AWS Cloud Infrastructure and Automation Mastery

As part of my cloud learning journey, I explored AWS Lambda and Route 53 in Amazon Web Services. I practiced creating Lambda functions using Python and configured IAM roles to perform tasks like stopping EC2 instances, deleting unused EBS volumes, and releasing unused Elastic IPs. I tested these functions to understand how serverless automation works in real-time. I also worked on Route 53 by creating hosted zones and configuring different routing policies such as simple, weighted, latency, failover, geolocation, geoproximity, and IP-based routing to manage traffic efficiently. This hands-on experience helped me understand how Lambda enables serverless automation and how Route 53 provides scalable and reliable traffic routing in cloud environments. Sharing my assignment work as part of continuous learning and practical experience. #AWS #Lambda #Route53 #CloudComputing #DevOps #Serverless #HandsOnLearning #CloudJourney

Day 16 / 30 – AWS Learning Journey ☁️ ✅ What I learned today: - What Amazon CloudWatch is and why it’s essential for AWS workloads - How CloudWatch supports: • Monitoring • Logging • Alarming • Reporting - Difference between default metrics and custom metrics - Observed real‑time metrics and configured monitoring through a demo 🔍 Key takeaway: You can’t improve or optimize what you don’t measure. CloudWatch provides the visibility and observability needed to operate cloud systems reliably. 📘 Resources: • AWS Zero To Hero Course For DevOps Engineers – YouTube • Official AWS CloudWatch Documentation 🎯 Next up: Understanding AWS Lambda and serverless architecture #30DaysOfAWS #AWS #CloudWatch #Monitoring #LearningInPublic

We have achieved AWS DevOps Competency! This recognition underscores our ability to design & operate scalable, secure & automated cloud environments on Amazon Web Services (AWS).   This milestone builds on our 40+ AWS certifications and showcases our proven DevOps capabilities in CI/CD, infrastructure automation, and #DevSecOps. We are excited to bring value to enterprises and fast-growing companies by accelerating release cycles, improving system reliability & embedding security across delivery pipelines.   Learn more about what our AWS DevOps Competency means for your business: https://lnkd.in/djEjvWCf #AWS #DevOps #CloudEngineering #10Pearls #TechExcellence

Most companies don't fail at transformation because of ambition. 𝗧𝗵𝗲𝘆 𝗳𝗮𝗶𝗹 𝗮𝘁 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻. That's the pattern I see in nearly every buyer conversation. Appetite for change is well ahead of delivery capability. Slow releases. Brittle environments. Teams shipping on heroics, not systems. So I'm genuinely pleased 10Pearls has earned the AWS DevOps Competency. Not for the badge but for what it represents. Amazon Web Services doesn't hand these out lightly. It's earned through repeated, audited proof that we help clients move faster, with stronger engineering foundations underneath. Credit where it's due: Zeeshan Aftab, Shama Ahmad, Aziz Shaikh, Gerlynn H., Ashar Hasan who drove this through. And thanks to Claudia Hritcu for the partnership. How are you navigating DevOps maturity? Happy to compare notes and I can share how we're helping clients with DevOps. #AWS #DevOps

Most engineers don’t realize this AWS mistake. I didn’t either… until I saw the bill. Your cloud cost isn’t high because AWS is expensive. It’s high because of how we use it. I’ve seen this across teams: • Over-provisioned instances • Idle resources running 24/7 • No visibility into usage You end up paying for things no one is even using. Fixing this doesn’t require new tools. Just better decisions. Swipe through this carousel to see what to fix → I share practical DevOps & cloud insights here 🚀 #aws #cloudcomputing #devops #softwareengineer #cloudengineer #finops #engineering

Your AWS architecture isn’t documented. It’s remembered. By one engineer. Who knows: • which service talks to what • why that one config exists • what will break if you change it Until they’re unavailable. And suddenly, everything feels risky. Cloud doesn’t fail because of outages. It fails because no one knows how it works anymore. #AWS #DevOps #CloudComputing #StartupTech #Engineering

Your AWS architecture isn’t documented. It’s remembered. By one engineer. Who knows: • which service talks to what • why that one config exists • what will break if you change it Until they’re unavailable. And suddenly, everything feels risky. Cloud doesn’t fail because of outages. It fails because no one knows how it works anymore. #AWS #DevOps #CloudComputing #StartupTech #Engineering

