Kubernetes vs ECS vs Fargate: Choosing the Right Container Platform

June 5, 2024 • 5 min read

Kubernetes vs ECS vs Fargate: Choosing the Right Container Platform

Published

June 5, 2024

Reading Time

5 min

Topics

4 Tags

Kubernetes AWS Containers ECS

What You'll Learn

This article breaks down kubernetes vs ecs vs fargate: choosing the right container platform into practical, actionable steps you can implement today.

“Should we use Kubernetes?” is the wrong question.

The right question: “What problem are we solving, and what’s the simplest tool that solves it?”

The Options

AWS ECS (Elastic Container Service)

What it is: AWS’s proprietary container orchestration service.

Best for:

  • Teams already on AWS
  • Simple microservice architectures
  • Teams that want managed infrastructure

Pros:

  • Deep AWS integration (ALB, IAM, CloudWatch, Secrets Manager)
  • Simpler than Kubernetes
  • No control plane to manage
  • Free (you only pay for compute)

Cons:

  • AWS lock-in
  • Less feature-rich than Kubernetes
  • Smaller community and ecosystem

When to choose ECS:

  • You’re on AWS and don’t need Kubernetes features
  • Your team is small (<10 engineers)
  • You want to ship features, not manage infrastructure

AWS Fargate

What it is: Serverless compute for containers (works with ECS or EKS).

Best for:

  • Teams that don’t want to manage servers
  • Variable or unpredictable workloads
  • Startups moving fast

Pros:

  • Zero server management
  • Pay per task (scales to zero)
  • Automatic scaling
  • Great for bursty workloads

Cons:

  • More expensive than EC2 (at scale)
  • Less control over underlying compute
  • Cold start times for scaling from zero

When to choose Fargate:

  • You want simple container deployment
  • Your workload is bursty (batch jobs, scheduled tasks)
  • You’re willing to pay for convenience

Kubernetes (EKS, GKE, AKS, self-managed)

What it is: Open-source container orchestration, runs anywhere.

Best for:

  • Multi-cloud or hybrid cloud strategies
  • Complex applications with advanced requirements
  • Large engineering teams
  • Companies that need portability

Pros:

  • Runs on any cloud (or on-prem)
  • Massive ecosystem (Helm, operators, service meshes)
  • Advanced features (stateful sets, custom resources, auto-scaling)
  • Industry standard

Cons:

  • Complex—steep learning curve
  • Requires dedicated operations expertise
  • Control plane management (even with EKS)
  • More moving parts = more things to break

When to choose Kubernetes:

  • You need multi-cloud portability
  • You have platform/SRE teams to manage it
  • You need advanced scheduling, networking, or storage
  • You’re running >50 microservices

Decision Framework

Step 1: Assess Your Team

Small team (<10 engineers)?
→ Start with ECS + Fargate. Kubernetes is overkill.

Platform/SRE team?
→ Kubernetes makes sense. You have the expertise to operate it.

No ops team?
→ Fargate or managed ECS. Avoid Kubernetes.

Step 2: Assess Your Workload

Stateless web apps?
→ ECS or Fargate is fine.

Stateful applications (databases, queues)?
→ Kubernetes has better primitives (StatefulSets, persistent volumes).

Batch/scheduled jobs?
→ Fargate is cost-effective for sporadic workloads.

Real-time, low-latency?
→ EC2-based ECS or self-managed Kubernetes for maximum control.

Step 3: Assess Your Constraints

Multi-cloud requirement?
→ Kubernetes is the only real option.

AWS-only?
→ ECS is simpler and cheaper.

Budget-conscious?
→ ECS on EC2 is cheapest. Fargate costs ~30% more.

Tight deadline?
→ ECS + Fargate ships fastest.

Real-World Scenarios

Scenario 1: Startup with 5 Engineers

Workload: API, background jobs, database
Choice: ECS + Fargate

Why: Team is small, focus should be on product. Kubernetes is too much overhead.

# ECS task definition (simplified)
{
  "family": "api",
  "networkMode": "awsvpc",
  "cpu": "256",
  "memory": "512",
  "containerDefinitions": [{
    "name": "api",
    "image": "myapp:latest",
    "portMappings": [{
      "containerPort": 8080
    }],
    "environment": [{
      "name": "DB_HOST",
      "value": "mydb.amazonaws.com"
    }]
  }]
}

Deploy with a single command. Focus on features, not infrastructure.

Scenario 2: Mid-Size Company, 50+ Services

Workload: Microservices, some stateful components, multi-region
Choice: EKS (managed Kubernetes)

Why: Complexity justifies Kubernetes. Platform team can manage it. Need advanced routing, service mesh, and multi-region failover.

# Kubernetes deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: api
spec:
  replicas: 3
  selector:
    matchLabels:
      app: api
  template:
    metadata:
      labels:
        app: api
    spec:
      containers:
      - name: api
        image: myapp:latest
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "256Mi"
            cpu: "250m"
          limits:
            memory: "512Mi"
            cpu: "500m"
---
apiVersion: v1
kind: Service
metadata:
  name: api
spec:
  selector:
    app: api
  ports:
  - port: 80
    targetPort: 8080
  type: LoadBalancer

Scenario 3: Enterprise, Multi-Cloud Strategy

Workload: Core services must run on AWS and GCP
Choice: Kubernetes (EKS + GKE)

Why: Portability matters. Kubernetes manifests work on both clouds. Avoid cloud-specific services (like ECS).

Migration Paths

ECS → Kubernetes

You can migrate incrementally:

  1. Deploy Kubernetes alongside ECS
  2. Move one service at a time
  3. Decommission ECS once migration is complete

We’ve done this for multiple clients. Timeline: 3-6 months for 20-30 services.

Fargate → EC2

If costs become an issue:

  1. Benchmark workload cost on Fargate vs EC2
  2. If savings >20%, switch to EC2-based ECS
  3. Use Spot instances for batch workloads (60-90% savings)

EC2 → Fargate

When operational burden > cost savings:

  1. Move non-critical services first (batch jobs, internal tools)
  2. Monitor cost vs. benefit
  3. Migrate core services if ROI is positive

Cost Comparison

Example: Running 10 containers, each needing 1 vCPU, 2GB RAM:

Fargate:
~$0.04 per vCPU-hour + $0.004 per GB-hour
= ~$35/day = ~$1,050/month

ECS on EC2 (t3.large):
t3.large: 2 vCPU, 8GB RAM = $0.0832/hour
5 instances (to run 10 containers) = $300/month

Savings: 70% with EC2

But with EC2, you manage:

  • OS patches
  • Scaling
  • Instance failures

Is $750/month worth your team’s time? Sometimes yes, sometimes no.

The Verdict

Start simple. Kubernetes is not a requirement.

Most teams should start with ECS + Fargate and migrate to Kubernetes only when they hit real limitations.

Red flags that you need Kubernetes:

  • Multi-cloud is a hard requirement
  • You’re running 50+ microservices
  • You need advanced networking (service meshes, complex routing)
  • You have dedicated platform engineers

Red flags you don’t need Kubernetes:

  • Team <20 engineers
  • All workloads are stateless
  • You’re AWS-only
  • “Everyone else is doing it”

Choose the tool that fits your team’s size, skills, and constraints. Not the one with the most hype.

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