This content originally appeared on DEV Community and was authored by Aditya Rawal
Part 2 of “System Design Explained Like a Human.”
This time, we explore how large-scale systems recover when the internet fights back.
1. Fault Tolerance & High Availability
Systems continue running even if parts fail.
Flipkart reroutes traffic to healthy zones within seconds.
Tools: Kubernetes health-checks, AWS ALB, Failover Groups.
2. Disaster Recovery & Data Replication
Keep live copies in different regions.
Netflix stores in Mumbai + Singapore for failover.
3. Event-Driven Microservices
Services communicate via events instead of blocking calls.
Example: Swiggy uses Kafka topics between Order, Payment, and Notification services.
4. CAP Trade-offs Revisited
Banking → CP
Social media → AP
Choose what fits your business.
5. Message Queues & Stream Processing
Queues smooth traffic spikes — like taking a token at the bank.
Tools: RabbitMQ, Kafka, Amazon SQS.
6. Rate Limiting & Circuit Breakers
Protect services from overload and cascading failures.
Libraries: Hystrix, Resilience4J.
7. Security & API Gateways
Auth every request via JWT / OAuth.
Gateways also log, throttle, and audit traffic.
8. Cost Optimization
Scale up during peak, scale down after.
Use spot instances and reserved capacity.
9. Monitoring & Alerting
Set SLO-based alerts on latency, error rate, and throughput.
Stacks: Datadog, Grafana, Prometheus.
10. Chaos Engineering
Inject controlled failures to test resilience.
Netflix’s Chaos Monkey kills servers randomly.
11. Data Sharding & Replication Patterns
Shard by user ID / region / hash key to avoid hotspots.
Replicate read-only copies for scale.
12. Global Systems & Edge Computing
Serve users from the nearest location.
CDNs + edge caching reduce latency.
13. Auto-Healing Infrastructure
Kubernetes restarts failed pods automatically.
No manual rebooting at 2 AM.
14. Real-World Case Study — Zomato Order Surge
Health check fails → Pod restarted
LB reroutes traffic
Auto-scaling adds instances
Result: users see a short delay, no downtime.
Conclusion
From caching and queues to chaos and recovery, this two-part journey showed how modern apps scale and survive.
Great architecture isn’t about preventing failure —
it’s about recovering so fast that no one notices.
If you liked this series, 
it on DEV.to and share with your team.
Let’s keep building systems that don’t just scale — they endure.
This content originally appeared on DEV Community and was authored by Aditya Rawal