My First AWS S3 Hands-On Experience ☁️

ADHIYA R — Tue, 15 Sep 2026 06:58:24 +0000

As part of my learning journey in Artificial Intelligence and Machine Learning, I recently attended the first session of a hands-on Cloud Computing Workshop.

Since cloud platforms are becoming an important part of deploying and scaling applications, especially in AI/ML, I wanted to get more comfortable working with cloud services rather than limiting my learning to theory.

For the first session, we worked with Amazon S3 (Simple Storage Service) and went through the basic process of creating a bucket, configuring it, uploading an object, and generating a URL to access the object.

🪣 Creating an S3 Bucket

We started with the basic building block of S3 — a bucket.

I created a bucket in the US East (N. Virginia) – us-east-1 region and selected the General purpose bucket type.

While creating the bucket, I got to explore some of the configurations available in S3, including:

Object Ownership
Block Public Access
Bucket Versioning
Tags
Default Encryption

These settings made me realize that creating cloud storage isn't simply about choosing a name and uploading files. There are also important considerations around ownership, access, security, and data management.

The workshop screenshots show the different configurations I went through while creating the bucket.

📤 Uploading an Object

Once the bucket was created, the next step was to upload an object into it.

The upload was completed successfully, and I could see the object listed inside the bucket.

This gave me a clearer understanding of the basic S3 structure:

S3 → Bucket → Object

Instead of thinking of S3 simply as online file storage, I started understanding how AWS organizes and manages objects within buckets.

💻 Uploading My Portfolio

As part of the hands-on activity, I also worked with my personal portfolio website.

I prepared my portfolio as an index.html file and uploaded it to the S3 bucket as an object. This was a simple but useful way to understand how a web file can be stored and accessed using cloud storage.

Instead of just uploading a random file, using my own portfolio made the activity more practical for me because it connected the AWS concepts with something I can actually use for my projects and future work.

This also helped me understand the basic flow of working with a web file in the cloud:

Portfolio → index.html → S3 Bucket → Object URL

🔗 Generating a Predefined URL

The next step was generating a predefined URL for the uploaded object.

The S3 console provides an option to share an object using a predefined URL with a specified validity period. This was an interesting part of the session because it introduced the idea of providing access to a stored object for a limited period rather than treating the entire bucket as publicly accessible.

The screenshot from the session shows the predefined URL configuration and the option to set its validity period.

💡 What I Took Away From the Session

Although this was an introductory S3 exercise, it helped me connect some of the cloud concepts I have studied with an actual AWS environment.

The main things I worked with were:

☁️ Cloud Storage — understanding how S3 stores objects in buckets.

🪣 Buckets & Objects — learning the basic structure used by S3.

🔐 Access & Security — exploring settings such as Block Public Access and Object Ownership.

🔒 Data Protection — getting introduced to default encryption.

🔗 Controlled Access — generating a predefined URL for an uploaded object.

As an AI/ML student, I think understanding these cloud fundamentals is important because building an ML model is only one part of the process. Eventually, models and applications need to store data, access resources, and be deployed in real environments.

🚀 Looking Forward

This was just the first session, but it gave me a good starting point for working with AWS.

I'm looking forward to exploring more cloud services in the upcoming sessions and understanding how these services can fit into real-world AI/ML applications.

One session done, more cloud concepts to explore! ☁️

DEV Community: ADHIYA R

My First AWS S3 Hands-On Experience ☁️