How I Quickly Built a Hit Counter for My Portfolio Website Using Serverless Technology

As a developer, I’m always on the lookout for new technologies to learn and experiment with. Recently, I came across a YouTube video by Piyush Garg about serverless computing and Amazon Lambda. Intrigued by the concept, I decided to dive in and create a hit counter for my portfolio website (Github link) as a learning project.

Step 1: Getting Started with Amazon Lambda

The idea of serverless computing fascinated me. The notion of running code without having to manage servers sounded like a perfect solution for my hit counter project. I followed the video tutorial to get a basic understanding of how Lambda works.

Step 2: Choosing the Right Database

Next, I needed a database to store the hit counter data. The challenge was to ensure that the performance wouldn’t be affected by opening a new connection every time the Lambda function was called. After some research and suggestions from Stack Overflow, I decided to use Amazon DynamoDB, a key-value database that I had never worked with before. I found another quick YouTube video to get up to speed with DynamoDB.

Step 3: Creating the DynamoDB Table and Lambda Function

With my new knowledge, I created a table in DynamoDB. I then turned to ChatGPT for help in writing the Lambda function. Initially, I considered writing it in Java, but after some advice, I realized that NodeJS or Python would be more suitable. Despite only knowing the basics of both languages, I managed to write the function and configure the API Gateway and IAM roles, learning everything on the fly.

Step 4: Integrating the API with My Portfolio Website

With the API ready, my next challenge was to integrate it with my static portfolio website. Since I’m not very familiar with frontend development, I uploaded my index.html and styles.css files and asked ChatGPT to add the counter.

Step 5: Resolving CORS Issues

I encountered a CORS error while trying to fetch data from my API. Once again, ChatGPT came to the rescue, guiding me through the necessary steps to configure CORS in API Gateway and update my Lambda function to handle OPTIONS requests properly.

Conclusion

In less than two hours, I had successfully implemented a hit counter on my portolio website, learning a multitude of new topics along the way. This project was a testament to how powerful generative AI tools like ChatGPT can be in boosting productivity and enabling developers to deliver solutions at lightning speed.

Key Takeaways

? Serverless Technology: Amazon Lambda simplifies running code without managing servers.

? Database Choice: Amazon DynamoDB is a great option for scalable, low-latency key-value storage.

? Generative AI: Tools like ChatGPT can significantly accelerate learning and development processes.

This experience has reinforced my belief in the potential of AI to transform the way we develop software. I look forward to exploring more technologies and sharing my learnings with the community.

Final Result: