Interviewers want you to reason about load, failure, and tradeoffs. Static diagrams help, but traffic and chaos stories are what separate a vague box diagram from a credible narrative. SysSimulator lets you practice that loop in the browser — free, no signup.
Most engineers prepare for system design interviews by reading. They memorize component names, copy architecture diagrams, and rehearse high-level explanations. Then they sit in the interview and get asked something like:
"Your cache is handling 98% of reads at 10,000 RPS. What exactly happens to your p99 latency if the cache goes down mid-traffic?"
The answer requires numbers, a timeline, and a mitigation — not a general description of caches. That's what interviewers at Google, Amazon, Meta, and other top companies are specifically trained to probe for. There are four things they are measuring:
Load reasoning. Can you talk in specific numbers? P50 and P99 latency at a given RPS. Queue depth under load. Connection pool utilization. Throughput ceiling of each component. "It scales" is not an answer. "At 10,000 RPS with 3 app server replicas, my p99 sits at 48ms — here's what happens when I push to 50,000" is.
Failure mode narration. "What if the cache dies?" has one correct structure: what fails first, what cascades in what order, what is the blast radius, how does the system degrade rather than fail completely, and what is your mitigation. An answer that skips any of these steps signals a gap.
Cost awareness. "Why not just add 10 more Redis nodes?" is a trap question. AWS cost estimation gives you the right answer — adding 10 nodes costs approximately $X more per month. Engineers who understand cost tradeoffs get hired at senior levels. Engineers who ignore cost do not.
Tradeoff articulation. Every design decision should have an explicit "because." SQL because reads are relational and consistency matters. Kafka because fan-out write volume exceeds what a synchronous call chain can absorb. Three replicas because that's the minimum for quorum in our consistency model and anything more doesn't justify the cost. The word "because" attached to a number is what separates senior from mid-level.
SysSimulator is built specifically to train these four skills. You run architecture under real simulated load, you watch what breaks, and you practice narrating it.
These are the questions that appear most often at FAANG and top-tier tech company interviews. Each links to the closest SysSimulator blueprint so you can run the architecture immediately.
1. Design Twitter / X
Core challenges: fan-out on write for timeline generation, caching at scale, CDN for media. At 100M DAU with a 1:100 write-to-read ratio, read traffic dominates — the cache hit rate is your most important metric. Blueprint: Social Feed.
2. Design WhatsApp / a chat system
Core challenges: WebSocket connection management, message delivery guarantees (at-least-once vs exactly-once), presence service, push notifications for offline users. The question interviewers ask: "what happens if a user sends a message while the recipient is offline?" Blueprint: Chat System.
3. Design YouTube / video streaming
Core challenges: upload pipeline (encoding, thumbnail generation, chunked storage), CDN for playback, metadata storage separate from blob storage. The bottleneck shifts depending on whether you're optimizing for upload throughput or read latency. Blueprint: Video Streaming.
4. Design Uber / a ride-matching system
Core challenges: geospatial indexing (S2 cells or geohashing), real-time location updates, driver-rider matching algorithm, surge pricing signal propagation. The hardest part is the write amplification from continuous location updates. Blueprint: Ride-Sharing Platform.
5. Design a URL shortener
Core challenges: hash collision handling, read-heavy caching (most URLs are read far more often than created), analytics pipeline for click tracking. Deceptively simple — the interesting parts are in the edge cases. Blueprint: URL Shortener.
6. Design a rate limiter
Core challenges: token bucket vs sliding window algorithm, atomic Redis operations for distributed rate limiting, rate limit headers and graceful rejection. The question behind the question: "how do you handle a distributed environment where your counters live across multiple servers?" Blueprint: API Rate Limiter.
7. Design a payment system
Core challenges: idempotency (charging a card exactly once even with retries), double-spend prevention, audit logging, reconciliation. The most important design property is that payment operations must be safe to retry without side effects. Blueprint: Payment Processing.
8. Design a notification system
Core challenges: multi-channel fan-out (push, email, SMS), delivery receipts, priority queues (urgent alerts vs marketing), handling undeliverable notifications. The scale question: how do you send 10 million push notifications in under 30 seconds? Blueprint: Notification Service.
9. Design a stock exchange / trading platform
Core challenges: order book management, matching engine (price-time priority), market data distribution, guaranteed message ordering. The matching engine is the hardest part — it must be single-threaded for correctness. Blueprint: Trading Platform.
10. Design a distributed cache / key-value store
Core challenges: consistent hashing for key distribution, eviction policies (LRU, LFU), hot key handling, replication for availability. The question interviewers ask: "what happens when a node goes down and its keys need to be redistributed?" Blueprint: Distributed Cache.
