Amazon ECS vs AWS Fargate: Complete Guide to Launch Types [2026]

If you've ever searched for "ECS vs Fargate," you've been asking the wrong question. You're not alone. This misconception is so common that AWS community forums rank in Google's top results for this topic.

Here's the reality: ECS and Fargate are not competing services. Amazon ECS is a container orchestration service, and Fargate is one of several compute options for running your ECS tasks. The actual comparison you should be making is between ECS launch types: Fargate vs EC2.

Understanding this relationship is critical for making the right container infrastructure decision, one that affects cost, operational burden, and application architecture for years to come. By the end of this guide, you'll understand exactly how ECS and Fargate work together, when to choose EC2 vs Fargate launch types, and have a decision framework to apply to your specific workload.

Why "ECS vs Fargate" Is the Wrong Question

The confusion stems from how AWS markets these services, but the architecture tells a different story. Amazon ECS sits at the orchestration layer. It manages task definitions, service deployments, scaling policies, and service discovery. It decides what containers should run and where.

Fargate, EC2, and the newer ECS Managed Instances are compute options that sit beneath ECS. They answer a different question: how should the containers run? This is an important distinction that changes how you evaluate your options.

Think of it this way: you don't compare your car's steering system to its engine. One controls direction, the other provides power. ECS orchestrates your containers. Fargate (or EC2) runs them.

Understanding the ECS Architecture

Before diving into comparisons, let me walk you through how these components actually fit together. Getting this foundation right will make every subsequent decision clearer.

ECS as the Container Orchestration Layer

Amazon Elastic Container Service (ECS) is a fully managed container orchestration service. It handles the control plane responsibilities: scheduling containers across your compute resources, maintaining desired state, integrating with load balancers, and managing deployments.

ECS itself is free. You pay only for the compute resources that run your containers. This is true whether you choose Fargate, EC2 instances, or the new ECS Managed Instances option.

Launch Types and Capacity Providers Explained

AWS offers two ways to specify compute for your ECS tasks: launch types and capacity providers. Understanding the difference matters for your architecture.

Launch types are the legacy approach. You specify FARGATE or EC2 in your task definition's requiresCompatibilities parameter. This works, but it's less flexible.

Capacity providers are the modern, recommended approach. They offer:

• Better control over resource allocation
• Mixed capacity strategies (e.g., Fargate + Fargate Spot)
• Seamless transitions between compute types
• Support for the newest options like ECS Managed Instances

You can have up to 20 capacity providers in a single strategy. This enables sophisticated deployments like running baseline workloads on reserved EC2 instances while handling traffic spikes with Fargate.

The Real Comparison: EC2 vs Fargate Compute

Now we can frame the actual decision correctly. When running containers on ECS, you choose between:

• Fargate: AWS manages all infrastructure. You specify CPU and memory, and AWS handles provisioning, patching, and scaling.
• EC2 Launch Type: You manage EC2 instances. You control instance types, AMIs, networking, and maintenance.
• ECS Managed Instances: Announced in September 2025, this hybrid option gives you EC2 flexibility with Fargate-like operations.
• External: For on-premises servers via ECS Anywhere (outside the scope of this comparison).

Now that you understand how ECS and Fargate work together, let's deep-dive into each compute option, starting with Fargate.

ECS with Fargate Launch Type

Fargate is the serverless compute option for ECS. When you choose Fargate, AWS handles all infrastructure management: provisioning, patching, scaling, and security updates. Each task runs in its own isolated environment with dedicated compute resources.

This hands-off approach has significant implications for your architecture and operations.

How Fargate Works

With Fargate, you define your container requirements in a task definition, specifying CPU, memory, and container images. AWS takes it from there. There's no cluster of EC2 instances to manage, no AMIs to maintain, no capacity planning to perform.

Each Fargate task runs on a single platform version revision throughout its lifecycle. When AWS releases new platform versions with security patches or feature updates, new tasks automatically use the latest revision. AWS also retires vulnerable tasks automatically when security issues are discovered.

The current recommended platform version is 1.4.0 (use "LATEST" in your configurations). Note that platform version 1.3.0 is scheduled for deprecation on March 2, 2026, with retirement on March 16, 2026.

Fargate Task Specifications and Limits

Fargate requires you to specify CPU and memory at the task level using valid combinations. Here's the complete specification matrix:

Ephemeral storage: 20 GB included by default, configurable up to 200 GB. Additional storage beyond 20 GB incurs extra charges.

