infrastructure provisioning across multiple cloud providers.

# Modern Terraform with best practices
terraform {
  required_version = ">= 1.6"
  
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
  
  backend "s3" {
    bucket         = "terraform-state-prod"
    key            = "infrastructure/eks-cluster"
    region         = "us-east-1"
    encrypt        = true
    dynamodb_table = "terraform-locks"
  }
}

# VPC Module
module "vpc" {
  source  = "terraform-aws-modules/vpc/aws"
  version = "~> 5.0"

  name = "production-vpc"
  cidr = "10.0.0.0/16"

  azs             = ["us-east-1a", "us-east-1b", "us-east-1c"]
  private_subnets = ["10.0.1.0/24", "10.0.2.0/24", "10.0.3.0/24"]
  public_subnets  = ["10.0.101.0/24", "10.0.102.0/24", "10.0.103.0/24"]

  enable_nat_gateway   = true
  single_nat_gateway   = false
  enable_dns_hostnames = true

  tags = {
    Environment = "production"
    ManagedBy   = "terraform"
  }
}

# EKS Cluster
module "eks" {
  source  = "terraform-aws-modules/eks/aws"
  version = "~> 19.0"

  cluster_name    = "production-eks"
  cluster_version = "1.28"

  vpc_id     = module.vpc.vpc_id
  subnet_ids = module.vpc.private_subnets

  eks_managed_node_groups = {
    general = {
      desired_size = 3
      min_size     = 2
      max_size     = 10

      instance_types = ["t3.large"]
      capacity_type  = "ON_DEMAND"

      labels = {
        workload = "general"
      }
    }
  }

  tags = {
    Environment = "production"
  }
}

Pulumi: Infrastructure as Real Code

For teams preferring general-purpose languages:

import * as aws from "@pulumi/aws";
import * as eks from "@pulumi/eks";

// Create VPC
const vpc = new aws.ec2.Vpc("production-vpc", {
    cidrBlock: "10.0.0.0/16",
    enableDnsHostnames: true,
    tags: { Name: "production-vpc" },
});

// Create EKS Cluster
const cluster = new eks.Cluster("production-eks", {
    vpcId: vpc.id,
    instanceType: "t3.medium",
    desiredCapacity: 3,
    minSize: 2,
    maxSize: 10,
    version: "1.28",
});

export const kubeconfig = cluster.kubeconfig;

OpenTofu: Open-Source Terraform Alternative

With Terraform's license change, OpenTofu has emerged as the open-source alternative:

# Install OpenTofu
brew install opentofu

# Compatible with Terraform syntax
tofu init
tofu plan
tofu apply

2. GitOps: Declarative Infrastructure

ArgoCD: Kubernetes GitOps Leader

apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: production-app
  namespace: argocd
spec:
  project: default
  
  source:
    repoURL: https://github.com/company/k8s-manifests
    targetRevision: main
    path: apps/production
    
    # Helm values
    helm:
      valueFiles:
        - values-production.yaml
      parameters:
        - name: image.tag
          value: "v1.2.3"
  
  destination:
    server: https://kubernetes.default.svc
    namespace: production
  
  syncPolicy:
    automated:
      prune: true
      selfHeal: true
      allowEmpty: false
    
    syncOptions:
      - CreateNamespace=true
      - PruneLast=true
    
    retry:
      limit: 5
      backoff:
        duration: 5s
        factor: 2
        maxDuration: 3m

Flux CD: Alternative GitOps Solution

apiVersion: source.toolkit.fluxcd.io/v1
kind: GitRepository
metadata:
  name: production-repo
  namespace: flux-system
spec:
  interval: 1m
  url: https://github.com/company/k8s-manifests
  ref:
    branch: main
  secretRef:
    name: git-credentials
---
apiVersion: kustomize.toolkit.fluxcd.io/v1
kind: Kustomization
metadata:
  name: production-apps
  namespace: flux-system
spec:
  interval: 10m
  sourceRef:
    kind: GitRepository
    name: production-repo
  path: ./apps/production
  prune: true
  wait: true
  timeout: 5m

