Topic
architecture
66 articles across 24 sub-topics
Sub-topic
18 articles
Designing for High Availability: The Road to 99.99% Reliability
TLDR: High Availability (HA) is the art of eliminating Single Points of Failure (SPOFs). By using Active-Active redundancy, automated health checks, and global failover via GSLB, you can achieve "Four
Microservices Architecture: Decomposition, Communication, and Trade-offs
TLDR: Microservices let teams deploy and scale services independently — but every service boundary you draw costs you a network hop, a consistency challenge, and an operational burden. The architectur
System Design HLD Example: Web Crawler
TLDR: A distributed web crawler must balance global throughput with per-domain politeness. The architectural crux is the URL Frontier, which manages priority and rate-limiting across a distributed fet
System Design HLD Example: Video Streaming (YouTube/Netflix)
TLDR: A video streaming platform is a two-sided architectural beast: a batch-oriented transcoding pipeline that converts raw uploads into multi-resolution segments, and a real-time global delivery net
System Design HLD Example: Ride-Sharing (Uber/Lyft)
TLDR: A ride-sharing platform is a high-velocity geospatial matching engine. Drivers stream GPS coordinates every 5 seconds into a Redis Geospatial Index. When a rider requests a trip, the Matching Se
System Design HLD Example: Proximity Service (Yelp/Google Places)
TLDR: A proximity service (Yelp/Google Places) solves the 2D search problem by encoding locations into Geohash strings, which are indexed in a standard B-tree. To guarantee results near grid boundarie
Sub-topic
10 articles
Modernization Architecture Patterns: Strangler Fig, Anti-Corruption Layers, and Modular Monoliths
TLDR: Large-scale modernization usually fails when teams try to replace an entire legacy platform in one synchronized rewrite. The safer approach is to create seams, translate old contracts into stabl
Integration Architecture Patterns: Orchestration, Choreography, Schema Contracts, and Idempotent Receivers
TLDR: Integration failures usually come from weak contracts, unsafe retries, and missing ownership rather than from choosing the wrong transport. Orchestration, choreography, schema contracts, and ide
Event Sourcing Pattern: Auditability, Replay, and Evolution of Domain State
TLDR: Event sourcing pays off when regulatory audit history and replay are first-class requirements — but it demands strict schema evolution, a snapshot strategy, and a framework that owns aggregate l
System Design HLD Example: Payment Processing Platform
TLDR: Payment systems optimize for correctness first, then throughput. This guide covers idempotency, double-entry ledgers, and reconciliation. Stripe processes over 250 million API requests per day,
System Design HLD Example: Notification Service (Email, SMS, Push)
TLDR: A notification platform routes events to per-channel Kafka queues, deduplicates with Redis, and tracks delivery via webhooks — ensuring that critical alerts like password resets never get blocke
System Design HLD Example: File Storage and Sync (Dropbox and Google Drive)
TLDR: Cloud sync systems separate immutable blob storage (S3) from atomic metadata operations (PostgreSQL), using chunk-level deduplication to optimize storage costs and delta-sync events to minimize
Sub-topic
6 articles
Medallion Architecture: Bronze, Silver, and Gold Layers in Practice
TLDR: Medallion Architecture solves the "data swamp" problem by organizing a data lake into three progressively refined zones — Bronze (raw, immutable), Silver (cleaned, conformed), Gold (aggregated,
Kappa Architecture: Streaming-First Data Pipelines
TLDR: Kappa architecture replaces Lambda's batch + speed dual codebases with a single streaming pipeline backed by a replayable Kafka log. Reprocessing becomes replaying from offset 0. One codebase, n
Big Data 101: The 5 Vs, Ecosystem, and Why Scale Breaks Everything
TLDR: Traditional databases fail at big data scale for three concrete reasons — storage saturation, compute bottleneck, and write-lock contention. The 5 Vs (Volume, Velocity, Variety, Veracity, Value)
Lambda Architecture Pattern: Balancing Batch Accuracy with Streaming Freshness
TLDR: Lambda architecture is justified when replay correctness and sub-minute freshness are both non-negotiable despite dual-path complexity. TLDR: Lambda architecture is a fit only when you need bo
Big Data Architecture Patterns: Lambda, Kappa, CDC, Medallion, and Data Mesh
TLDR: A serious data platform is defined less by where files are stored and more by how changes enter the system, how serving layers are materialized, and who owns quality over time. Lambda, Kappa, CD
Data Warehouse vs Data Lake vs Data Lakehouse: Which One to Choose?