Operating systems: Amazon Linux 2, Windows Server 2019 (Full and Core), Windows Server 2022 (Full and Core).

CPU architectures: Linux supports both x86_64 and ARM64 (Graviton). Windows requires x86_64.

Task launch throttling: Burst rate of 100 tasks, sustained rate of 20 tasks per second. The RunTask API is limited to 20 calls per second, with each call capable of launching up to 10 tasks.

Fargate Networking Requirements

All Fargate tasks must use the awsvpc network mode. This isn't optional, and it has important architectural implications.

With awsvpc mode, each task receives its own elastic network interface (ENI) with a private IP address from your VPC subnet. Security groups are applied directly to the task ENI, giving you fine-grained network control at the task level rather than the instance level.

Other networking characteristics:

• Public IP: Optional when using a public subnet
• IPv6: Supported in dual-stack VPCs (tasks receive both IPv4 and IPv6 addresses)
• Container communication: Containers within the same task communicate over localhost
• ENI limit: One ENI per task
• Platform version 1.4.0+: All network traffic flows through the task ENI

Fargate Security Model

Fargate's security model is one of its strongest differentiators. Each task runs in an isolated hardware-virtualized environment, meaning your containers don't share infrastructure with other customers' workloads.

Security restrictions enforced by Fargate:

• No privileged containers: Containers cannot run as privileged or with CAP_SYS_ADMIN/CAP_NET_ADMIN capabilities
• Limited Linux capabilities: Only CAP_SYS_PTRACE can be added (for monitoring tools)
• No host access: No access to the underlying host's file system, devices, or container runtime
• No customer host access: You cannot SSH into or connect to the host running your workloads

Automatic security features:

• Ephemeral storage encryption: All tasks launched after May 28, 2020 have storage encrypted with AES-256
• Optional KMS encryption: Bring your own KMS keys for ephemeral storage on platform version 1.4.0+
• Task-level isolation: CPU, memory, and ephemeral storage are never shared between tasks

This isolation model provides defense in depth against container escape vulnerabilities. Even if an attacker compromises a container, they cannot access host-based resources used by other tasks.

Fargate Spot for Cost Optimization

Fargate Spot runs your tasks on spare AWS compute capacity at up to 70% discount compared to regular Fargate pricing. The trade-off? Your tasks may be interrupted when AWS needs the capacity back.

How interruptions work:

1. AWS sends a 2-minute warning via Amazon EventBridge
2. Your running task receives a SIGTERM signal
3. Your container should handle SIGTERM for graceful shutdown
4. After interruption, ECS can request new Spot capacity from a different Availability Zone

Current limitations:

• Linux only (x86 and ARM architectures)
• Amazon ECS only (not available for EKS on Fargate)
• Not available for Windows containers

Ideal workloads for Fargate Spot:

• Batch processing jobs
• Data processing pipelines
• Development and testing environments
• Stateless applications with retry logic
• Non-critical background jobs

You can mix Fargate and Fargate Spot in the same cluster using capacity provider strategies with weights. This lets you run critical tasks on regular Fargate while cost-optimizing background workloads on Spot.

Now let's examine EC2 launch type for workloads requiring more control.

ECS with EC2 Launch Type

The EC2 launch type puts you in control of the underlying infrastructure. You provision EC2 instances, configure them with the ECS agent, and manage their lifecycle. In return, you get maximum flexibility over instance types, networking, and resource allocation.

Infrastructure Control and Flexibility

With EC2 launch type, you're responsible for:

• Instance provisioning and configuration
• AMI selection and maintenance
• Security patching and updates
• ECS agent and container runtime management
• Capacity planning and scaling

This responsibility comes with corresponding benefits:

• Full instance access: SSH into instances, access the operating system directly
• Custom AMIs: Use specialized images for compliance or performance requirements
• Instance metadata: Access EC2 instance metadata service from containers
• Multiple tasks per instance: Efficiently pack multiple small tasks on larger instances
• All Docker networking modes: Bridge, host, and awsvpc are all supported

GPU and Specialized Workload Support

Fargate does not support GPU workloads. If you need GPU acceleration, EC2 launch type is your only option.

ECS supports a comprehensive range of GPU instance types:

• P-series (general-purpose GPU): p2, p3, p4d, p5
• G-series (graphics-intensive): g3, g4, g5, g6, g6e

ECS provides GPU-optimized AMIs with pre-configured NVIDIA kernel drivers and Docker GPU runtime. In your task definition, you specify GPU requirements using the resourceRequirements field with type GPU.

