EC2 vs Lambda vs Fargate: Which AWS Compute Service for Your SaaS?

Quick Answer: Lambda for sporadic workloads ($5-30/month), EC2 for steady traffic ($25-200/month), Fargate for containerized apps without server management ($40-150/month). But here’s why the “best” choice depends on your specific use case.

Why This Decision Actually Matters

Choose the wrong compute service, and you’ll either overpay by 300% or deal with performance issues that kill your user experience. I’ve seen founders spend $800/month on EC2 when Lambda would cost them $40. I’ve also seen developers try to cram everything into Lambda and end up with timeout errors and angry users.

Let’s break down each option so you can make the right call for your SaaS application.

What Each Service Actually Does

EC2: Virtual Servers You Control

Think of EC2 as renting a computer in Amazon’s data center. You pick the size, install whatever you want, and it runs 24/7 until you turn it off.

Best for: Traditional web applications, APIs with steady traffic, databases, anything that needs to run continuously.

Cost model: Pay per hour the server runs (even if idle)

Starting cost: $6-25/month for small instances

Lambda: Code That Runs On-Demand

Lambda runs your code only when triggered. Someone hits your API? Lambda spins up, executes your function, returns a response, then disappears. You pay only for the milliseconds it ran.

Best for: APIs with sporadic traffic, background jobs, scheduled tasks, webhooks, and event-driven workloads.

Cost model: Pay per request and execution time

Starting cost: Often $0-10/month for low traffic

Fargate: Containers Without Server Management

Fargate runs Docker containers but handles all the server management for you. You define your container, AWS runs it, scales it, and you never think about the underlying servers.

Best for: Microservices, containerized applications, teams already using Docker, apps needing precise resource control.

Cost model: Pay for CPU and memory your container uses, per second

Starting cost: $30-50/month for small containers

The Real Cost Breakdown (2026 Pricing)

Let’s compare actual costs for a typical SaaS application handling 100,000 API requests per month.

Lambda Costs

Requests: 100,000 × $0.20 per million = $0.02 Compute time: 100,000 requests × 500ms average × $0.0000166667 per GB-second = $8.33

Total: $8.35/month

But it gets more expensive if:

• Requests are slow (1-2 second execution)
• High memory requirements (>512 MB)
• Constant traffic (Lambda shines with sporadic loads)

EC2 Costs (t4g.small instance)

Instance: 730 hours × $0.0168/hour = $12.26/month Storage (EBS): 20 GB × $0.10 = $2.00/month Data transfer: First 1 GB free, then $0.09/GB

Total: $14-30/month (depending on traffic)

Can handle: 500,000+ requests easily on one instance

Gets cheaper with: Reserved Instances (40% discount), Savings Plans (50% discount)

Fargate Costs (0.25 vCPU, 0.5 GB memory)

vCPU: $0.04048 per vCPU per hour × 730 hours × 0.25 = $7.39 Memory: $0.004445 per GB per hour × 730 hours × 0.5 = $1.62

Total: $9-45/month (depending on container size and running time)

Note: This assumes container runs 24/7. Can be more if you need larger containers.

When to Use Lambda (The Serverless Choice)

Perfect For:

APIs with unpredictable traffic – Black Friday spike? Lambda scales automatically.

Background jobs – Image processing, PDF generation, data transformations

Scheduled tasks – Daily reports, cleanup jobs, data syncing

 Webhooks – Stripe payments, Slack integrations, third-party callbacks

 Event-driven workflows – S3 file uploads trigger processing, DynamoDB changes trigger actions  

Startups testing product-market fit – Pay only for actual usage

Real Example:

A SaaS sending invoice PDFs gets 200 requests/day during business hours, zero at night.

Lambda cost: $5-8/month EC2 cost: $25/month (running 24/7 mostly idle)

Savings: 70% cheaper with Lambda

Lambda Limitations (Deal Breakers):

• 15-minute maximum execution time – Long-running jobs need EC2
• Cold starts – First request after idle period takes 1-3 seconds
• No persistent state – Can’t keep connections open, must reconnect to databases each time
• Package size limits – 250 MB unzipped, 50 MB zipped deployment  
• Not ideal for steady traffic – If requests are constant, EC2 becomes cheaper

Cost Trap:

If your Lambda functions call each other frequently or have high memory requirements (2+ GB), costs explode. Monitor closely.

When to Use EC2 (The Traditional Choice)

Perfect For:

Web applications with steady traffic – Your app serves users 24/7

Databases you manage – PostgreSQL, MySQL, MongoDB on your own server

Long-running processes – Video encoding, ML training, data analytics

WebSocket connections – Real-time chat, live updates, collaborative tools

Legacy applications – Existing apps that aren’t easily refactored for serverless

Predictable workloads – Traffic patterns are consistent and known

Real Example:

A B2B SaaS with 500 active users during business hours, consistent 1,000-2,000 requests/hour.

EC2 cost (t4g.medium with Savings Plan): $12-15/month Lambda cost: $80-120/month (due to constant traffic)

Savings: 85% cheaper with EC2

EC2 Strengths:

Full control – Install anything, configure everything, root access

Persistent connections – Keep database connections pooled, maintain state

No cold starts – Always ready to respond instantly

Cost-effective at scale – With Reserved Instances or Savings Plans, very cheap

No execution time limits – Run processes for hours, days, weeks

EC2 Challenges:

• You manage everything – Updates, security patches, scaling, monitoring
• Runs 24/7 – Pay even when idle (nights, weekends)
• Manual scaling – Need to configure Auto Scaling Groups  
• Longer setup time – More complex than Lambda to get running

Pro Tip:

Start with t4g instances (ARM-based). They’re 40% cheaper than x86 instances and perform great for most SaaS workloads.

