Quick Guide to Creating a Linux Server on AWS (EC2 Setup for Beginners)

How to Launch a Linux VM on AWS EC2 – A Step-by-Step Guide for Beginners

If you're just getting started with Amazon Web Services (AWS) and want to spin up your first Linux virtual machine (VM), you’re in the right place. In this guide, we'll walk through how to create a Linux VM using Amazon EC2 (Elastic Compute Cloud) — all through the AWS Management Console.

Whether you're testing applications, learning Linux, or just experimenting with AWS cloud computing, this simple walkthrough will help you get your VM up and running quickly.

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🔧 Step 1: Access the EC2 Dashboard

After logging into your AWS Console, you’ll want to head over to the EC2 Dashboard, which is where AWS manages virtual machines (called “instances”).

• If you’ve used EC2 recently, it will show up under “Recently visited” services.

• If not, just type “EC2” into the search bar and click the EC2 Dashboard link.

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🚀 Step 2: Launch a New Instance

Once you're on the EC2 dashboard:

1. Click “Launch Instance”.

2. Give your instance a name — for example, demo-5-12.

3. Choose an Amazon Machine Image (AMI). For this tutorial, we’re going with Amazon Linux 2023, which is optimized for AWS environments.

You can also choose Ubuntu, Windows, or other AMIs, depending on your needs.

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🧮 Step 3: Choose an Instance Type

Select t2.micro — it’s free tier eligible and works perfectly for lightweight use or learning purposes.

Tip: t2.nano is even smaller and still free tier eligible, but t2.micro offers a bit more headroom for experimentation.

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🔑 Step 4: Create a Key Pair

You need a key pair to securely log in to your VM.

• Click Create new key pair.

• Name it something like demo-5-12.

• Download the .pem file when prompted — you’ll need it later for SSH access via terminal or tools like PuTTY.

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🌐 Step 5: Configure Network & Storage

You can accept most defaults, but be sure the following are configured:

• Allow SSH traffic from anywhere (this is usually the default).

• Optional: Check HTTP and HTTPS if you plan to host a web app.

• Storage: 8GB is enough for a test VM, but you can increase it to up to 30GB and still stay in the free tier.

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☁️ Step 6: Launch and Connect to Your Instance

Click “Launch Instance”, and AWS will begin provisioning your VM. It may take a minute to initialize.

To connect:

1. Click on the Instance ID to view details.

2. Click Connect.

3. Use the browser-based SSH client to open a terminal — no extra configuration required!

You’ll be logged in as the ec2-user, and from there you can start running commands, installing packages, and more.

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✅ You’re All Set!

You’ve successfully launched and connected to a Linux VM on AWS! This is a great foundation for learning Linux, experimenting with web hosting, or preparing for AWS certifications.

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🔜 What’s Next?

In upcoming tutorials, we’ll cover:

• How to connect to your EC2 instance using PuTTY

• Installing and configuring software on your Linux VM

• Setting up web servers and deploying applications

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Final Tips:

• Always shut down unused instances to avoid charges.

• Keep your key pairs secure — without them, you can’t access your instances.

• Explore AWS's free tier offerings to experiment risk-free.

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Tags: AWS, EC2, Linux VM, Cloud Computing, Amazon Linux, SSH, AWS Tutorial, Free Tier, Virtual Machine, Cloud Hosting

Google Cloud - How to Set Up a Virtual Machine on Google Cloud (Step-by-...

How to Set Up a Virtual Machine (VM) on Google Cloud: A Beginner-Friendly Guide

Setting up a virtual machine (VM) in the cloud can sound intimidating, but it's actually pretty straightforward—especially with Google Cloud. In this post, I’ll walk you step-by-step through how to spin up a basic VM on Google Cloud, from choosing your machine type to connecting via SSH. This guide is perfect if you’re just getting started or need a refresher.

Step 1: Log into Google Cloud Console

First things first: make sure you have a Google Cloud account. If you already have a Google account, signing up for Google Cloud is pretty seamless.

Once you're in, go to cloud.google.com and click Console in the upper-right corner. This opens up the main dashboard with all the tools Google Cloud offers.

Step 2: Navigate to Compute Engine

To create a VM, head to the Compute Engine section. This is where all virtual machines are managed. Click “Create Instance” to get started.

Step 3: Name Your VM and Select a Region

Start by naming your VM. For this tutorial, I named mine testmachine (note: it must begin with a lowercase letter).

Next, choose the region closest to you or your users—this affects speed and latency. I selected Northern Virginia. You can leave the zone as “automatic” unless you have a specific reason to set it.

Step 4: Choose a Machine Type

Google Cloud offers several categories of VMs:

• General purpose

• Compute optimized

• Memory optimized

• GPU-based

For basic use or learning purposes, stick with General Purpose. I recommend selecting the E2 series and adjusting the machine type to e2-micro, which is very affordable—around $7.99/month, depending on the region and month.

Step 5: Pick an Operating System

Under the “Boot Disk” section, click Change to select your OS. By default, it uses Debian, but I prefer Ubuntu, which is based on Debian and widely supported.