Use cases enabled by GPU support: machine learning training and inference, high-performance computing, video processing and transcoding, and graphics rendering.

Task Placement Strategies

Fargate does not support task placement strategies or constraints. EC2 launch type gives you fine-grained control over where tasks run.

Placement strategies:

• spread: Distribute tasks across Availability Zones or instances for high availability
• binpack: Minimize the number of instances used (cost optimization)
• random: Place tasks randomly across available instances

Placement constraints:

• distinctInstance: Each task runs on a different instance
• memberOf: Tasks run only on instances matching a specified expression

Practical applications:

• Spread tasks across AZs for fault tolerance
• Target instances with specific attributes (GPU, SSD, particular AZ)
• Optimize resource utilization through binpacking
• Isolate sensitive workloads on dedicated instances

The default strategy for ECS services is spread using attribute:ecs.availability-zone.

EC2 Networking Options

Unlike Fargate's mandatory awsvpc mode, EC2 launch type supports multiple networking configurations:

• awsvpc mode (recommended): Each task gets its own ENI and IP address. Security groups apply at the task level.
• bridge mode: Default Docker bridge network. Containers share the host's network namespace.
• host mode: Containers directly use the host's network stack for maximum performance.

For most use cases, awsvpc mode is preferred because it provides the same security group granularity as Fargate while maintaining EC2's other advantages.

A recent addition to ECS offers a middle ground between Fargate and self-managed EC2.

Amazon ECS Managed Instances: The New Middle Ground

Announced in September 2025, Amazon ECS Managed Instances combines Fargate's operational simplicity with EC2's flexibility. AWS manages the infrastructure while you get access to the full range of EC2 instance types.

What AWS manages for you:

• Instance provisioning and scaling
• Security patching (automated every 14 days, schedulable via EC2 event windows)
• Cost optimization (automatically selects most cost-efficient instances)
• Operating system (runs on Bottlerocket, AWS's purpose-built container OS)

What you get:

• Access to all EC2 instance types, including GPU instances
• EC2 pricing models (Reserved Instances, Savings Plans, Spot)
• More flexibility than Fargate's fixed CPU/memory combinations

Trade-offs:

• Management fee on top of regular EC2 costs
• Less placement control than self-managed EC2
• Does not support task placement strategies

ECS Managed Instances is ideal for teams that want EC2 flexibility without the operational burden, particularly for GPU workloads or when you need specific instance types but don't want to manage the underlying infrastructure.

Now that we've covered all three compute options, let's compare them directly.

Comprehensive Feature Comparison

Here's how EC2 and Fargate launch types compare across key dimensions.

Infrastructure Management Comparison

Networking and Security Comparison

Task Definition and Capabilities

Storage Options Comparison

Storage choices often tie directly to pricing considerations. Let's examine the cost models.

Pricing and Cost Analysis

Understanding the pricing models is essential for making cost-effective decisions. The "right" choice depends heavily on your workload patterns.

Fargate Pricing Model

Fargate uses pure pay-as-you-go pricing. You pay for:

• vCPU hours
• Memory (GB) hours
• Ephemeral storage beyond 20 GB
• Operating system (Windows costs more than Linux)
• CPU architecture (ARM/Graviton is cheaper than x86)

Example pricing (US East, N. Virginia, as of 2026):

• Linux/X86: ~$0.04048 per vCPU-hour, ~$0.004445 per GB-hour
• Linux/ARM (Graviton): ~$0.03239 per vCPU-hour, ~$0.003556 per GB-hour (20% better price-performance)
• Windows: Higher rates than Linux

Billing details:

• Per-second billing with 1-minute minimum (Linux)
• Per-second billing with 5-minute minimum (Windows)
• Duration calculated from container image pull until task termination

EC2 Launch Type Pricing

With EC2 launch type, you pay for EC2 instances whether tasks are running or not. ECS orchestration itself is free.

Pricing options:

• On-Demand: Pay by the second with no commitment
• Reserved Instances: Up to 75% discount with 1- or 3-year commitment
• Savings Plans: Flexible commitment for up to 72% savings
• Spot Instances: Up to 90% discount for interruptible workloads

Total Cost of Ownership Scenarios

The raw compute costs tell only part of the story. Consider these scenarios:

Scenario 1: Variable Workload (Startup/Early Stage) A startup running 10 microservices with unpredictable traffic, scaling from near-zero at night to handling traffic spikes during business hours.