Here is exactly how to narrate a SysSimulator session in a live interview. This is the structure that earns the hire signal.
You've loaded the E-Commerce blueprint and set traffic to 10,000 RPS.
"I've got the e-commerce architecture running at 10,000 RPS — you can see the cache hit rate is sitting at 98% and p99 latency is 48ms. The system is healthy at this load. The app server cluster is at about 34% utilization, so there's significant headroom."
Now inject a cache stampede.
"I'm going to simulate what happens if the cache goes down during peak traffic. [inject] You can see the cache hit rate drops from 98% to near zero — every request is now a cache miss. Watch the database — it was handling about 200 QPS, and it's now absorbing the full 10,000 RPS of read traffic. Connection pool depth is climbing. Within 400 milliseconds, the database connection pool is exhausted. P99 latency spikes from 48ms to over 2,000ms. Error rate jumps to 34%."
"The blast radius is the entire read path. The mitigation I'd implement is a circuit breaker on the cache client that detects the miss rate spike and throttles traffic to the database — instead of all 10,000 RPS hitting the DB, we shed load to 20% of normal and serve stale data or degraded responses for the remaining 80% while the cache repopulates. Recovery time depends on cache warm-up speed."
"One thing I'd add in production that this simulator doesn't model: probabilistic early expiration on cache entries, so we never have a thundering herd of simultaneous misses on the same key."
That answer — with specific numbers, a named mitigation, a recovery timeline, and a production nuance — is what earns a strong hire signal.
Every time you make a scaling decision in SysSimulator, the AWS cost panel updates. This trains a habit that separates senior engineers from mid-level ones: attaching a dollar number to every tradeoff.
When an interviewer asks "why not three read replicas instead of one?", the right answer is not just "availability." It's: "Adding two more replicas costs approximately $380 more per month at our data size. The availability benefit — going from one potential failure point to three — is worth that for a revenue-critical read path. It wouldn't be worth it for an internal analytics query that can tolerate some lag."
Numbers anchor decisions. The cost panel gives you those numbers.
SysSimulator is a discrete-event educational simulator, not proof your design handles Black Friday. The numbers are directionally accurate based on real-world component benchmarks, not production-precise.
In interviews, say this explicitly if asked: "I used SysSimulator to explore failure modes and calibrate my intuition for load and cost. In production I'd validate with actual load tests, real observability tooling, and staged rollouts."
Interviewers respect intellectual honesty. What they're testing is whether you have the mental model to reason about load, failure, and cost — not whether your numbers are exact to two decimal places.
Is SysSimulator good for Google system design interviews?
Yes. Google interviewers specifically look for candidates who reason quantitatively about load, failure modes, and tradeoffs. They ask about specific numbers — p99 latency, throughput ceilings, bottleneck identification. SysSimulator trains exactly this.
Can I use it during a live video interview?
Yes. Open it in a browser tab and share your screen. The "Copy share link" feature lets you send the interviewer your exact diagram after the session if they want to review it.
What RPS should I simulate for a typical FAANG design question?
Start at 10,000 RPS for a mid-scale system. Push to 100,000 RPS to find bottlenecks. Always state your assumptions explicitly: "I'm assuming 100M DAU, 1% concurrent at peak, which gives me approximately 100,000 RPS at the load balancer."
How is SysSimulator different from drawing on Excalidraw or a whiteboard?
A whiteboard diagram doesn't fail. SysSimulator injects real failure modes, shows cascade effects, gives you specific latency and error numbers to narrate, and estimates AWS cost. It's the difference between describing how a car works and driving one.
Does it work on mobile?
The simulator canvas is designed for desktop — drag-and-drop architecture design requires a pointer. The content pages work on mobile, but use a laptop or desktop for simulation sessions.
Do I need to sign up or pay anything?
No. Open the browser, start simulating. No account, no email, no credit card, no rate limits.
Can I share my architecture with an interviewer?
Yes. "Copy share link" uploads your diagram and generates a short URL that expires in 7 days. Share it in the chat during a video interview or send it after.
What's the maximum RPS I can simulate?
Up to 100,000 RPS configurable from the toolbar. The Rust/WASM simulation engine has headroom beyond that — the 100,000 limit is set to keep UI metrics readable.
Can I customize the blueprints?
Yes. Load any of the 57 blueprints and modify component configuration — throughput limits, latency distributions, replica counts, cache hit rates. Everything is adjustable. Export as JSON to save your custom versions.
What are MCP agent blueprints?
A set of blueprints for AI agent architectures — systems using Model Context Protocol (MCP) tool servers, agent runtimes, vector stores, and tool registries. These unlock a separate set of AI-agent-specific chaos scenarios not available on standard microservice blueprints.