Automated EC2 Backups with AWS Lambda and EventBridge

Day 5: Why "Sharing is Caring" in the Cloud with Amazon EFS 📂 Yesterday we talked about EBS (the personal hard drive). Today, we’re leveling up to Amazon EFS (Elastic File System). 🤝 The Big Difference: > While EBS is usually married to one server, EFS is the social butterfly. It allows hundreds of EC2 instances to read and write to the same files simultaneously. 📈 No Limits: > The best part? It’s "Elastic." You don't have to guess how much storage you need. It grows and shrinks automatically as you add or remove files. The DevOps Takeaway: As a DevOps Engineer, EFS is my go-to for Shared Content. If I’m running a fleet of web servers, I don't want data trapped on a single instance. Using EFS ensures that my application stays "Stateless"—meaning any server can handle any request because they all share the same "brain" (storage). Choosing between EBS and EFS isn't about which is better; it's about architectural requirements! #AWS #EFS #CloudStorage #DevOps #SolutionsArchitect #Scalability #TechLearning #CloudArchitecture

You've clicked "Launch Instance" hundreds of times. But do you actually know what AWS does in those milliseconds after? I mapped every layer of EC2 — instance families, pricing models, networking, storage, lifecycle, scaling — into one complete reference. 10 years of production EC2 decisions. One article. Happy Learning! #AWS #CloudComputing #SoftwareArchitecture #DevOps

💰 Are you overpaying for AWS? Most companies are. After auditing dozens of cloud environments, the same patterns show up every time — oversized instances, forgotten EBS volumes, zero lifecycle policies, and on-demand pricing where Reserved Instances should be. Here's a complete breakdown of 8 proven AWS cost optimization strategies that can cut your cloud bill by 30–70%: ✅ Right-size your EC2 instances using Compute Optimizer ✅ Switch predictable workloads to Reserved Instances or Savings Plans ✅ Run batch jobs on Spot Instances — up to 90% cheaper ✅ Let Auto Scaling handle traffic spikes instead of over-provisioning ✅ Move cold data to S3 Glacier with lifecycle policies ✅ Go serverless where it makes sense — pay per invocation, not per hour ✅ Reduce data transfer costs with CloudFront & VPC endpoints ✅ Tag everything. Budget everything. Review monthly. 📌 Pro tip: Start with AWS Trusted Advisor and Cost Explorer — they'll surface quick wins in under 10 minutes. Cloud cost optimization isn't a one-time task. It's a culture. The teams that stay lean are the ones that build cost awareness into every architecture decision from day one. ♻️ Repost if this helped someone on your team. 💬 What's the biggest AWS cost win you've seen? Drop it in the comments. #AWS #CloudCost #CostOptimization #AWSCloud #CloudArchitecture #DevOps #FinOps #CloudComputing #AWSArchitecture #TechLeadership

🚀 **AWS EC2 Architecture Simplified – Build Scalable & Secure Systems** Understanding how Amazon Web Services powers applications through Amazon EC2 is a must for every cloud engineer. 📌 **What this architecture covers:** * 🌐 Users connect via Internet Gateway * 🔐 Secure access using Security Groups * 🏗️ Compute layer powered by EC2 instances * 💾 Storage with EBS & S3 * 🗄️ Database integration using RDS * 📊 Monitoring via CloudWatch * 🔑 Access control using IAM ⚙️ **Key Highlights:** ✔️ Highly scalable with Auto Scaling ✔️ Fault-tolerant across Availability Zones ✔️ Secure network isolation using VPC ✔️ Flexible compute resources on demand 💡 Whether you're building startups, enterprise apps, or backend APIs, EC2 remains the backbone of cloud infrastructure. 📈 **Pro Tip:** Always combine EC2 with Load Balancer + Auto Scaling for production-grade systems. --- 💬 What AWS service do you use the most in your projects? #AWS #EC2 #CloudComputing #DevOps #Architecture #SystemDesign #BackendDevelopment #TechLearning

🚀 Stop Clicking. Start Understanding the Why Behind AWS Services Instead of just “poking around” the console, an AWS certification trains you to think deeper about every service you use. 🤔 Why choose S3 over EBS for storage? ⚡ Why use Lambda instead of EC2 for certain workloads? 📊 Why does DynamoDB scale effortlessly for high-traffic applications? 💰 Why is one architecture more cost-efficient than another? It’s not about memorizing services — it’s about understanding the purpose, trade-offs, and real-world impact behind each decision. 🧠 You start seeing AWS as a system of intentional design choices, not just a collection of tools. And that shift? That’s what turns hands-on experience into real cloud expertise. #AWS #AWSCertified #CloudComputing #DevOps #Learning #TechCareers Amazon Web Services (AWS)