• Fargate advantage: Pay only for actual compute usage. No cost during idle periods.
• EC2 disadvantage: Paying for instances 24/7 with low utilization much of the time.
• Recommendation: Fargate, potentially with Fargate Spot for non-critical services.

Scenario 2: Steady-State High Utilization (Enterprise) An enterprise running 50+ services with consistent 70%+ utilization around the clock.

• EC2 advantage: Reserved Instances or Savings Plans dramatically reduce per-compute costs. High utilization means you're getting value from paid instances.
• Fargate disadvantage: Pay-as-you-go rates are higher than committed EC2 pricing at scale.
• Recommendation: EC2 with Reserved Instances or Savings Plans.

Scenario 3: Batch Processing Nightly data processing jobs running for 4 hours.

• Fargate Spot advantage: 70% discount, no infrastructure to maintain, scale to zero between runs.
• EC2 Spot advantage: Up to 90% discount, but you manage the instances.
• Recommendation: Fargate Spot if operational simplicity matters; EC2 Spot if maximizing savings is the priority.

Don't forget operational costs: The engineer hours spent patching EC2 instances, managing AMIs, and troubleshooting capacity issues have real cost. For many teams, Fargate's higher per-compute cost is offset by lower operational overhead.

Cost Optimization Strategies

• Compute Savings Plans: Up to 50% savings on Fargate with 1- or 3-year commitment
• Fargate Spot: Up to 70% discount for interruptible workloads
• ARM/Graviton: 20% better price-performance for Linux workloads
• Right-sizing: Match task resources to actual requirements (avoid over-provisioning)
• Hybrid capacity: Run baseline on EC2 Reserved Instances, handle spikes with Fargate

For detailed cost comparisons between Fargate and EC2 for your specific workload, use the AWS Fargate vs EC2 Pricing Calculator to model different scenarios.

With pricing understood, let's build a decision framework.

Decision Framework: Choosing the Right Launch Type

Requirements should drive your decision, not company size or vague notions of "control." Here's a systematic approach.

Choose Fargate When

Your workloads fit these criteria:

• Standard CPU and memory requirements (within the 0.25-16 vCPU, 0.5-120 GB range)
• No GPU or specialized hardware requirements
• No need for privileged containers or special Linux capabilities
• Variable or unpredictable traffic patterns
• Emphasis on operational simplicity

Your team situation:

• Limited operations capacity or infrastructure expertise
• Want to focus on application development, not infrastructure management
• Need to move fast with minimal setup

Your business drivers:

• Security isolation is a high priority
• Compliance requirements favor managed services
• Development and testing environments need rapid provisioning
• Applications can scale to zero during idle periods

Choose EC2 Launch Type When

Your workloads require:

• GPU acceleration (ML training, inference, video processing)
• Privileged containers or Docker-in-Docker
• Specific EC2 instance types not available in Fargate
• Host-level resource access
• Task placement control for compliance or performance
• Network modes other than awsvpc (bridge or host)

Your optimization goals:

• Consistently high utilization (70%+) with Reserved Instance savings
• Multiple small tasks efficiently packed on larger instances
• Custom AMIs for compliance or performance requirements
• Instance storage for high-performance local data

Consider ECS Managed Instances When

• You need EC2 instance types (especially GPU) but don't want operational burden
• Fargate's CPU/memory combinations don't fit your requirements
• You want AWS to handle patching and scaling
• You're willing to pay a management fee for reduced operations

Decision Tree

Use this flowchart for quick decision-making:

The decision tree assumes an either/or choice, but hybrid deployments are also valid.

Hybrid Deployments: Using Both Launch Types

A question I get frequently: "Can I use both Fargate and EC2 together in the same cluster?"

Yes, and it's more common than you might think.

How it works: ECS clusters can have multiple capacity providers. You define a capacity provider strategy that specifies which providers to use and in what proportion.

Common hybrid patterns:

1. Baseline + Burst: Run steady-state workloads on EC2 with Reserved Instances. Handle traffic spikes with Fargate. This optimizes cost while maintaining flexibility.

2. Workload-Specific Optimization: GPU workloads on EC2, web services on Fargate. Each workload uses the compute type that fits best.

3. Cost Tiers: Production on Fargate (operational simplicity matters), dev/test on EC2 Spot or Fargate Spot (cost optimization matters).

