☁️ My AWS Cloud Workshop Journey: From Cloud Basics to Deploying My Portfolio
Cloud computing has become an important part of modern software development, and as an AI/ML student, I wanted to gain practical exposure to how cloud technologies are used in real-world applications.
Recently, I attended an AWS Cloud Workshop that gave me both theoretical knowledge and hands-on experience with AWS services.
☁️ Understanding Cloud Computing
The workshop began with the fundamentals of cloud computing and how organizations can use cloud infrastructure instead of maintaining physical servers.
I learned about different cloud service models:
IaaS – Infrastructure as a Service
PaaS – Platform as a Service
CaaS – Containers as a Service
FaaS – Function as a Service
SaaS – Software as a Service
AIaaS – AI as a Service
Understanding these models helped me see how cloud platforms provide different levels of infrastructure and services depending on application requirements.
🤖 AI as a Service
As an AI/ML student, AIaaS was particularly interesting to me.
AIaaS allows developers and organizations to use AI capabilities through cloud services without having to build and maintain the entire AI infrastructure themselves.
This can be useful for applications involving machine learning, generative AI, computer vision, natural language processing, and other AI workloads.
🔐 Learning About AWS IAM
Another important concept I learned was AWS IAM (Identity and Access Management).
IAM helps control:
- Who can access AWS resources
- What resources they can access
- What actions they are allowed to perform
I also understood the importance of following security practices such as protecting root-user credentials and giving users only the permissions they actually need.
Exploring Amazon S3
One of the major AWS services I explored was Amazon S3 (Simple Storage Service).
S3 is an object storage service that can be used to store:
- Images
- Videos
- Documents
- Datasets
- Backups
- Website files
I learned about S3 buckets, objects, Block Public Access, versioning, tags, and presigned URLs.
🔄 S3 Versioning
S3 Versioning allows multiple versions of an object to be maintained. This can be useful when files are accidentally overwritten or deleted.
🔗 Presigned URLs
I also learned about presigned URLs, which can provide temporary access to private S3 objects without making the entire bucket publicly accessible.
🚀 My Hands-on Project – Portfolio Deployment
The most exciting part of the workshop was applying what I learned.
I created my personal portfolio website and deployed it using AWS.
First, I used Amazon S3 to store and host my portfolio files. Then, I integrated Amazon CloudFront to deliver the website through a CDN.
🌐 Deployment Architecture
Personal Portfolio
↓
Amazon S3
↓
Amazon CloudFront
↓
Users
This hands-on implementation helped me understand the complete process of taking a website from development to cloud deployment.
Instead of running the portfolio only on my local machine, I was able to make it accessible through AWS infrastructure.
💡 Key Takeaways
This workshop helped me gain both conceptual and practical knowledge of:
- ☁️ Cloud Computing
- AWS fundamentals
- IaaS, PaaS, CaaS, FaaS & SaaS
- AI as a Service
- 🔐 IAM and cloud security
- 🪣 Amazon S3
- 🔄 S3 Versioning
- 🔗 Presigned URLs
- 🌐 Amazon CloudFront
- 🚀 Website deployment on AWS
🎯 Final Thoughts
The workshop was a valuable learning experience because it wasn't limited to just understanding AWS concepts. I was able to build something and deploy it using AWS services.
Deploying my own portfolio with Amazon S3 and CloudFront gave me a better understanding of how cloud technologies can be used in real-world web applications.
This experience has motivated me to explore more AWS services and eventually integrate cloud computing with my AI/ML projects.
This is just the beginning of my AWS journey. ☁️🚀
Top comments (0)