Traffic & Edge
Load Balancing
Route requests across healthy servers and observe failover in action.
Round Robin RoutingSession Persistence (Sticky Sessions)Health Checks & Failover
Start with physical limits and capacity reasoning, then advance through infrastructure, distributed-system mechanics, HLD case studies, LLD, and a repeatable interview method.
Step through live packet routing, failover mechanisms, consensus protocols, and caching topologies with real-time state changes.
Route requests across healthy servers and observe failover in action.
Follow requests from users to nearby edge caches and the origin.
Send requests through a token bucket and inspect accepted and rejected traffic.
Compare cache hits, misses, eviction, and database fallbacks.
Distribute records across shards and see how a shard key routes queries.
Add and remove servers while tracking the small set of remapped keys.
Route writes to a primary and observe replication lag across read replicas.
Publish jobs, build a backlog, and scale consumers to drain the queue.
Trigger failures and follow a circuit breaker through closed, open, and half-open states.
Publish events and watch independent subscribers process the stream.
Create a network partition and compare CP and AP system behavior.
Observe heartbeats, timeouts, voting, and a new leader taking control.
Change demand and capacity to see saturation, queue growth, and safe headroom.
Adjust retry budgets and observe how failures amplify downstream traffic.
Tune read and write quorums and inspect overlap, latency, and availability.
Compare arrival and service rates while watching backlog and overload grow.
Change replication lag and test whether regional failover meets the declared RPO.
Compare measured availability with a target and calculate the remaining error budget.
Inject a saga failure and count the compensations required for completed steps.
Split a dominant key across buckets and observe its maximum per-owner traffic share.
Academic & production standards
Every lesson is cross-verified against established distributed-systems papers, official specifications, and production postmortems.
Put the framework to work
Move from requirements and estimates to APIs, data models, failure paths, and explicit trade-offs in one guided workflow.