Swap Usage: A Cloud Engineer's Diagnostic Tool

AWS bills you for a lot of things while you sleep. Dev servers nobody is using. Staging environments that ran after the last deploy. Test databases from last week’s debugging session.EC2 instances someone forgot to shut down. None of these feel expensive individually. But together they quietly add up. We have been there, our development environments were running 24 hours a day even though engineers only used them maybe 8–9 hours. That’s a lot of wasted compute. Once we started automatically shutting things down overnight, the difference was obvious on the next AWS bill. That experience is actually what pushed me to start building ParkMyAWS. Just a simple way to schedule EC2 and RDS instances so they stop when nobody needs them and start again the next morning. Sometimes the best SaaS ideas are just fixing a small but annoying habit. Do you shut down your dev infrastructure overnight, or does it run all the time? #AWS #IndieHacker #SoloFounder #BuildingInPublic

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

One of the most underrated questions in cloud architecture: 👉 “What will this cost me every month?” Most of the time, you design first… and figure out cost later. That’s where surprises happen. With CloudForge, I wanted to flip that. Now, as you design your infrastructure visually, you can ask for cost estimates directly and get a breakdown instantly — right inside VS Code. In this example: • A simple Linux VM setup • Full cost breakdown (compute, disk, diagnostics) • Monthly estimate range • Even cost optimisation suggestions (reserved instances, spot VMs, downsizing) No switching tools. No guesswork. No delayed surprises. Just design → understand → optimise in one flow. This is the kind of thing that makes infra design feel a lot more real and a lot less theoretical. #Cloud #Azure #DevOps #FinOps #IaC #Terraform #CloudCost #PlatformEngineering #VSCode

EC2 vs Lambda vs Fargate — this confuses almost every beginner in AWS. Here’s the simplest breakdown 👇 EC2 → Full control, but you manage everything Lambda → No servers, event-driven execution Fargate → Containers without managing infrastructure 💡 The real trick is NOT learning all 3… It’s knowing WHEN to use each. Most people overuse EC2 Smart engineers choose based on use case. 👉 My rule: • Control → EC2 • Automation → Lambda • Containers → Fargate Which one do you use the most in real projects? #AWS #CloudComputing #DevOps #Serverless #Fargate #EC2 #Lambda #CloudEngineering

💡Why Your AWS Setup Fails (And How I Fixed It with a Load Balancer) Just built my first scalable setup on AWS! I deployed an application using Amazon EC2 and configured an Application Load Balancer to distribute traffic across multiple instances. Key learnings: How load balancing actually works behind the scenes Importance of health checks & availability zones Debugging real-world issues (timeouts, traffic routing, etc.) It was challenging at first, but seeing traffic successfully distributed across servers was worth it If you're learning AWS, this is a must-try hands-on project! #AWS #CloudComputing #DevOps #Learning #EC2 #LoadBalancer #Tech

AWS Fundamentals #4 — EC2 Instance Storage Your storage choice on EC2 is an architectural decision, not a default. EBS (Elastic Block Store) — persistent block storage, survives instance stop/termination. Default choice for most workloads. Comes in gp3, io2, st1, sc1 depending on your IOPS and throughput needs. Instance Store — physically attached to the host. Extremely fast, zero network latency. But data is gone the moment the instance stops or fails. Use it for temp files, buffers, caches. EFS (Elastic File System) — shared file storage across multiple instances. Good for shared content, container workloads, lift and shift from on-prem NFS. Instance Store data is not backed up. It is not replicated. If the instance goes down, the data goes with it. Treat it as volatile by design. For IOPS-heavy workloads like databases, gp3 gives you 3000 IOPS baseline at no extra cost. Most teams are still on gp2 paying more for less. Are you still running gp2, or have you migrated to gp3? #AWS #EC2 #CloudStorage #DevOps #AWSFundamentals