3. CI/CD: Modern Pipeline Tools

GitHub Actions: Integrated CI/CD

name: Production Deployment

on:
  push:
    branches: [main]
    tags: ['v*']

env:
  REGISTRY: ghcr.io
  IMAGE_NAME: ${{ github.repository }}

jobs:
  build-and-test:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      packages: write
    
    steps:
      - uses: actions/checkout@v4
      
      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v3
      
      - name: Log in to Container Registry
        uses: docker/login-action@v3
        with:
          registry: ${{ env.REGISTRY }}
          username: ${{ github.actor }}
          password: ${{ secrets.GITHUB_TOKEN }}
      
      - name: Extract metadata
        id: meta
        uses: docker/metadata-action@v5
        with:
          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
          tags: |
            type=ref,event=branch
            type=semver,pattern={{version}}
            type=sha,prefix={{branch}}-
      
      - name: Build and push
        uses: docker/build-push-action@v5
        with:
          context: .
          push: true
          tags: ${{ steps.meta.outputs.tags }}
          labels: ${{ steps.meta.outputs.labels }}
          cache-from: type=gha
          cache-to: type=gha,mode=max
      
      - name: Run tests
        run: |
          docker run --rm ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }} \
            npm test
  
  deploy:
    needs: build-and-test
    runs-on: ubuntu-latest
    if: github.ref == 'refs/heads/main'
    
    steps:
      - name: Update K8s manifests
        run: |
          git clone https://${GITHUB_TOKEN}@github.com/company/k8s-manifests
          cd k8s-manifests
          yq e -i '.spec.template.spec.containers[0].image = "${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}"' \
            apps/production/deployment.yaml
          git add .
          git commit -m "Update image to ${{ github.sha }}"
          git push

Tekton: Kubernetes-Native Pipelines

apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: build-and-deploy
spec:
  params:
    - name: git-url
    - name: image-name
  
  workspaces:
    - name: shared-workspace
  
  tasks:
    - name: fetch-repository
      taskRef:
        name: git-clone
      workspaces:
        - name: output
          workspace: shared-workspace
      params:
        - name: url
          value: $(params.git-url)
    
    - name: build-image
      taskRef:
        name: buildah
      runAfter:
        - fetch-repository
      workspaces:
        - name: source
          workspace: shared-workspace
      params:
        - name: IMAGE
          value: $(params.image-name)
    
    - name: deploy-to-k8s
      taskRef:
        name: kubernetes-actions
      runAfter:
        - build-image
      params:
        - name: script
          value: |
            kubectl set image deployment/app app=$(params.image-name)
            kubectl rollout status deployment/app

4. Service Mesh: Traffic Management

Istio: Feature-Rich Service Mesh

# Virtual Service for Canary Deployment
apiVersion: networking.istio.io/v1beta1
kind: VirtualService
metadata:
  name: reviews-route
spec:
  hosts:
    - reviews
  http:
    - match:
        - headers:
            user-agent:
              regex: ".*Chrome.*"
      route:
        - destination:
            host: reviews
            subset: v2
          weight: 100
    - route:
        - destination:
            host: reviews
            subset: v1
          weight: 90
        - destination:
            host: reviews
            subset: v2
          weight: 10
---
# Destination Rule
apiVersion: networking.istio.io/v1beta1
kind: DestinationRule
metadata:
  name: reviews
spec:
  host: reviews
  trafficPolicy:
    loadBalancer:
      simple: LEAST_REQUEST
  subsets:
    - name: v1
      labels:
        version: v1
    - name: v2
      labels:
        version: v2

Linkerd: Lightweight Alternative

# Linkerd Traffic Split for Canary
apiVersion: split.smi-spec.io/v1alpha1
kind: TrafficSplit
metadata:
  name: api-canary
spec:
  service: api
  backends:
    - service: api-stable
      weight: 90
    - service: api-canary
      weight: 10

5. Observability Stack

The Three Pillars

Metrics → Logs → Traces

Prometheus + Grafana: Metrics

# ServiceMonitor for Prometheus Operator
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: app-metrics
spec:
  selector:
    matchLabels:
      app: myapp
  endpoints:
    - port: metrics
      interval: 30s
      path: /metrics
---
# PrometheusRule for Alerts
apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
  name: app-alerts
spec:
  groups:
    - name: app
      interval: 30s
      rules:
        - alert: HighErrorRate
          expr: |
            rate(http_requests_total{status=~"5.."}[5m]) > 0.05
          for: 5m
          labels:
            severity: critical
          annotations:
            summary: "High error rate detected"
            description: "Error rate is {{ $value | humanizePercentage }}"