Select Ubuntu Minimal, stick with the default 10GB boot disk (you can increase this later if needed), and click Select.

Step 6: Allow Web Traffic (Optional)

In the Firewall section, check both:

• Allow HTTP traffic

• Allow HTTPS traffic

This is important if you plan to run a web server on your VM.

Step 7: Launch the VM

Scroll down and click Create. Google Cloud will start provisioning your instance. Once it’s ready, you’ll see a green checkmark under the Status column.

Step 8: Connect to Your VM

Click the name of your VM, then click SSH at the top of the details page. This opens a terminal directly in your browser.

Google Cloud automatically handles the SSH keys and authentication for you—no password needed. You’re now connected to your VM!

Step 9: Stop or Delete the VM (To Save Money)

If you're done using the VM, you have two options:

• Stop the VM: Click the Stop button. This halts the machine without deleting it, so you can restart it later.

• Delete the VM: Click the Delete button if you no longer need it.

Bonus Tip: Use Instance Schedules

Google Cloud lets you create Instance Schedules to automatically turn your VM on or off at set times—great for saving money if you only need it during certain hours.

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Final Thoughts

That's it! You now know how to set up a VM on Google Cloud, choose your configuration, connect securely, and manage costs. Whether you're experimenting, developing, or running lightweight applications, this basic setup will get you off the ground quickly.

I'm Dean—thanks for following along. If you found this guide helpful, feel free to share or drop me a line with your questions or feedback.

How to Use ChatGPT to Troubleshoot Any Windows Problem (Fast & Easy!)

How to Use ChatGPT to Troubleshoot Windows Errors

Troubleshooting Windows issues—whether on a personal computer, a work laptop, or even a Windows Server—can be frustrating and time-consuming. You’re often met with cryptic error codes, vague messages, and the tedious task of scouring forums for solutions. But what if you could skip the endless Googling and get focused, actionable help right away?

Enter ChatGPT. In this guide, we'll explore how to use ChatGPT to streamline your Windows troubleshooting process—from analyzing error messages to parsing dump files and event logs.

Why Use ChatGPT for Windows Troubleshooting?

ChatGPT doesn’t replace your role as the troubleshooter—it enhances it. Think of it as your digital assistant that does the heavy lifting: analyzing errors, aggregating solutions, and walking you through the steps to resolve issues.

Whether you're using Windows Home, Pro, or Server editions, ChatGPT can:

• Interpret error messages and event IDs

• Provide command-line instructions for common fixes

• Analyze logs, screenshots, and dump files

• Offer context-aware recommendations based on your feedback

Getting Started: Using ChatGPT to Understand Event Viewer Errors

When diagnosing a problem, your first stop is often the Windows Event Viewer. You might see an error with an event ID like 7011. Instead of manually searching for what it means, simply enter the event ID into ChatGPT:

Prompt: "What does Windows Event ID 7011 mean?"

ChatGPT will respond with:

• A summary of the error

• Common causes

• Recommended troubleshooting steps

• Relevant command-line tools (e.g., running sfc /scannow)

This alone can save you hours of digging through technical forums.

Uploading Logs and Files for Analysis

The power of ChatGPT extends beyond just interpreting text prompts. You can upload various files for deeper analysis:

1. Event Viewer Logs

Save logs from the Event Viewer (Application, System, Security, etc.) and upload them to ChatGPT. The assistant can then analyze the sequence of events and highlight key issues or potential causes.

2. Error Messages from Screenshots

Instead of typing out long error messages, take a screenshot using tools like Snagit or a simple print screen. Upload the image to ChatGPT, and it will extract the text, interpret the error, and suggest next steps.

Tip: Even smartphone pictures of error screens can work if they're clear enough.

3. Memory Dump Files

When Windows crashes, it often generates a memory dump file. These files can be dense and hard to interpret without special software. ChatGPT can read dump files (once uploaded) and provide insights on what might have caused the crash.

Don’t know where the dump files are? Just ask ChatGPT:
Prompt: "Where are Windows dump files stored?"

4. Windows Update Logs

If you're experiencing issues after a recent update, exporting and analyzing the Windows Update log can be very revealing. Don’t know how to create one? ChatGPT can guide you with PowerShell commands to export the update history into a readable text file.

Once uploaded, ChatGPT will review the log, highlight errors or failed updates, and suggest corrective actions.

Keeping the Conversation Organized

When working with ChatGPT, keep these best practices in mind:

• Use separate chats for separate issues. This keeps the troubleshooting process organized and avoids confusion.

• Stay in the same chat thread when following up on a specific problem. ChatGPT retains context within the same session, helping you build on previous steps and feedback.

• Provide feedback and updates. Let ChatGPT know what you've tried, what worked, and what didn’t. This helps refine its advice.

Summary: Turning ChatGPT into Your Troubleshooting Ally

From pinpointing the cause of cryptic errors to analyzing complex log files, ChatGPT can drastically improve your Windows troubleshooting workflow. It acts as a multi-tool for tech support, helping you save time, reduce frustration, and resolve problems with confidence.

Whether you're an IT professional or a tech-savvy home user, integrating ChatGPT into your diagnostic toolkit is a game-changer.