Tools: Designing a Highly Available Web Application on AWS (Production-Grade Guide)

What Does “Highly Available” Really Mean? ## Core Architecture Overview ## Step 1: Design Across Failure Domains ## What Most Tutorials Miss ## Step 2: VPC Design for Resilience ## Step 3: Load Balancing Done Right ## Pro Tip: ## Step 4: Auto Scaling — Beyond “Min 2 Instances” ## What Most People Ignore ## Step 5: Stateless Application Design ## Step 6: Database High Availability ## Exceptional Considerations ## Step 7: DNS Strategy Matters More Than You Think ## Step 8: Multi-Region Strategy (Advanced HA) ## Step 9: Deployment Strategy That Preserves Availability ## Step 10: Observability is Part of Availability ## Step 11: Security Impacts Availability ## Step 12: Chaos Engineering (The Part Nobody Covers) ## Cost Optimization vs High Availability ## Real-World Production Checklist ## Final Architecture Summary High availability (HA) is not a checkbox — it’s a design philosophy. Most tutorials show you how to launch two EC2 instances behind a load balancer and call it “highly available.” But real-world availability involves failure domains, DNS strategy, health checks, data consistency, deployment patterns, observability, and cost trade-offs. In this guide, I’ll walk you through how to design a production-grade, highly available web application on AWS, covering the architectural decisions most tutorials skip. Before touching AWS services, define availability in business terms. Designing for 99.9% is very different from 99.99%. Costs increase exponentially. A production-ready highly available web application on AWS typically looks like this: But the real HA story is about how you configure these. A single AZ can fail. So: ✅ Deploy EC2 instances in at least two AZs ✅ Enable Multi-AZ for RDS ✅ Ensure Load Balancer spans multiple AZs Use Application Load Balancer (ALB) from Elastic Load Balancing. Important production configurations: Use slow start mode for new instances to prevent sudden traffic spikes during scaling. To scale horizontally: Stateful apps break high availability. Multi-AZ ≠ Multi-Region. That’s disaster recovery. Using Amazon Route 53: Most people never test DNS failover until outage day. If your RTO is minutes: Active-Passive is cheaper than Active-Active. Never deploy directly to live servers. With Amazon CloudWatch: Availability isn’t about avoiding failure — it’s about detecting and recovering fast. A DDoS attack is also an availability issue. If you don’t test failure, you don’t have HA. Use AWS Fault Injection Simulator. Availability is proven, not assumed. Is 99.99% required? Or is 99.9% enough? Overengineering is common. ✔ Multi-AZ deployment ✔ Auto Scaling min 2 ✔ Stateless design ✔ DB Multi-AZ ✔ Health checks validated ✔ DNS failover tested ✔ Backups tested ✔ Monitoring alerts configured ✔ Infrastructure as Code ✔ Regular failover drills A truly highly available AWS web app is: High availability is not a diagram — it’s operational discipline. If you enjoyed this deep dive into AWS high availability architecture, let’s connect and keep learning together: 🐦 Twitter (X): https://x.com/Abhishek_4896 💼 LinkedIn: https://www.linkedin.com/in/abhishekjaiswal076/ I regularly share content on: DevOps & Cloud Architecture Production Engineering SRE & Incident Management Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse - SLA (Service Level Agreement) – What you promise (e.g., 99.9% uptime) - SLO (Service Level Objective) – Your internal reliability target - RTO (Recovery Time Objective) – How fast you must recover - RPO (Recovery Point Objective) – How much data loss is acceptable - DNS Layer → Amazon Route 53 - CDN Layer → Amazon CloudFront - Load Balancer → Elastic Load Balancing - Compute → Amazon EC2 with Auto Scaling - Database → Amazon RDS - Object Storage → Amazon S3 - Caching → Amazon ElastiCache - Observability → Amazon CloudWatch - Security → AWS WAF - Availability Zones (AZs) - Data Centers - Ensure subnets are evenly distributed - Check cross-zone load balancing - Validate health check grace periods - Simulate AZ failure (don’t assume) - Public Subnets → ALB - Private Subnets → EC2 - Private DB Subnets → RDS - Use NAT Gateways in multiple AZs (yes, it costs more — but avoids single AZ egress failure) - Use separate route tables per AZ - Enable VPC Flow Logs for debugging outages - Enable cross-zone load balancing - Configure health checks correctly - Use HTTPS with ACM certificates - Redirect HTTP → HTTPS - Enable access logs to S3 - Set min = 2 (across AZs) - Use target tracking scaling - Warm up time aligned with app startup - Use lifecycle hooks for graceful shutdown - Use mixed instance types (spot + on-demand) - Instance scale-in protection - Draining connections before termination - Handling stateful sessions (use Redis) - Store sessions in Amazon ElastiCache - Store uploads in Amazon S3 - Avoid local disk dependencies - Externalize configuration - Enable Multi-AZ deployment - Use read replicas for scaling reads - Enable automated backups - Turn on Performance Insights - Test failover manually - Monitor replication lag - Tune connection pooling - Use parameter groups for HA tuning - Consider cross-region read replica for DR - Use health checks - Configure failover routing - Reduce TTL for faster failover - Use weighted routing for blue/green - Deploy in two regions - Use Route53 failover routing - Use S3 cross-region replication - Use RDS cross-region replica - Store infrastructure as code - Rolling deployments - Blue/Green deployments - Canary releases - GitHub Actions - Health checks pass before shifting traffic - Automatic rollback enabled - Monitor ALB 5xx errors - Monitor RDS failovers - Monitor CPU, memory, disk - Enable custom metrics - Centralized logging - AWS WAF to protect from DDoS - Shield Standard (enabled by default) - Security Groups least privilege - IAM roles for EC2 - Secrets Manager for credentials - Kill EC2 instance manually - Stop RDS primary - Simulate AZ outage - Break network routes - Multi-AZ NAT doubles cost - Multi-Region doubles infra - Read replicas increase DB cost - Distributed across AZs - Scales automatically - Stateless at compute layer - Resilient at database layer - Protected at network edge - Monitored proactively - Tested under failure