Loki: Log Aggregation

# Promtail configuration
clients:
  - url: http://loki:3100/loki/api/v1/push

scrape_configs:
  - job_name: kubernetes-pods
    kubernetes_sd_configs:
      - role: pod
    relabel_configs:
      - source_labels: [__meta_kubernetes_pod_label_app]
        target_label: app
      - source_labels: [__meta_kubernetes_namespace]
        target_label: namespace
    pipeline_stages:
      - docker: {}
      - json:
          expressions:
            level: level
            message: message
      - labels:
          level:

Jaeger/Tempo: Distributed Tracing

# OpenTelemetry Collector
apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-collector-config
data:
  config.yaml: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: 0.0.0.0:4317
          http:
            endpoint: 0.0.0.0:4318
    
    processors:
      batch:
        timeout: 10s
        send_batch_size: 1024
      
      memory_limiter:
        check_interval: 1s
        limit_mib: 512
    
    exporters:
      jaeger:
        endpoint: jaeger:14250
        tls:
          insecure: true
      
      prometheus:
        endpoint: "0.0.0.0:8889"
    
    service:
      pipelines:
        traces:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [jaeger]
        metrics:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [prometheus]

6. Secret Management

HashiCorp Vault

# Vault Kubernetes Auth
path "auth/kubernetes/login" {
  capabilities = ["create", "read"]
}

# Policy for application secrets
path "secret/data/production/app/*" {
  capabilities = ["read", "list"]
}

# Dynamic database credentials
path "database/creds/app-readonly" {
  capabilities = ["read"]
}

External Secrets Operator

apiVersion: external-secrets.io/v1beta1
kind: SecretStore
metadata:
  name: vault-backend
spec:
  provider:
    vault:
      server: "https://vault.company.com"
      path: "secret"
      version: "v2"
      auth:
        kubernetes:
          mountPath: "kubernetes"
          role: "app-role"
---
apiVersion: external-secrets.io/v1beta1
kind: ExternalSecret
metadata:
  name: app-secrets
spec:
  refreshInterval: 1h
  secretStoreRef:
    name: vault-backend
    kind: SecretStore
  target:
    name: app-secrets
    creationPolicy: Owner
  data:
    - secretKey: database-password
      remoteRef:
        key: production/app/database
        property: password

7. Policy as Code

Open Policy Agent (OPA)

package kubernetes.admission

# Deny pods without resource limits
deny[msg] {
  input.request.kind.kind == "Pod"
  container := input.request.object.spec.containers[_]
  not container.resources.limits
  msg := sprintf("Container %v must have resource limits", [container.name])
}

# Require non-root user
deny[msg] {
  input.request.kind.kind == "Pod"
  not input.request.object.spec.securityContext.runAsNonRoot
  msg := "Pods must run as non-root user"
}

# Deny privileged containers
deny[msg] {
  input.request.kind.kind == "Pod"
  container := input.request.object.spec.containers[_]
  container.securityContext.privileged
  msg := sprintf("Container %v cannot run in privileged mode", [container.name])
}

Kyverno: Kubernetes Native Policies

apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: require-labels
spec:
  validationFailureAction: enforce
  rules:
    - name: check-labels
      match:
        any:
          - resources:
              kinds:
                - Pod
      validate:
        message: "Labels 'app' and 'env' are required"
        pattern:
          metadata:
            labels:
              app: "?*"
              env: "?*"
---
apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: add-network-policy
spec:
  rules:
    - name: default-deny
      match:
        any:
          - resources:
              kinds:
                - Namespace
      generate:
        kind: NetworkPolicy
        name: default-deny
        namespace: "{{request.object.metadata.name}}"
        data:
          spec:
            podSelector: {}
            policyTypes:
              - Ingress
              - Egress

