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Ikoh Sylva
Ikoh Sylva

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Monitoring Containers on AWS ECS with CloudWatch

One of the biggest realizations I had during my cloud engineering journey was this:

Deploying an application is only half the job.

The other half?

  • Monitoring it.

  • Understanding how it behaves under load.

  • Knowing when something is wrong before users complain.

Because in real-world cloud environments, applications are constantly consuming resources, handling requests, and responding to changing traffic patterns. If you’re not monitoring them properly, you’re essentially operating blind.

That’s exactly what this hands-on project aims to help us understand.

In this guide, I’ll walk you through how I monitored containerized workloads running on Amazon ECS, configured task resource settings, and visualized metrics using Amazon CloudWatch dashboards.

Image of AWS ECS dashboard

What we’ll Be Building

In this project, we will:

  • Deploy a containerized application on ECS

  • Configure CPU and memory allocation in the task definition

  • Monitor resource usage using CloudWatch

  • Build a dashboard with CPU and memory widgets

  • Simulate load to observe metric changes in real time

By the end, you’ll understand how to move from simply running containers to actually observing and managing them effectively.

Why Monitoring Matters

Imagine deploying an application that suddenly:

  • Runs out of memory

  • Uses excessive CPU

  • Becomes slow under traffic spikes

Without monitoring:

  • You won’t know why performance dropped

  • Troubleshooting becomes difficult

  • Downtime becomes more likely

With monitoring:

  • You gain visibility

  • You can detect issues early

  • You make informed scaling decisions

This is why observability is such a huge part of modern DevOps and Cloud Engineering.

Architecture Overview

Users
   |
   v
Amazon ECS Cluster
   |
Running ECS Service
   |
Task Definition
(CPU + Memory Allocation)
   |
CloudWatch Metrics & Dashboard
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Step 1: ECS Cluster and Running Service

The first step was deploying a containerized application on ECS.

The deployment included:

  • An ECS Cluster

  • A Running ECS Service

  • Active ECS Tasks

This is the foundation where your application runs.

Step 2: Configure Task Definition Resources

One thing beginners often overlook is this:
Containers don’t have unlimited resources.

When creating the ECS task definition, I configured:

  • CPU allocation

  • Memory allocation

Example:

  • CPU: 512

  • Memory: 1024 MiB

Why This Matters

Resource allocation helps:

  • Prevent resource exhaustion

  • Improve application stability

  • Optimize cloud costs

  • Define scaling expectations

This is how cloud platforms control workload behavior.

Step 3: Monitoring with CloudWatch

Now comes the exciting part.

Once the ECS service was running, AWS automatically started sending metrics to CloudWatch.

I created a dashboard showing:

  • CPU utilization

  • Memory utilization

These widgets provided real-time visibility into how the container was behaving.

Image of AWS analytics dashboard

Creating the Dashboard

  1. Go to CloudWatch

  2. Navigate to Dashboards

  3. Create Dashboard

  4. Add Widgets:

  • ECS CPU Utilization

  • ECS Memory Utilization

What These Metrics Tell You

CPU Utilization

Shows how much processing power the container is using.

High CPU may indicate:

  • Heavy traffic

  • Inefficient code

  • Need for scaling

Memory Utilization

Shows RAM consumption.

High memory usage may indicate:

  • Memory leaks

  • Insufficient allocation

  • Application instability risks

Simulate Load

This was one of the most interesting parts.

To see real metric changes, I simulated load against the application using repeated browser refreshes or lightweight testing tools.

And suddenly:

  • CPU usage increased

  • Memory usage shifted

Watching the graphs move in real time made everything feel much more practical.

Why Simulating Load Is Important

This helps you understand:

  • How applications behave under pressure

  • When scaling might be needed

  • How monitoring tools detect changes

Common Mistakes Beginners Make

  1. Ignoring Resource Limits
    Containers can crash if memory is exhausted.

  2. Not Monitoring Applications
    You can’t fix what you can’t see.

  3. Misinterpreting Metrics
    Temporary spikes are normal patterns matter more.

What This Project Really Teaches

At first glance, this might seem like:

“Just another ECS deployment.”

But it’s actually teaching something deeper:

  • Operational visibility

  • Resource management

  • Observability fundamentals

  • Performance awareness

One of the most important transitions in cloud engineering is moving from:

“My application is running” to “I understand how my application is performing.”

That’s where monitoring changes everything.

This project helped reinforce that cloud engineering isn’t only about infrastructure it’s also about visibility, reliability, and operational intelligence.

And honestly? That’s where things start getting really interesting.

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I’m also excited to share that I’ve been able to secure a special discount, in partnership with Sanjeev Kumar’s team, for the DevOps & Cloud Job Placement / Mentorship Program.

For those who may not be familiar, Sanjeev Kumar brings over 20 years of hands-on experience across multiple domains and every phase of product delivery. He is known for his strong architectural mindset, with a deep focus on Automation, DevOps, Cloud, and Security.

Sanjeev has extensive expertise in technology assessment, working closely with senior leadership, architects, and diverse software delivery teams to build scalable and secure systems. Beyond industry practice, he is also an active educator, running a YouTube channel dedicated to helping professionals successfully transition into DevOps and Cloud careers.

This is a great opportunity for anyone looking to level up their DevOps/Cloud skills with real-world mentorship and career guidance.

Do refer below for the link with a dedicated discount automatically applied at checkout;

DevOps & Cloud Job Placement / Mentorship Program.

If you also found this interesting and would love to take the next steps in the application process with AltSchool Africa do use my referral link below;

Apply here or use this Code: W2jBG8 during the registration process and by so doing, you will be supporting me and also getting a discount!

Special Offer: By signing up through the link and using the code shared, you’ll receive a 10% discount!

Don’t miss out on this opportunity to transform your future and also save while doing it! Let’s grow together in the tech space. Also feel free to reach out if you need assistance or clarity regarding the program.

I’m Ikoh Sylva, a passionate cloud computing enthusiast with hands-on experience in AWS. I’m documenting my cloud journey here from a beginner’s perspective, aiming to inspire others along the way.

If you find my contents helpful, please like and follow my posts, and consider sharing this article with anyone starting their own cloud journey.

Let’s connect on social media. I’d love to engage and exchange ideas with you!

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