In this hands-on guide, we'll go from an idea to a published website using modern AI tooling. We'll explore the concept of vibe coding, use Firebase Studio to build the app, deploy it, optionally add a custom domain via CloudMySite, and even set up monitoring and cleanup steps.
This is the full journey — from prompting to production. You can also check the contents of this blog live in below video:
What if you could create a complete, polished advertisement — visuals, voiceover, and full video — all for under $12?
That's exactly what I set out to prove in this project. In this blog post, I'll walk you through:
This tutorial guides you through the process of using Vertex AI to train and deploy an AutoML Image Classification model. You'll use a public flower image dataset, train the model using AutoML, evaluate its performance, deploy it to an endpoint, and send predictions — all from the Google Cloud Console.
First, let's understand what cloud data transfer is and its significance. In today's digital age, many applications are transitioning to the cloud, often resulting in hybrid models wherecomponents may reside on-premises or in cloud environments. This shift necessitates robustdata transfer capabilities to ensure seamless communication between on-premises and cloud components.
Businesses are moving towards cloud services not because they enjoy managing data centers, but because they aim to run their operations more efficiently. Cloud providers specialize in managing data center operations, allowing businesses to focus on their core activities. This fundamental shift underlines the need for ongoing data transfer from onpremises infrastructure to cloud environments.
In the ever-evolving world of technology, one question frequently arises among professionals and businesses alike: which cloud provider is the best fit for my needs? With a plethora of options available, including giants like AWS (Amazon Web Services), Microsoft Azure, and Google Cloud, the decision can seem daunting. This blog aims to shed light on the key differences and strengths of these leading cloud services, helping you navigate the complex landscape of cloud computing.
"Choose wisely: AWS's global reach and vast services, Azure's seamless integration with Microsoft's ecosystem, and Google Cloud's leading data analytics and machine learning capabilities are shaping the future of the cloud, driving innovation, and redefining what's possible in technology."