Series Overview
The Mastering System Design series builds a first-principles mental model for system design interviews and real production architecture. Each post stands alone, includes a mermaid diagram, and emphasizes trade-offs and failure modes.
TL;DR / Key Takeaways
- Start with requirements and sizing before choosing any architecture.
- Use the map to see how traffic, data, messaging, and reliability connect.
- Jump to any topic below, or read in order for the full progression.
How to Use This Series
- If you are new to system design, read them in order and practice them.
- If you are interviewing, focus on the trade-offs and failure modes called out in each post.
- If you are building systems, use each post as a checklist for architecture reviews.
Series Index
Mental Models
Build a requirements-first mindset, define core metrics, and size the system with back-of-the-envelope math. The key trade-off is between latency, availability, and cost, and the main failure mode is failing to make assumptions.
Read: How to Think in System Design: Mental Models
Think About Load, Scale, and Capacity Planning
Learn QPS, concurrency, and read vs. write patterns, then choose between vertical and horizontal scaling. This post highlights the trade-off between scale and cost, and the failure mode of underestimating peak load.
Read: Think About Load, Scale, and Capacity Planning
Why Load Balancers and Traffic Management
Compare L4 and L7 routing, balancing algorithms, and health checks. The trade-off is between simplicity and intelligent routing, and the common failure mode is uneven load caused by stale or missing health signals.
Read: Why Load Balancers and Traffic Management
Caching: Performance at Scale
Understand cache-aside, write-through, and write-behind patterns, plus TTLs and eviction. You balance freshness against speed, and guard against stampedes and stale reads.
Read: Caching: Performance at Scale
Databases: SQL vs NoSQL vs NewSQL
Frame data choices by workload, indexing, replication, and sharding. The trade-offs are between consistency and flexibility versus scale, with failure modes such as write amplification or hot partitions.
Read: Databases: SQL vs NoSQL vs NewSQL
Consistency Models and the CAP Theorem
Explain CAP correctly, choose a consistency model, and use quorum reads and writes. The trade-off is between availability and consistency under partitions, with failure modes such as split-brain and stale data.
Read: Consistency Models and the CAP Theorem
Messaging, Queues, and Event-Driven Systems
Decide between sync and async, queues and streams, and delivery semantics. The trade-off is throughput versus ordering and delivery guarantees, and the failure modes include poison messages and duplicate processing.
Read: Messaging, Queues, and Event-Driven Systems
APIs, Contracts, and Data Flow
Compare REST, GraphQL, and gRPC, then design contracts, versioning, and idempotency. The trade-off is flexibility versus stability, and the failure mode is breaking clients with incompatible changes.
Read: APIs, Contracts, and Data Flow
Reliability, Fault Tolerance, and Resilience
Use redundancy, circuit breakers, retries, and bulkheads to survive failures. The trade-off is resilience versus complexity and cost, and the failure mode is retry storms that cascade across dependencies.
Read: Reliability, Fault Tolerance, and Resilience
Data Partitioning and Distributed Systems
Partition data horizontally, manage hot shards, and rebalance safely. The trade-off is scale versus operational complexity, and the failure mode is hotspots and cross-shard latency spikes.
Read: Data Partitioning and Distributed Systems
Observability and Operability
Design metrics, logs, and traces around SLIs and SLOs. The trade-off is between signal and noise, and the failure mode is the creation of blind spots due to missing or noisy telemetry.
Read: Observability and Operability
Putting It All Together: Interview-Grade System Designs
Walk through end-to-end designs, then practice narrating trade-offs under pressure. The trade-off is breadth versus depth, and the failure mode is skipping the rationale behind your choices.
Read: Putting It All Together: Interview-Grade System Designs