DEV Community: Akash Kumar

Unlock $100K in AWS Credits with AWS Activate

Akash Kumar — Wed, 07 Jan 2026 11:29:15 +0000

For most tech startups, the biggest challenge isn’t the idea, the team, or even the market.

Before product market fit, before revenue, and sometimes even before a public launch, founders are forced to pay for servers, cloud resources, databases, deployments, monitoring etc.

For many early stage startups, this becomes an invisible entry barrier that stops the them before they can begin.

For me even it could have been the same, but thanks to Amazon Web Services (AWS) Activate Program.

This article is written for startup founders across the globe, especially those building in the tech, SaaS, AI, and other such spaces.

I’ll share how AWS startup programs are helping founders break this barrier and how you can claim AWS credits ranging from $1,000 to $100,000 through different startup enabling platforms.

AWS Startup Program

AWS has built one of the strongest startup focused ecosystems in the world. Through AWS Activate, founders can access:

Cloud credits
Technical guidance
Architecture reviews
Training and best practices

Depending on your stage and eligibility, AWS credits can go up to $100,000.

Let’s break this down into three practical paths, starting from the earliest founder stage.

Founders Tier: Get Up to $1,000 in AWS Credits, Open to Everyone

If you’re an early stage founder, solo developer, or just validating an idea, AWS offers a Founders Tier.

Who is this for?

Early stage startups
Early MVP builders
Developers experimenting with products

What you get?

Up to $1,000 in AWS credits
Valid for core AWS services
Enough to build, test, and deploy an MVP

For Founders tier no accelerator or certification from startup enabler is required.

Portfolio Tier: Get Up to $100,000 in AWS Credits

It differs from the Founders Tier offered in the Activate program because here startup needs to be affiliated with an AWS Activate Provider, meaning some kind of seed/VC firm, accelerator, incubator, or other startup-enabling institutions.

Who is this for?

Early stage startups officially incorporated
Early MVP builders
Startups who maintain a working website
Startups affiliated to some kind of seed/VC firm, accelerator, incubator, or other startup-enabling institutions

What you get?

Up to $100,000 in AWS credits
Valid for core AWS services and technical support
Enough to build, test, and deploy production ready application with 2 years initial validity of the credits.

AWS Credits via NVIDIA Inception Program (Global)

The NVIDIA Inception Program is one of the best global opportunities for startups, including Indian startups. You can read more about the program here.

Minimum requirements

You need to provide unique contact information for one developer and one business executive
Email aliases (e.g., info@domain.com) and generic domains (e.g., gmail.com) are not accepted. If your NVIDIA account uses one of these email types, you’ll need to create a new one with the business email that you want to use for your program application
To qualify for membership, your company needs to employ at least one developer
The company needs to maintain a working website
The company should be officially incorporated
The company should be be less than 10 years old

The following types of organizations do not qualify for membership, consulting and outsourced development firms, companies associated with cryptocurrency, cloud service providers, resellers and distributors, public companies.

Once you apply to this program it usually takes 2-5 working days to get a confirmation on selection or rejection.

Once selected, you can apply for AWS credits by navigating to the Benefits section and choosing the credit tier based on your eligibility. Simply select the appropriate credit range and click Request Benefit to submit your application.

To claim AWS credits, make sure you are not using a personal or Gmail account. The email address used for your AWS Builder ID or AWS account must match the same official business email used during your NVIDIA Inception program registration. Mismatched or personal emails may lead to rejection or delays in credit approval

Fill in the additional details required in the application form and once approved the credits will be credited to your linked AWS Account.

Based on my experience, claiming AWS Activate credits is not just about filling out an application it’s about clarity and intent.

The first and most important thing is to be precise about how you plan to use AWS. Any cloud provider(there are others as well in Nvidia Inception Program) wants startups to genuinely build on their platform, not just claim credits and leave. So before applying, make sure you’ve clearly decided that AWS is the cloud you want to build on.

From my personal journey, I’ve been using AWS for the last six years, and today our entire workload runs on AWS. This long-term commitment matters, and it should reflect strongly in your application.

