🖥️ Day 3 — Deep Dive into Amazon EC2

Saurabh GuptaSaurabh Gupta
1 min read

What is Amazon EC2?

EC2 (Elastic Compute Cloud) is AWS’s virtual server hosting service. It lets you launch and manage compute instances in the cloud — perfect for apps, websites, ML models, or test environments.

⚙️ Core Concepts You Must Know:

  • AMI (Amazon Machine Image): OS + software config snapshot

  • Instance Types: Pre-defined hardware (CPU, RAM) setups (e.g., t2.micro)

  • Key Pairs: For secure SSH access

  • Security Groups: Firewall rules for instances

  • EBS: Persistent block storage for EC2

🚀 How to Launch an EC2 Instance

  1. Select your AMI (e.g., Amazon Linux, Ubuntu)

  2. Choose an instance type

  3. Configure network, storage, and tagging

  4. Set your security group (open port 22 for SSH)

  5. Launch with your key pair!

💸 EC2 Pricing Options

ModelBest ForOn-DemandShort-term, testing workloadsReservedLong-term, predictable trafficSpotCost-saving batch processingSavings PlanFlexible long-term commitments

✅ EC2 Best Practices

  • Use IAM roles over embedding access keys

  • Enable detailed CloudWatch monitoring

  • Avoid running as root

  • Automate AMI backups

  • Auto Scaling + Elastic Load Balancing for uptime

🔗 Resources

Aws Ec2

Aws Learning

Data Science

Cloud Computing

100daysofcloud

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Written by

Saurabh Gupta
Saurabh Gupta

I'm a highly analytical and results-driven Data Analyst with 2 years of experience extracting actionable insights from complex datasets to drive business decisions. In my previous role at C5i, I specialized in developing dashboards, optimizing data collection processes. While I've enjoyed diving deep into data analysis, I'm now actively upskilling and transitioning my career towards Data Engineering and AI/ML Engineering, with a strong focus on AWS Cloud technologies. I'm passionate about building the robust data pipelines and scalable infrastructure that power advanced analytics and machine learning models. My journey into AWS has already begun, where I'm gaining hands-on experience with services like S3 for data lakes and EC2 for compute. I'm eager to leverage my analytical foundation and growing cloud expertise to contribute to innovative projects, ensuring data is not just understood, but efficiently managed and utilized to build impactful AI/ML solutions."