Yash Vishwakarma’s Post

🚀 What is AWS Lambda? (In simple terms) Imagine running your code without worrying about servers at all 🤯 That’s exactly what AWS Lambda does. 👉 It is a serverless compute service where: You don’t manage servers You don’t worry about scaling You only pay for what you use 💡 How it works: An event triggers your function → Lambda runs your code → returns the result 📌 Real-world example: When a user uploads an image to S3 → Lambda automatically resizes it → stores the optimized image 🔥 Why developers love it: ✔ No infrastructure management ✔ Auto scaling ✔ Cost-efficient ✔ Easy integration with AWS services 👉 Focus on your logic, AWS handles the rest. 💭 Once you understand Lambda, you’ll never look at backend the same way again. #AWS #Lambda #Serverless #CloudComputing #DevOps #TechSimplified #LearningInPublic

🚀 Understanding Terraform Made Simple! If you’re getting started with Infrastructure as Code (IaC), this flow makes Terraform super easy to grasp 👇 🔹 Terraform Workflow in 5 Simple Steps: 1️⃣ Write (.tf files) Define your desired infrastructure (servers, networks, storage). 2️⃣ Init (terraform init) Initialize the working directory, download providers, and configure backend. 3️⃣ Plan (terraform plan) Preview what Terraform will create, update, or destroy before making changes. 4️⃣ Apply (terraform apply) Provision or update your infrastructure in real environments (AWS, Azure, GCP, etc.). 5️⃣ Destroy (terraform destroy) Clean up resources when they’re no longer needed. 💡 Key Concept: Terraform uses a state file (.tfstate) to track your infrastructure and ensure consistency between configuration and real-world resources. 🔥 Why Terraform? ✔️ Automates infrastructure ✔️ Ensures consistency ✔️ Enables scalability ✔️ Supports multi-cloud environments 👉 In short: Write → Init → Plan → Apply → Destroy Simple, Powerful, and Reproducible! #DevOps #Terraform #CloudComputing #InfrastructureAsCode #AWS #Azure #GCP #Automation #Kubernetes #Learning

Amazon Machine Image (AMI) – Backup And Scalable Server Setup In AWS 🚀 Today I Explored Amazon Machine Image (AMI) And How It Helps In Creating Scalable And Reliable Infrastructure In AWS. 🔹 What Is AMI? An AMI Is A Pre-Configured Template (Blueprint) Used To Launch EC2 Instances. It Includes OS, Applications, And Configurations, Allowing You To Create Identical Servers Easily. 🔧 Two Important EC2 Options I Learned: 1] Launch More Like This Copies Configuration (Instance Type, Security Group, IAM, VPC, Etc.) Does NOT Copy Installed Apps Or Data Best For Quickly Creating Similar Servers 2] Create Image (AMI) Creates A Full Snapshot Of The Instance Includes OS, Installed Software, Files, And Configurations Best For Backup, Disaster Recovery, And Cloning 📌 Key Difference: Launch More Like This = Same Configuration, Fresh Server Create Image (AMI) = Exact Copy Of Server (Data + Setup) 💡 Hands-On Learnings: ✔ Launched Multiple EC2 Instances Using User Data Script (Nginx Setup) ✔ Verified All Instances Running Same Web Page Using Public IPs (As Shown In Page 8) ✔ Created AMI From Existing Instance And Launched Identical Server ✔ Shared AMI With Another AWS Account Using Permissions ✔ Learned AMI Works Using EBS Snapshots For Full Backup ⚠️ Important Tip: Always Deregister Unused AMIs And Delete Associated Snapshots To Avoid Unnecessary AWS Costs (Highlighted On Page 23). Big Thanks To My Mentor Trupti Mane For Continuous Guidance 🙌 #AWS #EC2 #AMI #DevOps #CloudComputing #LearningJourney #AWSBeginner