TLDR: Warehouse = structured, clean data for BI and SQL dashboards (Snowflake, BigQuery). Lake = raw, messy data for ML and data science (S3, HDFS). Lakehouse = open table formats (Delta Lake, Iceberg
Sub-topic
4 articles
Simplifying Code with the Single Responsibility Principle
TLDR TLDR: The Single Responsibility Principle says a class should have only one reason to change. If a change in DB schema AND a change in email format both require you to edit the same class, that
Interface Segregation Principle: No Fat Interfaces
TLDR TLDR: The Interface Segregation Principle (ISP) states that clients should not be forced to depend on methods they don't use. Split large "fat" interfaces into smaller, role-specific ones. A Rob
How the Open/Closed Principle Enhances Software Development
TLDR TLDR: The Open/Closed Principle (OCP) states software entities should be open for extension (add new behavior) but closed for modification (don't touch existing, tested code). This prevents new
Dependency Inversion Principle: Decoupling Your Code
TLDR TLDR: The Dependency Inversion Principle (DIP) states that high-level business logic should depend on abstractions (interfaces), not on concrete implementations (MySQL, SendGrid, etc.). This let
Sub-topic
3 articles
Stream Processing Pipeline Pattern: Stateful Real-Time Data Products
TLDR: Stream pipelines succeed when event-time semantics, state management, and replay strategy are designed together — and Kafka Streams lets you build all three directly inside your Spring Boot serv
Dimensional Modeling and SCD Patterns: Building Stable Analytics Warehouses
TLDR: Dimensional modeling with explicit SCD policy is the foundation for reproducible metrics and trustworthy historical analytics. TLDR: Dimensional models stay trustworthy only when teams define
Data Pipeline Orchestration Pattern: DAG Scheduling, Retries, and Recovery
TLDR: Pipeline orchestration is an operational control plane problem that requires explicit dependency, retry, and backfill contracts. TLDR: Pipeline orchestration is less about drawing DAGs and mor
Sub-topic
3 articles
Serverless Architecture Pattern: Event-Driven Scale with Operational Guardrails
TLDR: Serverless is strongest for spiky asynchronous workloads when cold-start, observability, and state boundaries are intentionally designed. TLDR: Serverless works best for spiky, event-driven wo
Infrastructure as Code Pattern: GitOps, Reusable Modules, and Policy Guardrails
TLDR: Infrastructure as code is useful because it makes infrastructure changes reviewable, repeatable, and testable. It becomes production-grade only when module boundaries, state locking, GitOps flow
Cloud Architecture Patterns: Cells, Control Planes, Sidecars, and Queue-Based Load Leveling
TLDR: Cloud scale is not created by sprinkling managed services around a diagram. It comes from isolating failure domains, separating coordination from request serving, and smoothing bursty work befor
Sub-topic
2 articles
Sparse Mixture of Experts: How MoE LLMs Do More With Less Compute
TLDR: Mixture of Experts (MoE) replaces the single dense Feed-Forward Network (FFN) layer in each Transformer block with N independent expert FFNs plus a learned router. Only the top-K experts activat
Dense LLM Architecture: How Every Parameter Works on Every Token
TLDR: In a dense LLM every single parameter is active for every token in every forward pass — no routing, no selection. A transformer block runs multi-head self-attention (Q, K, V) followed by a feed-
Sub-topic
2 articles
Microservices Data Patterns: Saga, Transactional Outbox, CQRS, and Event Sourcing
TLDR: Microservices get risky when teams distribute writes without defining how business invariants survive network delays, retries, and partial failures. Patterns like transactional outbox, saga, CQR
CQRS Pattern: Separating Write Models from Query Models at Scale
TLDR: CQRS works when read and write workloads diverge, but only with explicit freshness budgets and projection reliability. The hard part is not separating models — it is operating lag, replay, and r
Sub-topic
2 articles
Deployment Architecture Patterns: Blue-Green, Canary, Shadow Traffic, Feature Flags, and GitOps
TLDR: Release safety is an architecture capability, not just a CI/CD convenience. Blue-green, canary, shadow traffic, feature flags, and GitOps patterns exist to control blast radius, measure regressi