AWS in Plain English ☁️ If you're getting started with Amazon Web Services, here’s a simple way to understand the core services: • EC2 → Your virtual computer in the cloud • S3 → Scalable storage for files and data • RDS → Managed relational (SQL) databases • Lambda → Run code without managing servers • API Gateway → Entry point for creating and managing APIs • CloudWatch → Monitoring, logs, and alerts • VPC → Your isolated private network in the cloud • IAM → Controls access and permissions • CloudFront → Global content delivery for faster performance • DynamoDB → Fully managed NoSQL database • SNS → Push notifications and messaging • SQS → Reliable message queuing service 💡 Master these, and about 80% of AWS becomes much easier to understand. #AWS #CloudComputing #TechSimplified #DevOps #Learning #Cloud #SoftwareEngineering

We saved a SaaS client $39,600/year on AWS. No replatform. No rewrite. No cutting corners on reliability. Just cleaning up what should have been reviewed months ago. Here’s the breakdown ↓ A client came to us with a simple question: “Can you review our AWS setup? Our product is growing, but our AWS bill is growing faster.” Monthly bill: $14.2K After 2 weeks of work: $10.9K Yearly savings: $39.6K Performance impact: zero What we found: Their ECS services were massively overprovisioned. Too many tasks. Too much idle CPU. Non-prod workloads running full-time. So we: → Rightsized ECS task CPU/memory → Enabled autoscaling on real usage → Shut down non-prod after hours → Moved some workloads to Graviton → Saved: $1.2K/month Then we looked at database costs. They had oversized RDS instances. A read replica with low usage. And storage still sitting on older config. So we: → Rightsized RDS → Removed one underused replica → Moved storage from gp2 to gp3 → Saved: $900/month Next: Lambda. Several functions had provisioned concurrency turned on all day. Memory allocation was far above actual need. So we: → Reduced memory on key functions → Limited provisioned concurrency to peak windows → Saved: $500/month Then data transfer. CloudFront caching was weak. Too many requests were hitting origin. So we: → Fixed cache policies → Improved asset caching and compression → Reduced origin load and egress → Saved: $700/month We also found: Unused Elastic IPs Old snapshots Idle load balancers And spend with no real owner So we: → Cleaned up unused resources → Added tagging and budget alerts → Built a FinOps dashboard for ongoing visibility → Saved: $300/month The truth AWS does not become expensive overnight. It becomes expensive when no one owns the details. If your infra has not been reviewed in the last 90 days, there is a good chance you are leaking money already. Comment “AWS” or DM me and I’ll send review link.

💰 Save up to 90% on EC2? Yes, with Spot Instances Not all workloads need guaranteed uptime. Sometimes, you just need compute power at the best possible price. That’s where AWS Spot Instances shine. 🔹 They run unused EC2 capacity 🔹 You pay much less (up to 90% off) 🔹 But they can be reclaimed by AWS with a 2-minute notice So… when should you use them? ✅ Perfect for: - CI/CD jobs - Data processing - Stateless containers - ML training or batch jobs - Load testing and distributed rendering ❌ Not ideal for: - Stateful apps - Databases - Any workload that can't tolerate interruption 💡 Pro tip: Use them with Auto Scaling Groups, Spot Fleets, or Kubernetes (EKS) to build cost-optimized and resilient architectures. Are you using Spot Instances in production? Curious to hear how you've implemented them 👇 #AWS #EC2 #CloudComputing #FinOps #DevOps #CloudCostOptimization #SpotInstances ##ec2 #cloudcomputing #protip #cloud #CloudArchitecture #compute #workload #awsec2 #autoscaling #spotinstances #spot #aws

AWS has 200+ services. But 90% of real-world cloud infrastructure runs on just 5. Here they are. ☁️ 🖥️ EC2 — Elastic Compute Cloud Virtual servers on demand. Scale up during traffic spikes, scale down to save costs. The backbone of most AWS deployments. 🪣 S3 — Simple Storage Service Store anything — files, backups, static websites, ML datasets. 99.999999999% durability. It simply doesn't lose your data. 🗄️ RDS — Relational Database Service Managed MySQL, PostgreSQL, Aurora. AWS handles patching, backups, and failover — you focus on queries. ⚡ Lambda — Serverless Compute Run code without managing servers. Pay only per execution. Perfect for event-driven architectures and microservices. 🔒 VPC — Virtual Private Cloud Your own isolated network inside AWS. Control traffic, set subnets, define security rules. Foundation of secure cloud architecture. Master these 5 and you'll understand 80% of what runs in production AWS environments today. Follow Developers Street for more cloud concepts, simplified. 🌐 www.developersstreet.com 📞 +91 9412892908 #AWS #CloudComputing #DevOps #CloudArchitecture #AWSCertification #SoftwareEngineering #TechCareers #DevelopersStreet #CloudEngineer #ServerlessComputing #BackendDevelopment #SystemDesign #TechLeadership #AmazonWebServices #WebDevelopment

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