If You Struggle with Designing Rate Limiters, Learn the Token Bucket Algorithm
The blog teaches the token bucket algorithm, the core technique behind rate limiters used by AWS API Gateway, Stripe, Shopify and many other production services. It breaks down the algorithm step‑by‑step, defines the five essential parameters, and shows how to scale it to distributed environments. The guide also provides a ready‑to‑use interview answer structure, aiming to help candidates ace system‑design questions at companies like Google, Amazon and Meta. By mastering token bucket, engineers can design fair, cost‑controlled APIs and avoid common interview pitfalls.
RAM, Disk, and Network: The Speed Differences That Explain Caching, Batching, and CDNs
The post explains how the three primary data‑movement layers—RAM, disk, and network—differ dramatically in latency, shaping modern backend architecture. RAM delivers nanosecond‑scale access, while disks operate in the millisecond range, and network calls add tens to hundreds of milliseconds. These...
From One Bad Query to Full System Outage: The Cascading Failure Path Every Engineer Should Understand
A single poorly written database query can cascade into a full system outage by forcing a full table scan or a Cartesian product, exhausting server resources. The post explains how missing indexes, absent limiting clauses, or incorrect join conditions turn...
The 3-Question Framework for Choosing Between Fail-Fast and Graceful Degradation
The post explains how to decide between fail‑fast and graceful degradation for system components. Graceful degradation maintains core functionality by falling back to simple, static responses when non‑critical services fail, while fail‑fast returns an immediate error for critical failures to...
The 4-Layer Metrics Pipeline: OpenTelemetry, Kafka, Time-Series Storage, and Grafana
The blog outlines a four‑layer real‑time metrics pipeline—instrumentation with OpenTelemetry, transport via Kafka, time‑series storage (Prometheus, Mimir, InfluxDB), and visualization in Grafana. It argues that pull‑based scraping introduces multi‑minute latency and drops short‑lived workloads, while a streaming architecture delivers sub‑second...
Consistent Hashing Is HARD Until You Learn How Dynamo Actually Uses It
The post demystifies consistent hashing by showing how Amazon Dynamo (the engine behind DynamoDB) implements it in production. It explains why naive modular hashing fails, introduces the hash ring and virtual nodes, and details Dynamo's replication, preference lists, and coordinator...
Multi-Agent AI Systems Explained: Why One Agent Isn't Enough (and How to Coordinate Many)
The post explains that single‑agent AI often falters when asked to juggle multiple tools and large context windows, leading to errors and hallucinations. Multi‑agent systems solve this by delegating distinct responsibilities to specialized agents—Planner, Executor, Critic, and Orchestrator—mirroring microservices architecture....
The 3 Caching Tools That Power Modern Backend Systems (Redis, Memcached, KeyDB)
Caching is essential for modern back‑ends, storing frequently accessed data in RAM to avoid costly database hits. The blog breaks down the three dominant in‑memory caches in 2026—Redis, Memcached, and KeyDB—highlighting their architectures, data‑structure support, and persistence models. It notes...
API Gateway vs Service Mesh vs Sidecar Proxy: A Decision Framework
The blog clarifies the distinct roles of API gateways, service meshes, and sidecar proxies in microservice architectures, emphasizing their placement in the stack and traffic direction. It explains north‑south traffic (external client requests) versus east‑west traffic (internal service calls) and...
Why Most Candidates Use AI Wrong for System Design Prep (And the Workflow That Actually Works)
Candidates preparing for system‑design interviews are misusing AI by copying generated solutions instead of practicing synthesis. The post argues that reading AI‑crafted designs creates an illusion of competence, while interviewers assess real‑time problem‑solving and trade‑off reasoning. It proposes a workflow...
Why Your Cache Is Serving Stale Data (5 Invalidation Bugs Explained)
The article explains why caches often serve stale data, focusing on five real‑world invalidation bugs that surface as systems scale. It highlights how missed write paths, misaligned TTLs, and other patterns let outdated information linger despite a healthy‑looking stack. By...
Kafka vs Message Queue: Why You Are Probably Using the Wrong One
The post contrasts message queues with distributed logs like Apache Kafka, highlighting that queues delete messages after consumption while logs retain data for replay. It explains how broker and consumer responsibilities differ, affecting scalability and operational complexity. The author warns...
How to Design a Rate Limiter: 3 Algorithms Every Backend Engineer Should Know
The article explains why backend services need rate limiters and walks readers through three core algorithms—Fixed Window, Token Bucket, and Leaky Bucket. It highlights the performance demands of real‑time API gating and argues that Redis’s in‑memory operations make the checks...
How Location Search Actually Works (The Algorithms Behind Uber, DoorDash, and Yelp)
The article explains why traditional relational databases struggle with large‑scale location queries and how spatial indexing solves the problem. It details the inefficiency of naïve O(N) distance calculations and the limitations of B‑Tree indexes for two‑dimensional data. The piece then...
JSON Web Tokens Explained: The Authentication Pattern Behind Every Modern API
JSON Web Tokens (JWT) have become the de‑facto standard for stateless authentication in modern APIs. By embedding user identifiers and permission claims directly in a signed token, servers can verify identity without consulting a central session store. This eliminates the...