AWS Compute Options: EC2, Lambda, ECS, Fargate Compared

💰 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

Today I worked on creating an AMI for an EC2 instance in the us-east-1 region using the AWS CLI. Command used: aws ec2 create-image --instance-id --name "" --region us-east-1 Verification: aws ec2 describe-images --image-ids --query "Images[*].State" --region us-east-1 Result: "available" 🎉 #AWS #EC2 #CloudComputing #DevOps

Recently in an interview, I was asked to explain a real-time architecture using AWS ALB and Auto Scaling. Here’s how I explained it in a simple way: A user sends a request over the internet, which first goes through Route 53 (DNS). Then it enters the VPC via the Internet Gateway. From there, the request is handled by an Application Load Balancer (ALB). The ALB is deployed across multiple Availability Zones in public subnets, so even if one AZ goes down, the application is still available. The main job of ALB is to distribute traffic across multiple backend servers. Now, the important part — the EC2 instances are not in public subnets. They are placed inside private subnets for better security. These instances are part of an Auto Scaling Group, which automatically increases or decreases the number of servers based on traffic. If traffic increases, new instances are launched. If traffic decreases, extra instances are terminated. This helps in both performance and cost optimization. Since the servers are in private subnets, they don’t have direct internet access. So, we use a NAT Gateway in the public subnet to allow outbound internet access (for updates, packages, etc.). Security Groups are configured in such a way that: ALB accepts traffic from the internet EC2 instances accept traffic only from ALB This setup ensures high availability, scalability, and strong security. This was one of those questions where explaining the flow clearly matters more than just naming services. #AWS #DevOps #Cloud #InterviewExperience #AutoScaling #ALB #CloudArchitecture

I worked on attaching a volume to an EC2 instance in the us-east-1 region today. Using the AWS CLI. Command used: aws ec2 attach-volume --volume-id [ID] --instance-id [ID] --device [***] --region us-east-1 Verification: aws ec2 describe-volumes --volume-id [ID] --query "Volumes[*].Attachments[*].State" --region us-east-1 Result: "attached" 🎉 #AWS #EC2 #CloudComputing #DevOps

Just finished 2 AWS modules: EC2, Auto Scaling +Elastic Load Balancing. Here are 4 things that actually surprised me:   • EC2 pricing models are an architecture decision, not just a billing one. On-Demand vs Reserved vs Spot affects what workloads you can even run.   • A VPC without proper subnet design is a security incident waiting to happen. Public subnets for load balancers. Private subnets for everything else. NAT Gateway bridges the gap not the other way around.   • Auto Scaling isn't just about traffic spikes.It's about self-healing. If an instance fails a health check, ASG replaces it automatically. That's resilience built into the infrastructure itself.   • Load balancers are the front door to scalable systems. ALB routes by content. NLB handles millions of requests per second at Layer 4. Picking the right one matters. The mental model shift: You're not managing servers. You're designing systems that respond to what's happening automatically. Cheat sheets on first comment #AWS #CloudComputing #EC2 #VPC #AutoScaling #DevOps #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

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

Today I worked on terminating an EC2 instance in the us-east-1 region using the AWS CLI. Command used: aws ec2 terminate-instances --instance-ids --region us-east-1 Verification: aws ec2 describe-instances --instance-ids --query "Reservations[*].Instances[*].State.Name" --region us-east-1 Result: "terminated" 🎉 #AWS #EC2 #CloudComputing #DevOps

🚀 AWS Scalable Architecture Project Deployed a highly available and secure architecture using core AWS services: 🔹 Flow: Internet → ALB → Target Group → ASG → EC2 🔹 ALB in Public Subnet for traffic distribution 🔹 EC2 in Private Subnets for security 🔹 Auto Scaling Group for dynamic scaling 🔹 Multi-AZ for high availability 🔹 Health Checks for reliability 💡 Built with focus on scalability, security, and fault tolerance #AWS #DevOps #Cloud #EC2 #AutoScaling #LoadBalancer #CloudArchitecture

⚡ Lambda vs. ECS vs. EKS: Stop guessing. Start choosing. I see this mistake every week: Teams running a single microservice on EKS. Teams running 20-minute video encoding in Lambda. Teams spending $500/month on something that should cost $5. Here's a framework to choose the right AWS compute service: AWS Lambda ✅ Event-driven workloads ✅ Infrequent or bursty traffic ✅ Simple APIs, data processing ⚠️ 15-minute timeout limit Amazon ECS (Fargate) ✅ Microservices, web apps ✅ Batch processing ✅ 24/7 workloads ✅ Sweet spot for most containerized apps Amazon EKS ✅ Multi-cloud strategy ✅ Existing Kubernetes investment ✅ Service mesh (Istio, Linkerd) ⚠️ $72/month minimum (control plane) The Numbers (Real Examples): Low-traffic API (10K req/day): • Lambda: $2-5/month 🏆 • ECS Fargate: $30-40 • EKS: $100-150 High-traffic API (1M req/day): • Lambda: $400-500 • ECS Fargate: $300-400 🏆 • EKS: $500-700 The Best Architects Use Multiple: Pattern: API Gateway → Lambda (auth) → ECS (processing) Pattern: EventBridge → Lambda (orchestration) → ECS (batch) Pattern: EKS (core) + Lambda (extensions) Quick Decision Tree: • Event-driven & <15 min → Lambda • Containerized & on AWS → ECS Fargate • Multi-cloud or K8s features → EKS • GPU/ML workloads → ECS EC2 or EKS I wrote a comprehensive guide with cost breakdowns, code examples, and a decision framework. Read the full article here: https://lnkd.in/ds7Cx6rD What's your default compute service on AWS? Lambda, ECS, or EKS? hashtag#AWS hashtag#Lambda hashtag#ECS hashtag#EKS hashtag#Serverless hashtag#Kubernetes hashtag#CloudArchitecture