8. Cost Management

OpenCost: Kubernetes Cost Monitoring

apiVersion: v1
kind: ConfigMap
metadata:
  name: opencost-config
data:
  default.json: |
    {
      "provider": "aws",
      "description": "AWS Cost Configuration",
      "CPU": "0.031611",
      "spotCPU": "0.006655",
      "RAM": "0.004237",
      "spotRAM": "0.000892",
      "GPU": "0.95",
      "storage": "0.00005479452",
      "zoneNetworkEgress": "0.01",
      "regionNetworkEgress": "0.01",
      "internetNetworkEgress": "0.12"
    }

Kubecost Integration

# Install Kubecost
helm install kubecost kubecost/cost-analyzer \
  --namespace kubecost --create-namespace \
  --set kubecostToken="YOUR_TOKEN"

# View cost allocation
kubectl port-forward -n kubecost svc/kubecost-cost-analyzer 9090:9090

9. Developer Portals

Backstage: Internal Developer Platform

# app-config.yaml
app:
  title: FreeOps Developer Portal
  baseUrl: https://portal.freeops.io

backend:
  baseUrl: https://portal.freeops.io
  cors:
    origin: https://portal.freeops.io
  database:
    client: pg
    connection:
      host: ${POSTGRES_HOST}
      port: ${POSTGRES_PORT}
      user: ${POSTGRES_USER}
      password: ${POSTGRES_PASSWORD}

catalog:
  rules:
    - allow: [Component, System, API, Resource, Location]
  locations:
    - type: url
      target: https://github.com/company/software-catalog/blob/main/catalog-info.yaml

Port: Developer Portal Alternative

# port-entity.yaml
identifier: payment-service
title: Payment Service
blueprint: microservice
properties:
  language: golang
  team: payments
  tier: critical
  lifecycle: production
  runtime: kubernetes
relations:
  dependsOn:
    - postgres-db
    - redis-cache

10. Platform Automation

Crossplane: Universal Control Plane

apiVersion: database.aws.crossplane.io/v1beta1
kind: RDSInstance
metadata:
  name: production-db
spec:
  forProvider:
    region: us-east-1
    dbInstanceClass: db.t3.medium
    masterUsername: admin
    allocatedStorage: 100
    engine: postgres
    engineVersion: "14.7"
    skipFinalSnapshot: false
  writeConnectionSecretToRef:
    name: db-credentials
    namespace: production
  providerConfigRef:
    name: aws-provider

Emerging Tools to Watch

🔥 Kratix - Framework for building platforms
🔥 Score - Workload specification standard
🔥 Dapr - Distributed application runtime
🔥 Telepresence - Local development for K8s
🔥 Garden - Development orchestration
🔥 Tilt - Multi-service development

Building Your Platform Stack

Recommended Starting Stack

┌─────────────────────────────────────┐
│     Developer Portal (Backstage)     │
└─────────────────────────────────────┘
           │
┌─────────────────────────────────────┐
│        GitOps (ArgoCD/Flux)         │
└─────────────────────────────────────┘
           │
┌─────────────────────────────────────┐
│   Kubernetes (EKS/GKE/AKS)         │
│   + Service Mesh (Istio/Linkerd)   │
└─────────────────────────────────────┘
           │
┌─────────────────────────────────────┐
│  Observability (Prometheus/Loki)    │
│  + Tracing (Jaeger/Tempo)           │
└─────────────────────────────────────┘

Conclusion

Platform engineering is about creating paved roads that make the right way the easy way. The tools landscape is rich and constantly evolving, but the principles remain constant:

✅ Automate everything - Reduce manual toil
✅ Self-service - Enable developer autonomy
✅ Observability - Make systems transparent
✅ Security - Shift left on security practices
✅ Standards - Create golden paths
✅ Documentation - Make knowledge accessible

Next Steps

1. Assess current state - Understand pain points
2. Define platform vision - Set clear goals
3. Start small - Pick one area to improve
4. Measure success - Track DORA metrics
5. Iterate - Continuously improve based on feedback

The future of platform engineering is bright, with tools becoming more powerful and accessible. Start building your platform today and empower your teams to ship software faster and more reliably.

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Which platform engineering tools are you excited about? Share your experiences and challenges in the comments!