HLD · SYSTEM DESIGN · INTERACTIVE LEARNING

System design finally
makes sense.

100+ animated concepts that evolve as you scroll. Interactive simulations you control. Game levels that test you under real pressure.

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CONCEPT 04 · LOAD BALANCING — FRAME 3 OF 6LIVE DIAGRAM
CLIENT
10k req/s
LOAD BALANCER
Round Robin
APP SERVER 1
CPU 38%
APP SERVER 2
CPU 41%
APP SERVER 3
CPU 35%
DATABASE
Primary
SCROLL TO ADVANCE FRAME ↓
100+
CONCEPTS
3
LEARNING MODES
$0
TO START
✦CAP Theorem✦Load Balancing✦Cache Stampede✦Consistent Hashing✦Vertical Scaling✦Replication✦Sharding✦CDN✦Auto-scaling✦Leader Election✦Rate Limiting✦Circuit Breakers✦Write-Through Cache✦SQL vs NoSQL✦Cache Invalidation✦Horizontal Scaling✦Two-Phase Commit✦LSM Trees✦ACID vs BASE✦Cache Aside✦Read Replicas✦Message Queues✦Event Sourcing✦CQRS✦Bloom Filters✦Geohashing✦WebSockets✦CAP Theorem✦Load Balancing✦Cache Stampede✦Consistent Hashing✦Vertical Scaling✦Replication✦Sharding✦CDN✦Auto-scaling✦Leader Election✦Rate Limiting✦Circuit Breakers✦Write-Through Cache✦SQL vs NoSQL✦Cache Invalidation✦Horizontal Scaling✦Two-Phase Commit✦LSM Trees✦ACID vs BASE✦Cache Aside✦Read Replicas✦Message Queues✦Event Sourcing✦CQRS✦Bloom Filters✦Geohashing✦WebSockets✦CAP Theorem✦Load Balancing✦Cache Stampede✦Consistent Hashing✦Vertical Scaling✦Replication✦Sharding✦CDN✦Auto-scaling✦Leader Election✦Rate Limiting✦Circuit Breakers✦Write-Through Cache✦SQL vs NoSQL✦Cache Invalidation✦Horizontal Scaling✦Two-Phase Commit✦LSM Trees✦ACID vs BASE✦Cache Aside✦Read Replicas✦Message Queues✦Event Sourcing✦CQRS✦Bloom Filters✦Geohashing✦WebSockets✦CAP Theorem✦Load Balancing✦Cache Stampede✦Consistent Hashing✦Vertical Scaling✦Replication✦Sharding✦CDN✦Auto-scaling✦Leader Election✦Rate Limiting✦Circuit Breakers✦Write-Through Cache✦SQL vs NoSQL✦Cache Invalidation✦Horizontal Scaling✦Two-Phase Commit✦LSM Trees✦ACID vs BASE✦Cache Aside✦Read Replicas✦Message Queues✦Event Sourcing✦CQRS✦Bloom Filters✦Geohashing✦WebSockets
THE PROBLEM

Why static content
doesn't stick.

You've read the blogs. Watched the videos. But ask you to explain consistent hashing under pressure — and it blurs. Here's why.

01
Reading ≠ understanding
Text describes systems sequentially. Real distributed systems are concurrent and spatial. Your brain can't simulate that from words alone.
02
Static diagrams miss the motion
A snapshot can't show what happens when a node fails, traffic spikes, or a cache expires. One frozen frame tells you nothing about a live system.
03
No way to test your model
Passive consumption feels productive. But understanding only locks in when you make a decision and see the consequence play out.
HOW IT WORKS

Three ways to learn.
All in one place.

Each mode targets a different stage — build the mental model, practice it hands-on, then prove you can apply it under pressure.

Client
Cache HIT
Cache MISS
DB
SCROLL ↓
FRAME 3 / 8
MODE 01
Animated Concepts
Read the explanation — the diagram evolves with every paragraph. Each frame tied to a moment in the text. No clicks, no setup.
100+ CONCEPTS
EC2
Client
STEP 2 / 4 · YOUR TASK
Connect a Client node to your EC2 instance
✓ Check my work
MODE 02
Interactive Lessons
Step-by-step guided lessons where you build a real architecture on a live canvas, validating each decision before moving forward.
HANDS-ON
⚠ SYSTEM ALERT — CPU 92%
CPU LOAD92%
t3.small 92%
→ scale?
MODE 03
Game Levels
Real failure scenarios. Traffic spikes, node outages, cache stampedes. Build an architecture that holds — before time runs out.
COMING SOON
WHAT'S INSIDE

Every concept you need.
Built to actually teach.

From vertical scaling to distributed consensus — animated, interactive, and explained without hand-waving.

ALL
SCALABILITY
CACHING
DISTRIBUTED SYSTEMS
DATABASES
ClientLBS1S2S3
SCALABILITY
Load Balancing
How traffic gets distributed across servers — round robin, least connections, and what happens when one goes down.
ANIMATEDOpen →
ConsistencyAvailabilityPartitionpick 2
DISTRIBUTED SYSTEMS
CAP Theorem
Consistency, availability, partition tolerance — why you can only ever guarantee two, and what that means in practice.
ANIMATEDOpen →
t3.smallxlarge
SCALABILITY
Vertical Scaling
Make the machine bigger. Fast to apply, but there's always a ceiling.
LESSONOpen →
C1C2C3CACHEEXPIREDDB
CACHING
Cache Stampede
When a cache expires and every request hits the database at once — how to prevent the thundering herd.
ANIMATEDOpen →
RouterShard 1Shard 2Shard 3
DATABASES
Sharding
Splitting data across multiple database nodes — how routers decide which shard holds your key.
ANIMATEDOpen →
S1S2S3+S4+
SCALABILITY
Horizontal Scaling
Add more machines instead of a bigger one. The foundation of every large-scale system.
ANIMATEDOpen →
PrimaryWRITEReplica 1Replica 2
DATABASES
Replication
Primary-replica patterns, replication lag, and how read scaling works in distributed databases.
ANIMATEDOpen →
N1N2N3key
DISTRIBUTED SYSTEMS
Consistent Hashing
Hash rings that minimize key remapping when nodes join or leave — the backbone of distributed caches.
ANIMATEDOpen →
CACHESource DBINVALIDATEREFRESH
CACHING
Cache Invalidation
The hard part of caching — when to invalidate, how to propagate the signal, and avoiding stale reads.
ANIMATEDOpen →
Coming soon
SCALABILITY
Rate Limiting
Token buckets, sliding windows, and why protecting your API matters.
COMING SOON
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✦All playable system design levels
✦Cloud progress tracking
✦Saved level attempts and receipts
✦New content updates
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