𝗔𝗪𝗦 𝗟𝗮𝗺𝗯𝗱𝗮 𝘁𝘂𝗿𝗻𝗲𝗱 𝘀𝗲𝗿𝘃𝗲𝗿𝘀 𝗶𝗻𝘁𝗼 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀 At Amazon Web Services (AWS), infrastructure doesn’t always mean servers. Sometimes, it’s just code that runs when needed. That changes how applications are built. Without serverless: • teams manage idle infrastructure • scaling requires planning • costs grow with unused resources With AWS Lambda, teams run 𝗲𝘃𝗲𝗻𝘁-𝗱𝗿𝗶𝘃𝗲𝗻 𝗰𝗼𝗱𝗲 𝘁𝗵𝗮𝘁 𝘀𝗰𝗮𝗹𝗲𝘀 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰𝗮𝗹𝗹𝘆. The DevOps lesson: 𝗗𝗼𝗻’𝘁 𝗺𝗮𝗻𝗮𝗴𝗲 𝘀𝗲𝗿𝘃𝗲𝗿𝘀. 𝗠𝗮𝗻𝗮𝗴𝗲 𝗲𝘃𝗲𝗻𝘁𝘀. When compute becomes on-demand, you only pay for what you use. At ServerScribe, we help teams design architectures that scale automatically — without operational overhead. Are you still managing servers — or building serverless systems? 👇 #DevOps #ServerScribe #AWSLambda #Serverless #CloudComputing #SRE #Scalability

Just built a simple but powerful AWS project 🚀 Automated backup system using Amazon S3 + AWS Lambda + SNS — where every file upload is validated and instantly notifies via email 📩 Loved working with serverless architecture and seeing everything run automatically without managing servers. Small project, big learning 💡 #AWS #CloudComputing #Serverless #LearningByDoing

S3 is now a File System! AWS introduced S3 Files on April 7, 2026. I’ve just finished testing it and it’s a game changer for shared storage architectures. What I built:  A WordPress site running across multiple EC2 instances using S3 Files as shared storage and RDS as the database. Why this matters:  • Full NFS v4.1+ support • Mount S3 buckets directly on EC2, ECS, EKS, Lambda and Fargate  • ~1 ms latency for active data with high throughput for large reads  • No need for EFS • S3 remains the single source of truth The boundary between object storage and file systems is blurring, simplifying architectures and reducing operational overhead for shared workloads. AWS blog:  https://lnkd.in/gfRE-8z6 #AWS #CloudInfrastructure #AmazonS3 #S3Files #DevOps #CloudEngineering #WordPressOnAWS #SolutionsArchitect

Excited to share my latest project: Migrating Legacy AWS Infrastructure to Infrastructure as Code using AWS CDK (TypeScript). I took a manually built “ClickOps” environment and redesigned it into a secure, reproducible AWS architecture with a VPC, public/private subnet segmentation, EC2, RDS, Security Groups, and AWS Secrets Manager, all deployed through code. Beyond implementation, I focused on the why behind the architecture decisions, applying system design principles around security, scalability, reliability, and cost optimization. 📖 Medium article —link in the first comment #AWS #AWSCDK #InfrastructureAsCode #DevOps #CloudArchitecture #SystemDesign

Today I worked on creating a volume snapshot in the us-east-1 region using the AWS CLI. This is a common practice for backups or before performing risky system updates. Command used: aws ec2 create-snapshot --volume-id --description "" --tag-specifications 'ResourceType=snapshot,Tags=[{Key=Name,Value=}]' --region us-east-1 Verification: aws ec2 describe-snapshots --snapshot-ids --query "Snapshots[*].State" --region us-east-1 Result: "completed" 🎉 #AWS #EC2 #CloudComputing #DevOps

Trouble connecting to an EC2 instance? A generic error message often points to underlying health issues, from OS boot failures to storage or resource constraints. In this guide, Brien Posey walks through how to diagnose problems using status checks, monitoring data and system logs. Learn how to troubleshoot EC2 connection issues: https://lnkd.in/dK9rcYym #AWS #EC2 #CloudComputing #DevOps #ITOps

What is the difference between AWS #Lambda and Amazon #EC2? #AWS Lambda Serverless — no need to manage servers Runs code only when triggered (event-driven) Automatically scales up or down Pay only for execution time Best for short tasks, automation, APIs Amazon EC2 Virtual servers with full control You manage OS, software, and scaling Runs continuously until stopped Pay for uptime (even if idle) Best for long-running applications and full control Final Answer: Lambda = No servers + event-driven + pay per use EC2 = Full control + always running + pay for uptime Tip: In real-world projects, both are often used together. #AWS #CloudComputing #DevOps #Serverless #EC2 #Lambda #USA #Europe