When applying for AWS credits through Nvidia Inception, it’s important to clearly explain:

Which AWS services you plan to use?
How your product depends on these services?
How you plan to scale your usage over time?
How AWS fits into your long-term architecture?
Nvidia libraries, models, services you are more likely to use on AWS.

These questions may appear directly in the application form, or during a review. The more accurately you answer, the stronger is your chance to unlock higher credit tiers.

If you are applying for AWS credits for the first time and have not received any credits before, I strongly recommend starting with a $10,000 credit tier. Once you have an active workload and usage history, you can later apply for a higher credit tier.

These are my personal views and learnings, but they’ve worked well for us. Feel free to reach out if you need any help with setting up AWS, want to collaborate, or just exchange ideas and learnings.

Pathfinder: Your Smart Career Compass – Built in 1 Day with GitHub Copilot!

Akash Kumar — Sun, 19 Jan 2025 10:21:07 +0000

This is a submission for the GitHub Copilot Challenge : Fresh Starts

What I Built

Pathfinder is a comprehensive career transition platform designed for anyone and everyone seeking a fresh start. It guides users to explore career paths suited to their personality, skills, and preferences through an engaging psychometric survey.

The platform also provides tailored career clusters, matching careers, and resources like upskilling programs or educational information.

Demo

You can access the website using this link => : Pathfinder APP

Repo

You can access the complete source code of Pathfinder on GitHub. Feel free to explore, fork, or contribute to the project!

thecodexakash / pathfinder

Pathfinder: Fresh Start for Everyone

Objective

Pathfinder is a web application designed to help anyone discover career paths tailored to their skills, interests, and life circumstances through an engaging psychometric assessment. Whether you're starting fresh, transitioning, or transforming your career, Pathfinder provides actionable insights, resources, and inspiration to guide your journey.

Features & Functionality

1. Psychometric Career Survey

Input: Users answer a series of psychometric questions related to interests, skills, values, and lifestyle preferences.
Output: A personalized report suggesting:
- Career clusters (e.g., technology, education, design).
- Potential industries.
- Actionable plans such as upskilling resources and mentorship programs - coming soon

2. Personalized Career Clusters

Recommend 2–3 career clusters tailored to the user’s survey results.
Provide insights explaining why these careers suit the user.

3. Accessibility and Usability

Mobile-friendly and fully accessible following WCAG guidelines.

Development Workflow

1. Tech Stack

Frontend: Next.js with React and Tailwind CSS.
Hosting: Vercel or Netlify…

View on GitHub

Copilot Experience

GitHub Copilot was instrumental in the development of Pathfinder.
Here’s how I used Copilot:

Survey Logic & State Management:

Generated React components for the psychometric survey.
Autocompleted state management logic using hooks like useState and useReducer.
Assisted in creating and managing a global state store using Zustand for seamless state management across the app.
Simplified the process of designing the overall application screens and connecting them to the store.

API Integration:

Used Copilot to scaffold functions in Next.js for calculating psychometric scores and fetching career recommendations, eliminating the need to create a separate backend API.

Visualizations:

Suggested code for integrating Chart.js to create career cluster graphs.
Accessibility Features:
Debugged accessibility issues with Copilot’s assistance, ensuring WCAG compliance.

Debugging and Code Refactoring:
1. Bug Fixes: Whether it was a broken API call or a frontend rendering issue, Copilot offered suggestions that resolved issues in no time.
2. Code Optimization: Copilot often suggested cleaner, more efficient ways of writing the same code, which helped improve the overall performance of the app.

Time Saved

By using GitHub Copilot, I estimated a 50% reduction in development time. It helped me automate repetitive coding tasks, quickly prototype new features, and debug with ease. As a result, I was able to focus on refining the user experience and integrating innovative features like developing the questions for career survey without wasting time on boilerplate code.

GitHub Models

No, I did not use GitHub Models for this project.

Conclusion

Building Pathfinder has been an exciting and fulfilling journey. This app isn’t just about recommending careers—it’s about giving people, the confidence and resources to take that first step toward a new beginning.

