What is Sysiq and how is it different from reading static blogs?

Sysiq is an interactive system design platform where you don't just read about distributed systems — you actively build and test them. Solve real-world engineering challenges using a live diagram canvas, guided architectural labs, and real-time napkin math estimation tools.

Is Sysiq suitable for preparing for FAANG system design interviews?

Yes. Sysiq is tailored specifically for mid-level, senior, and staff engineering interviews (L4–L7). The problem bank covers actual interview scenarios: URL shorteners, distributed rate limiters, key-value stores, video streaming architectures, and real-time chat systems.

Can I use Sysiq for free?

Yes. Foundational modules, introductory interview problems, the Napkin Math calculator, and the global engineering leaderboard are all free with no time limit.

Do I need prior distributed systems experience to get started?

Not at all. The curriculum starts with fundamental building blocks — DNS, reverse proxies, database replication, and caching — and progressively walks you up to complex architectures like Raft consensus, vector clocks, and LSM-tree compaction.

Curriculum

16 modules · 67 topics

Foundations

Scalability, latency, throughput, and the availability-consistency tradeoff — the vocabulary you need before anything else makes sense

Distributed Systems

CAP theorem, consistency models (weak, eventual, strong), and availability patterns like failover and replication

Networking & DNS

DNS resolution, TCP vs UDP vs QUIC, TLS handshakes, HTTP protocol evolution, CDN edge caching, and connection pooling

Load Balancing

L4 vs L7 balancing, routing algorithms (round robin, least connections, consistent hashing), reverse proxies, and horizontal scaling

Application Architecture

Monoliths vs microservices, service discovery, REST vs gRPC, idempotency patterns, and retry strategies with backoff

Databases

ACID transactions, storage engine internals (B+ trees, LSM trees), isolation levels, replication topologies, sharding strategies, and query optimization

NoSQL Databases

Key-value stores, document databases, wide-column stores, and graph databases — when each model fits and when it doesn't

Caching Strategies

Cache-aside, write-through, write-behind patterns, eviction policies, cache stampede protection, and CDN edge caching

Asynchronous Processing

Message queues vs event logs, delivery guarantees (at-most/at-least/exactly-once), dead letter queues, backpressure, and background workers

Security

Authentication flows, authorization models, encryption at rest and in transit, OAuth2/OIDC, JWTs, and mutual TLS

Advanced Storage & S3

S3 architecture and consistency model, block vs file vs object storage tradeoffs, and HDFS for large-scale batch processing

Event-Driven Architecture

Kafka internals (partitions, offsets, consumer groups), event sourcing, CQRS, and real-time protocols (WebSockets, SSE)

Advanced Distributed Concepts

Consistent hashing, Raft and Paxos consensus, logical and vector clocks, TrueTime, and gossip protocols

Specialized Data Structures

Bloom filters, HyperLogLog, Count-Min Sketch, Snowflake IDs, geohashing, and rate-limiting algorithms used in production systems

Data Engineering

MapReduce batch processing, stream processing with Flink and Spark, and OLAP vs OLTP data warehouse architectures

Resilience & Observability

Circuit breakers, bulkheads, load shedding, and the three pillars of observability (metrics, logs, distributed traces)