Navigating the AWS ecosystem can be challenging, especially when deciding which compute service best fits your architecture. As an IT Engineer, I often get asked about the differences between these core services. Here is a high-level breakdown of the AWS Compute family to help you make an informed decision: 🔹 EC2 (Elastic Compute Cloud): The foundation. It provides virtual servers (instances) where you have full control over the OS and stack. Ideal for applications requiring custom configurations. 🔹 Lambda: The king of Serverless. Run code without provisioning or managing servers. You only pay for the compute time you consume. Perfect for event-driven tasks. 🔹 ECS (Elastic Container Service) & EKS (Elastic Kubernetes Service): Your go-to for containerization. ECS is AWS’s native container orchestrator (highly integrated), while EKS is the managed Kubernetes service for those who need industry-standard orchestration. 🔹 Fargate: Serverless compute for containers. It works with both ECS and EKS, removing the need to manage the underlying EC2 instances. You focus on the containers; AWS handles the rest. 🔹 AWS Batch: Designed for batch computing. It efficiently plans, schedules, and executes your batch computing workloads across the full range of AWS compute services. Key Takeaway: There is no "one size fits all." The choice depends on your need for control versus your desire for operational simplicity. What is your "go-to" compute service for new projects? #AWS #CloudComputing #ITEngineering #DevOps #Serverless #TechCommunity #CloudArchitecture

🚀 𝗗𝗮𝘆 𝟮𝟲/𝟭𝟬𝟬: Scaling to the Cloud with Amazon EKS After building clusters "𝘁𝗵𝗲 𝗵𝗮𝗿𝗱 𝘄𝗮𝘆" with Kubeadm, it’s time to see how the pros scale. Today, I moved my Kubernetes journey to the cloud using 𝗔𝗺𝗮𝘇𝗼𝗻 𝗘𝗞𝗦 (Elastic Kubernetes Service). 𝐖𝐡𝐚𝐭 𝐈 𝐂𝐨𝐯𝐞𝐫𝐞𝐝 𝐓𝐨𝐝𝐚𝐲: • 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗔𝗺𝗮𝘇𝗼𝗻 𝗘𝗞𝗦? It is a managed service that takes the burden of managing the Control Plane off your shoulders. AWS ensures the API Server and etcd are highly available, secure, and patched, so you can focus entirely on your worker nodes and applications. • 𝗘𝗞𝗦 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: ➣ 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗣𝗹𝗮𝗻𝗲: Managed by AWS across multiple Availability Zones (AZs). ➣ 𝗪𝗼𝗿𝗸𝗲𝗿 𝗡𝗼𝗱𝗲𝘀: Can be self-managed EC2 instances, Managed Node Groups, or even "serverless" using AWS Fargate. ➣ 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴: Uses the VPC CNI for native AWS networking performance. • 𝟯 𝗪𝗮𝘆𝘀 𝘁𝗼 𝗦𝗽𝗶𝗻 𝗨𝗽 𝗮 𝗖𝗹𝘂𝘀𝘁𝗲𝗿: ➣ 𝗔𝗪𝗦 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗖𝗼𝗻𝘀𝗼𝗹𝗲: Great for visual learners and beginners to understand the configuration steps manually. ➣ 𝗲𝗸𝘀𝗰𝘁𝗹 (𝗧𝗵𝗲 𝗖𝗟𝗜 𝗪𝗮𝘆): The official CLI tool for EKS. It’s incredibly fast-one command can bootstrap an entire cluster with VPCs and IAM roles using CloudFormation under the hood. ➣ 𝗧𝗲𝗿𝗿𝗮𝗳𝗼𝗿𝗺 (𝗜𝗮𝗖): The industry standard for "Infrastructure as Code." Perfect for keeping your cluster setup version-controlled and repeatable. 🛠️ 𝗛𝗮𝗻𝗱𝘀-𝗼𝗻 𝗟𝗮𝗯:  Deploying a Full Stack App on EKS 🔗 𝗚𝗶𝘁𝗛𝘂𝗯 𝗥𝗲𝗽𝗼:https://lnkd.in/ga2Qazby #DevOps #Kubernetes #AWS #EKS #CloudComputing #InfrastructureAsCode #Terraform #Eksctl #SoftwareEngineering #100DaysOfDevOps #CloudNative #FullStack #Automation