Pathfinder is more than a web app—it’s a lifeline for anyone who feels stuck, unsure, or ready for a change.By combining psychometric insights, personalized career clusters, and actionable resources, Pathfinder makes career transitions less overwhelming. The app offers a guiding hand, helping users find their strengths and navigate toward industries and roles that truly align with their skills and life goals.

Step-by-Step Guide: Migrating Data Between MongoDB Atlas Accounts Easily

Akash Kumar — Fri, 13 Sep 2024 17:48:45 +0000

Introduction

Migrating a MongoDB database between different hosts can be necessary for several reasons, such as moving your local database to a remote server, creating backup copies, or even pulling production data for local testing and development.

Thankfully, MongoDB offers an effortless way to handle this through mongodump and mongorestore, a powerful tool that simplifies the migration process.

Whether you're switching between MongoDB Atlas accounts or moving from a local to a cloud database, this guide will show you how to migrate your data seamlessly in just a few steps.

Step 1: Installing MongoDB Database Tools

MongoDB Database Tools are command-line utilities that help you manage and move data.

Install these tools on your platform to get started.

You can download the tool by clicking here

Step 2: Setting up Environment Variable

Go to the path where the MongoDB Database Tools is installed and the copy the path until the /bin as shown.

Then open the Environment Variables and within the User variable update the path.

Select "PATH", click "Edit" , click "New" => Add path which the mongodb data tools is C:\Program Files\MongoDB\Tools\100\bin and then click on Ok.

Step 3: Dump Data to a Directory

mongodump --uri "SOURCE-CONNECTION-STRING-URI"

'SOURCE-CONNECTION-STRING-URI' is URL you are using to connect your app to MongoDB -- either local something like mongodb://127.0.0.1/someDatabase or can be remote server like mongodb+srv://yourapp:<password>@cluster0.xyz123.mongodb.net/someDatabase

The command will save a dump of your entire database into a folder and in the directory where the command was run.

Step 4: Restore Data from Directory

mongorestore --uri "DESTINATION-CONNECTION-STRING-URI"

Run the above command in the same folder where the dump was created and that's it.

Conclusion

In conclusion, this short tutorial showcased how easily data can be transferred between MongoDB instances using mongodump and mongorestore.

With these easy steps, you can quickly back up and restore your data with no hassle.

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Complete Guide on Next.js Deployment on AWS Elastic Beanstalk: Using-Docker, AWS CodePipeline & CodeBuild

Akash Kumar — Thu, 12 Sep 2024 10:33:12 +0000

Introduction

Deploying a Next.js web application to production can be streamlined and efficient when leveraging AWS (Amazon Web Services) Elastic Beanstalk, Docker, and CI/CD pipelines with AWS Code Build, Code Deploy, and GitLab. This guide will walk you through setting up a modern deployment pipeline to ensure your app is robust, scalable, and easy to maintain.

Prerequisites

Before diving into the deployment process, ensure you have:

An AWS root account or an IAM account with permission to create Elastic Beanstalk environments within AWS
Docker installed on your local machine
GitLab or GitHub account with a repository for your Next.js app
A Next.js project that is ready for deployment

Step 1: Set Up AWS Elastic Beanstalk

Create an Elastic Beanstalk Environment - Log in to the AWS Management Console, navigate to Elastic Beanstalk, and create a new application.

Enter your application name and click on Create.
After you have created the application, it is now time to create the New Environment. Click on Create new environment.

Choose Web server environment. The environment name will have the suffix env along with your application name, and you can edit it if desired.

Enter the valid environment name along with the domain. Enter the domain name .

Choose the appropriate platform. In this case, we will choose Managed Platform and Docker as the platform.

In application code, choose Sample Application since we will be deploying our own code through AWS Code Pipeline.
In presets you can leave it to default, however, for production applications, it is advisable to use the High availability instance. Once you have selected the preset click on Next.
Create or use your existing service role. It is important to have Elastic Beanstalk service role along with EC2 service role setup before proceeding with the EC2 instance creation.
However, if you wish to SSH into the EC2 instance from your terminal, add an EC2 key pair, and create an EC2 instance profile to perform the necessary operations.

Choose your VPC in which you want to deploy your EC2 instance.

