#Aws Lambda Function

AWS Lambda explained with a real backend example. When a user uploads an image to Amazon S3, it triggers an AWS Lambda function automatically. That function runs image processing logic and resizes the photo for web, mobile, and tablet — without managing any server. This is serverless architecture in action. No always-on backend. No infrastructure management. You pay only for execution time. If you're learning cloud computing, backend development, or AWS architecture, understanding event-driven systems like S3 + Lambda is essential. #aws #awslambda #serverlessarchitecture #cloudcomputing #backenddevelopment

Part 2 of 4: Build a Login System on AWS 🔐 Here's every component you need for a scalable login: ⚡ AWS Lambda — your backend code that scales with traffic 🔀 API Gateway — sits between frontend & backend for routing & security 🗄️ DynamoDB — stores your user data (like a super fast Excel sheet) 📧 Simple Email Service (SES) — handles email verification The best part? Just describe what you want to AI: "I want a Lambda behind API Gateway with access to a DynamoDB table and email service" — and it writes all the infrastructure code with AWS CDK! 🤯 #AWS #SystemDesign #VibeCoding #LearnToCode #CloudComputing #Lambda #DynamoDB #APIGateway #BackendDevelopment #AITools

In this episode of our AWS Explained Series, we break down how teams can run production code without provisioning, patching, or maintaining servers. With AWS Lambda, you upload your code, define the trigger, and AWS handles the infrastructure behind it. Scaling and availability happen automatically, and pricing is typically based on requests and execution time (with a few optional add-ons depending on how you run it). That’s why Lambda is a great fit for event-driven workloads like S3 file uploads, API requests, database changes, and background jobs. Nothing runs idle. Nothing burns budget waiting for traffic. At the same time, serverless isn’t a silver bullet. Lambda works best for short-lived, stateless execution. Long-running processes, persistent connections, or complex state often require other compute models. Knowing where Lambda fits, and where it doesn’t, is what turns serverless from a cost saver into a real architectural advantage. EZOps Cloud. Cloud and DevOps merging expertise and innovation. #aws #serverless #awslambda #cloudarchitecture #ezopscloud

Lambda@Edge: Run code closer to your users with CloudFront! Faster, smarter, and more secure. Level up your cloud game! #LambdaEdge #CloudFront #AWS #Serverless #CloudComputing #WebDevelopment

🚀 Weekend Session: AWS Cloud → Terraform Automation Training 🎯 Limited seats — register now👇 Link to Register: https://forms.gle/qZi8CWuES2Z5VJsh6 (OR) Link is available in Bio We start from AWS Cloud basics and then move step-by-step into Terraform automation (IaC) — exactly how it works in real DevOps teams. 🎯 ✅ AWS fundamentals (beginner friendly) ✅ Terraform from scratch ✅ Live demos & real-time explanation ✅ Certificate included Perfect for beginners & working professionals. 📅 Feb 14, 15, 21 & 22 | ⏰ 7 PM IST #devopstraining #cloudcomputing #aws #terraform #srtechops

Sharing complete AWS + Terraform material used in real-world projects. If you're serious about building strong Cloud & DevOps skills, drop your email ID in the comments. No shortcuts. No fluff. Only practical knowledge. Let’s grow the right way. 🔥 #devops #aws #Terraform #java #python

AWS DevOps Pro Challenge! 🛠🚀 📚 Scenario: Automated Multi-Account Rollout Check the video for the explanation! 🎥 Day 12/40 Feed posts are available at @sk.vives.aws AI generates daily AWS DOP scenarios. #DevOps #DOPS #IAM #AWSConfig #AWSOrganizations #Lambda #CloudFormation #AWS #DevOps #DOP #DevOpsEngineer #AWSCertified #CI_CD #Automation #SRE #CloudEngineering #CloudComputing #Certification #AWSLearning #Study #Engineer #DailyUpdate #Reels #TechReels

Explaining an AWS service that we use to my technical cofounder, as non technical cofounder with minimal understanding 💻 For anyone interested, the actual explanation is here: AWS Lambda is a serverless compute service. It runs code in response to events. You upload your code as a Lambda function. A function is a small program. It has an input, logic, and an output. Lambda waits for an event to trigger the function. Events come from other AWS services or external systems. Common triggers include API requests, file uploads, database changes, and timers. When an event occurs, Lambda creates an execution environment. It loads your code into memory. It passes the event data to your function. The function runs from start to finish. When it finishes, the environment shuts down or is reused. You do not manage servers. You do not choose instance sizes. You do not handle scaling or availability. AWS automatically runs as many copies as needed. Each event gets its own isolated execution. Ten events run ten executions. Ten thousand events run ten thousand executions. Lambda charges based on usage. You pay for execution time and memory used. Billing is measured in milliseconds. Functions have limits. Execution time is capped. Memory and CPU are fixed per run. Local storage is temporary. Lambda works best for short, stateless tasks. State should live in databases or storage services. A common pattern uses Lambda with an API. An HTTP request triggers the function. The function runs logic. It returns a response. Another pattern uses file processing. A file upload triggers the function. The function transforms the file. It saves the result elsewhere. Another pattern uses automation. A scheduled event triggers the function. The function runs maintenance tasks. Think of Lambda as code that runs only when needed. AWS handles infrastructure, scaling, and failures. You focus on logic and events. #tech #saas #entrepreneur #founder #startup