When to Use Fargate (The Container Choice)

Perfect For:

Microservices architecture – Multiple small services instead of monolith

Teams using Docker – Already containerized? Fargate is natural fit

Batch processing jobs – Data pipelines, ETL workflows, scheduled processing

APIs with variable load – More control than Lambda, less management than EC2

CI/CD pipelines – Build, test, deploy in containers

Multi-language applications – Different services in Python, Node.js, Go

Real Example:

A SaaS with 3 microservices (API, worker, scheduler) running in containers.

Fargate cost: $60-90/month (all three services) EC2 cost: $40-60/month (but you manage servers) Lambda cost: Not ideal for this architecture

Trade-off: Pay 30-50% more than EC2 but zero server management

Fargate Strengths:

No server management – AWS handles patching, scaling, availability

Precise resource control – Specify exact CPU/memory per container

Easy scaling – Scales containers up/down automatically

Isolated environments – Each container runs independently

Works with ECS and EKS – Flexible orchestration options

Fargate Limitations:

• More expensive than EC2 – Typically 20-40% cost premium
• Less control than EC2 – Can’t SSH into servers, limited customization  
• Learning curve – Need to understand containers and orchestration
• Cold starts exist – When scaling up, containers take 30-60 seconds to start

When Fargate Makes Sense:

If your team already uses Docker and values time over money, Fargate is brilliant. The $20-40/month premium over EC2 is worth it to avoid server management.

The Hybrid Approach (What Smart Teams Actually Do)

Most successful SaaS applications don’t choose one—they use all three strategically:

Architecture Example:

EC2 (t4g.medium): Main web application, handles core traffic

• Cost: $25/month with Savings Plan
• Handles: 80% of user requests, WebSocket connections

Lambda: Background tasks and sporadic workloads

• Image resizing when users upload
• Sending emails (via SES)
• Generating reports on-demand
• Processing webhooks from Stripe
• Cost: $15-30/month

Fargate: Batch processing and data pipelines

• Daily data exports
• ETL jobs running every 6 hours
• Scheduled cleanups
• Cost: $30/month (runs only when needed)

Total infrastructure: $70-85/month for a production SaaS handling 500K+ requests/month

Why this works: Each service does what it’s best at, total cost is optimized.

Decision Framework: Which Should You Choose?

Ask yourself these questions:

Question 1: What’s your traffic pattern?

Sporadic/unpredictable → Lambda Steady 24/7 → EC2 Batch jobs + APIs → Lambda + EC2 hybrid Containerized microservices → Fargate

Question 2: What’s your technical comfort level?

Just want to deploy code, don’t care about servers → Lambda or Fargate Comfortable managing servers and optimizing → EC2 Love Docker, hate server management → Fargate

Question 3: What’s your budget?

$0-50/month → Lambda (if sporadic) or 1 small EC2 $50-200/month → EC2 or EC2 + Lambda hybrid $200+/month → Mix of all three, optimized per workload

Question 4: What are your performance requirements?

Sub-100ms response times required → EC2 (no cold starts) Okay with occasional 1-2 second delays → Lambda Need container-level isolation → Fargate

Question 5: How fast are you growing?

Testing MVP, uncertain growth → Lambda (scales automatically, pay per use) Steady growth, predictable traffic → EC2 with Reserved Instances Rapid scaling, lots of services → Fargate or EKS

Common Mistakes to Avoid

Mistake #1: Using Lambda for everything because “serverless is cool”

• Lambda at high, steady traffic costs 3-5x more than EC2
• Cold starts ruin user experience for user-facing APIs

Mistake #2: Running small EC2 instances at 5% CPU

• You’re paying for 24/7 capacity you don’t need
• Lambda would cost 90% less

Mistake #3: Choosing Fargate without understanding containers

• Adds complexity without benefits if you’re not containerized
• EC2 or Lambda would be simpler

Mistake #4: Not monitoring costs

• Lambda can spike unexpectedly with infinite loops or DDoS
• Set up billing alerts immediately

Mistake #5: Ignoring cold starts on user-facing APIs

• Lambda cold starts take 1-3 seconds
• Users perceive this as “slow” or “broken”
• Use provisioned concurrency ($15-30/month extra) or switch to EC2

The Bottom Line: What Should You Actually Choose?

For Most SaaS Startups (MVP Stage):

Start with Lambda + RDS

• Total cost: $40-80/month
• Minimal management
• Scales automatically
• Switch to EC2 when traffic becomes steady

For Growing SaaS (1,000-10,000 users):

EC2 (1-2 instances) + Lambda for background jobs

• Total cost: $80-150/month
• Better performance
• Lower per-request costs
• Use Auto Scaling for spikes

For Established SaaS (10,000+ users):

Hybrid: EC2 + Lambda + Fargate

• Total cost: $300-1,000+/month
• Each service optimized for its workload
• Reserved Instances for 40% savings
• Complex but cost-efficient

Your Next Steps

1. Audit your current workload – What’s the traffic pattern? Steady or sporadic?
2. Calculate actual costs – Use AWS Pricing Calculator
3. Start small – One compute option, expand as needed
4. Monitor religiously – Set up CloudWatch alarms and AWS Budgets
5. Optimize quarterly – Review Cost Explorer, adjust strategy

�� Not sure which compute option fits your SaaS? Get a free consultation – We’ll analyze your requirements and recommend the most cost-effective solution.