4. Gradual Migration: Migrating from EC2 to Fargate? Run both during the transition. Shift workloads gradually.

Capacity provider strategy example:

FARGATE: weight 1
FARGATE_SPOT: weight 2

This runs 1/3 of tasks on regular Fargate and 2/3 on Fargate Spot.

Limits to know:

• Maximum 20 capacity providers in a strategy
• At least one provider must have a weight greater than zero
• Only one provider can have a defined base value
• Strategy cannot mix Fargate and Auto Scaling group capacity providers in certain configurations

Whether hybrid or single launch type, you may need to migrate between options as requirements evolve.

Migration Between Launch Types

Requirements change. The good news: all capacity provider migrations are supported.

Supported migrations:

• EC2 Auto Scaling to ECS Managed Instances
• Fargate to ECS Managed Instances
• EC2 to Fargate (and vice versa)
• Any capacity provider to any other capacity provider

Migration requirements:

1. Task definition compatibility: Update requiresCompatibilities to include the target launch type. The task definition must pass validation for the new compute type.
2. Service update: Update your service to use the new capacity provider strategy.
3. Parameter validation: Fargate has restrictions EC2 doesn't (no GPU, no privileged, awsvpc required). Remove unsupported parameters before migrating to Fargate.

Common migration issues:

• Fargate requires awsvpc network mode
• Fargate requires task-level CPU and memory specifications
• GPU resources not available on Fargate
• Privileged container settings fail validation on Fargate

Zero-downtime migration approach:

1. Create a new task definition revision with target compatibility
2. Update the service with the new capacity provider and task definition
3. ECS performs a rolling deployment, replacing old tasks with new
4. Monitor metrics and rollback if needed

Before migrating, be aware of common misconceptions that can derail projects.

Common Misconceptions and Pitfalls

Misconception 1: "ECS and Fargate are alternatives" We've covered this, but it bears repeating. They're layers in the same architecture, not competing services.

Misconception 2: "Fargate is always more expensive" This oversimplification ignores:

• Operational costs of managing EC2 instances
• Utilization rates (Fargate wins at low utilization)
• Fargate Spot and Savings Plans options
• The value of engineering time spent on infrastructure

Pitfall: Not considering operational costs in TCO If your engineers spend 10 hours a month managing ECS EC2 infrastructure, that's real cost. Many teams find Fargate's premium is more than offset by operational savings.

Pitfall: Choosing EC2 for "control" without using that control If you're not using GPU, task placement, or privileged containers, and you're running standard instances with default configurations, you're paying an operations tax for control you're not using. Default to Fargate unless you have specific requirements for EC2 features.

Pitfall: Not leveraging Fargate Spot for appropriate workloads Many teams run all workloads on regular Fargate when batch jobs, dev environments, and stateless services could run on Spot at 70% discount.

Pitfall: Ignoring ECS Managed Instances Since it's new (2025), many architectures don't consider this option. If you need GPU but don't want to manage infrastructure, Managed Instances is worth evaluating.

Conclusion

Let me summarize what we've covered:

1. ECS and Fargate aren't alternatives. ECS is the orchestrator; Fargate and EC2 are compute options within ECS.

2. Choose Fargate for operational simplicity. Zero infrastructure management, per-second billing, strong security isolation. Best for variable workloads and teams wanting to focus on applications rather than infrastructure.

3. Choose EC2 for control and cost optimization at scale. GPU support, task placement, privileged containers, Reserved Instance pricing. Best for steady-state high utilization and specialized requirements.

4. ECS Managed Instances offers a middle ground. EC2 flexibility with managed operations. Evaluate for GPU workloads when you want AWS to handle infrastructure.

5. Hybrid deployments are valid. Mix Fargate and EC2 in the same cluster for workload-specific optimization.

Your next step: Evaluate your workload characteristics using the decision framework above. If you're starting fresh, Fargate is the sensible default. Reach for EC2 only when you have specific requirements that Fargate can't meet.

For hands-on implementation, you might want to explore how to deploy an Application Load Balanced Fargate service with CDK, set up scheduled Fargate tasks for batch processing, or learn how to access containers for debugging with ECS Exec. Understanding task roles vs execution roles is also essential for proper IAM configuration.

If you haven't already made the ECS decision, you might also want to read Amazon ECS vs Amazon EC2 to understand why container orchestration often beats raw EC2 instances.

What questions do you have about choosing between Fargate and EC2 for your workloads? Drop a comment below.