I ran a full infrastructure audit that cut an AWS bill by 33%, saving $1,500 per month with zero impact on reliability. Standard AWS deployments often suffer from cost creep because provisioning drifts past its original justification. When version pins aren't reviewed and storage tiers are chosen too conservatively, you end up paying a premium for resources that don't drive performance. The optimization targeted six specific areas across the stack: • 𝗖𝗼𝗺𝗽𝘂𝘁𝗲: Terminated idle EC2 instances and migrated stateless services to EKS Spot instances. • 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲: Upgraded RDS PostgreSQL to exit expensive extended support windows and migrated storage from provisioned IOPS (io1) to gp3. • 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀: Upgraded EKS clusters to standard support versions to eliminate vCPU/hour surcharges. • 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴: Consolidated multiple ALBs into a single load balancer using path-based and host-based routing. By moving away from "conservative" defaults, we changed the cost profile of the environment: • 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝗦𝘂𝗽𝗽𝗼𝗿𝘁: Upgrading EKS and RDS removed persistent surcharges for out-of-support versions. • 𝗦𝗽𝗼𝘁 𝗨𝘁𝗶𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Using Karpenter to provision Spot nodes with On-Demand fallback reduced compute costs by ~60%. • 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 𝗧𝗶𝗲𝗿𝘀: gp3 provided the required 3,000 IOPS without the separate provisioning charges of io1. Outcome: • Monthly bill reduced from $4,500 to $3,000. • $18,000 in annual recurring savings. • Cleaned up multi-region resource sprawl and redundant load balancer fixed costs. The production lesson:  Cloud waste isn't usually one massive error; it’s the accumulation of "extended support" premiums and idle resources across multiple regions. If you haven't reviewed your version pins and storage tiers in six months, you are overpaying. If you're running a non-trivial AWS footprint, this is worth looking at. DMs open or reach me via jakops.cloud Read the full breakdown here: https://lnkd.in/dyxXPKKa #AWS #CostOptimization #CloudEngineering #DevOps

My client upgraded their RDS from r6g.2xlarge to r6g.8xlarge last week. CPU was at 99%. System was down. Panic mode. Cost jumped $340/month instantly. The real cause? A single query running for 23 minutes with no index — blocking every other request. The instance was fine. The query was broken. This is the most common mistake I see with AWS: → System slows down → Upgrade the instance → Problem "solved" → Root cause still unknown → Same thing happens next month We're building EC2 + RDS correlation in InfraDesk — so instead of guessing, you see exactly: Which query is blocking your database How many EC2 threads are waiting on RDS Whether you need to scale OR just fix a query Most tools show EC2 and RDS separately. We're connecting the dots. Because your outage is never just one thing. If you've ever panic-upgraded an AWS instance — drop a 🙋 below. Would love to know how common this actually is. #AWS #CloudCost #FinOps #RDS #BuildInPublic #InfraDesk #CostOptimization #Startup

AWS just gave you a reason to stop rewriting your file-system code. Amazon S3 Files lets you mount an S3 bucket like NFS — on EC2, ECS Fargate, and Lambda — with zero changes to your app logic. → Hard prerequisites (versioning, SSE, CLI version) → IAM roles — file system + compute, done right → Network model — TCP 2049, per-AZ mount targets → Full CLI walkthrough for EC2, Lambda & ECS Fargate → Terraform tracks for all three platforms → A final operator checklist before you go live Swipe through 👇 #AWS #CloudEngineering #DevOps #S3 #Infrastructure

An engineer with 18 years on AWS moved some files to S3. Did his homework. Confirmed same-region EC2-to-S3 transfers are free. Double checked. Good to go. A few days later, AWS Cost Anomaly Detection sent him an alert. 20,167 GB of NAT Gateway transfers. In a single day. $907 on the invoice. He stared at the dashboard. How? He specifically confirmed S3 transfers were free. Here's what happened. His VPC had a NAT Gateway. Most production setups do. By default, S3 traffic routes through it. Even though S3 is an AWS service. Even though it's in the same region. Every byte went out through NAT Gateway and back in. At $0.045 per GB. The fix? A VPC Endpoint for S3. Took 5 minutes to set up. The bill had already crossed $1,000. 18 years on AWS. And a default setting he didn't know about cost him $1,000. What's the worst AWS billing surprise you've had? #AWS #CloudCosts #Engineering