After selecting the VPC, choose the subnet in each Availability Zone. To run your load balancer and instances in the same public subnets, assign public IP addresses to the instances as shown in the image.

Since, we do not need to configure a database, we can continue to the next step by clicking on Next.
For root volume, we will choose General Purpose SSD.
Now, from the security group, you can either select from an already existing security group or leave it as it is, and Elastic Beanstalk will create one for you while setting up the EC2 instance.
If deploying for production purposes, it is always advisable to configure autoscaling and select the type of instance that the Elastic Beanstalk will create to serve the traffic. We will go with the t3 family.

Click on Next.
In health reporting, we will go with the Basic reporting, but feel free to choose from the available options based on the type of report you need.
We will also uncheck the Managed platform updates as it is not required for the demo website.
Keep rest of the settings as it is and click on Next.
Finally, review your changes and click on Submit.
Elastic Beanstalk will launch your environment, and it will take some time.

After a successful launch, you will see congratulations screen.

Step 2: Create your Next.js app (or use an existing one)

To create a Next.js app, open your terminal, cd into the directory you would like to create the app in, and run the following command:


npx create-next-app@latest nextjs-blog --use-npm --example "https://github.com/vercel/next-learn/tree/main/basics/learn-starter"

If you already have your existing code ready you may skip to the next part

You now have a new directory called nextjs-blog. Let us cd into it:


cd nextjs-blog

Then, run the following command:


npm run dev

This starts your Next.js app’s "development server" (more on this later) on port 3000.

Let's check to see if it is working. Open http://localhost:3000 in your browser.

Now it is time to create a Dockerfile within the application.
Create a file named Dockerfile in the root of your application and add the following code:


FROM node:18-alpine 

RUN mkdir -p /app 

WORKDIR /app 

COPY . . 

RUN npm install 

RUN npm run build 

EXPOSE 3000 

CMD ["npm", "start"]

After making the changes, it is important to check if the build is successful. Start the docker engine and run the following command:


docker build -t testapp .

Once the build is successful, then run the application with the command below:


docker run -p 3000:3000 testapp

Create a file named buildspec.yml in the root of your application and add the following code. This file will be used at a later stage when setting up the code pipeline within AWS.


version: 0.2 

artifacts: 

  type: zip 

  files: 

    - '**/*'

After adding these files to your new or existing code, push these changes to the remote repository on Gitlab or GitHub.

Step 3: Setup Code Pipeline

Log in to the AWS Management Console, navigate to Code Pipeline, and click on create pipeline.
Enter a valid Pipeline name and choose the execution mode for the pipeline. In our case, we will select Queued (Pipeline type V2 required).
Create a new service role if it does not already exist or select from existing service role and click Next.

From the source provider select where you have your artifacts stored. We will select "Gitlab".
From the connection list, select an existing connection or create a new connection.

Once the connection is successful, then select the Repository name and the branch from which the code will be used.
For trigger type, we will choose No filter and click on Next.

Next, we select the Build Provider. In our case, we will select AWS Code Build. Select region or leave it to default AWS Region.

Then create a new project in Code Build by clicking on Create project. This will open a new window. Enter the project name and leave everything inside the Environment as default.

When specifying the build specification, make sure you select Use buildspec file. This is the same file that we created earlier. Leave other settings as default and move to the next step.

When you click on Continue to Code pipeline the window will automatically close and take you back to the code pipeline screen.
Specify the build type as single build and click on Next.

In add deploy stage, select the deploy provider. In this case, it will be AWS Elastic Beanstalk where we want the application to be finally deployed.

Select the application name, environment name, configure rollback settings and click on Next. Review you Code pipeline settings and click on Create Pipeline.

Step 4: Website is Live!

Deploying Next.js web application to production is really easy and can de done more efficiently with AWS Elastic Beanstalk, Docker, and CI/CD pipelines using AWS Code Build, Code Deploy, and GitLab.

You can access it using the URL provided by Elastic Beanstalk. Make changes locally and it will automatically get deployed when you push to your branch.

Happy Coding!!

If you found this helpful, please like this post and follow for more useful tips!.

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