Canary Deployment Pattern: Progressive Delivery Guarded by SLOs
TLDR: Canary deployment is useful only when the rollout gates are defined before the rollout starts. Sending 1% of traffic to a bad build is still a bad release if you do not know what metric forces r
Sub-topic
2 articles
'The Developer''s Guide: When to Use Code, ML, LLMs, or Agents'
TLDR: AI is a tool, not a religion. Use Code for deterministic logic (banking, math). Use Traditional ML for structured predictions (fraud, recommendations). Use LLMs for unstructured text (summarizat
A Guide to Pre-training Large Language Models
TLDR: Pre-training is the phase where an LLM learns "Language" and "World Knowledge" by reading petabytes of text. It uses Self-Supervised Learning to predict the next word in a sentence. This creates
Sub-topic
1 article
Service Mesh Pattern: Control Plane, Data Plane, and Zero-Trust Traffic
TLDR: A service mesh intercepts all service-to-service traffic via injected Envoy sidecar proxies, letting a platform team enforce mTLS, retries, timeouts, and circuit breaking centrally — without cha
Sub-topic
1 article
Saga Pattern: Coordinating Distributed Transactions with Compensation
TLDR: A Saga replaces fragile distributed 2PC with a sequence of local transactions, each backed by an explicit compensating transaction. Use orchestration when workflow control needs a single brain;
Sub-topic
1 article
MLOps Model Serving and Monitoring Patterns for Production Readiness
TLDR: Production ML reliability depends on joining inference serving, data-quality signals, and rollback automation into one operating loop. TLDR: This dedicated deep dive focuses on the internals,
Sub-topic
1 article
Feature Flags Pattern: Decouple Deployments from User Exposure
TLDR: Feature flags separate deploy from exposure. They are operationally valuable when you need cohort rollout, instant kill switches, or entitlement control without rebuilding or redeploying the ser
Sub-topic
1 article
Dead Letter Queue Pattern: Isolating Poison Messages and Recovering Safely
TLDR: A dead letter queue protects throughput by moving repeatedly failing messages out of the hot path. It only works if retries are bounded, triage has an owner, and replay is a deliberate workflow
Sub-topic
1 article
Circuit Breaker Pattern: Prevent Cascading Failures in Service Calls
TLDR: Circuit breakers protect callers from repeatedly hitting a failing dependency. They turn slow failure into fast failure, giving the rest of the system room to recover. TLDR: A circuit breaker
Sub-topic
1 article
Change Data Capture Pattern: Log-Based Data Movement Without Full Reloads
TLDR: Change data capture moves committed database changes into downstream systems without full reloads. It is most useful when freshness matters, replay matters, and the source database must remain t
Sub-topic
1 article
Bulkhead Pattern: Isolating Capacity to Protect Critical Workloads
TLDR: Bulkheads isolate capacity so one overloaded dependency or workload class cannot consume every thread, queue slot, or connection in the service. TLDR: Use bulkheads when different workloads do
Sub-topic
1 article
Blue-Green Deployment Pattern: Safe Cutovers with Instant Rollback
TLDR: Blue-green deployment reduces release risk by preparing the new environment completely before traffic moves. It is most effective when rollback is a routing change, not a rebuild. TLDR: Blue-g
Sub-topic
1 article
AI Architecture Patterns: Routers, Planner-Worker Loops, Memory Layers, and Evaluation Guardrails
TLDR: A single agent loop is enough for a demo, but production AI systems need explicit layers for routing, execution, memory, and evaluation. Those layers determine safety, latency, cost, and traceab
Sub-topic
1 article
Understanding Consistency Patterns: An In-Depth Analysis
TLDR TLDR: Consistency is about whether all nodes in a distributed system show the same data at the same time. Strong consistency gives correctness but costs latency. Eventual consistency gives speed
Sub-topic
1 article
How Transformer Architecture Works: A Deep Dive
TLDR: The Transformer is the architecture behind every major LLM (GPT, BERT, Claude, Gemini). Its core innovation is Self-Attention — a mechanism that lets the model weigh relationships between all to
