Engineering deep dives, not tutorials.
System design, distributed systems, and production patterns for engineers who build at scale.
Latest Articles
Fresh deep dives into system design, security, and engineering.
Idempotency in Distributed Systems — Why Your Retry Just Charged the Customer Twice
A practical guide to idempotency: why retries cause double charges, how idempotency keys and dedup stores fix it, delivery semantics (at-least-once vs exactly-once), and how to make non-idempotent operations like payments safe.
Message Queue vs Stream — RabbitMQ/SQS vs Kafka, and When to Use Which
The real difference between a message queue (RabbitMQ, SQS) and an event stream (Kafka): consume-and-delete vs append-and-keep, how each scales consumers, delivery and ordering guarantees, and a simple test for choosing the right one.
Vector Databases & Embeddings, Explained — From Text to Similarity Search
A clear guide to embeddings and vector databases: what an embedding really is, how approximate nearest-neighbour (ANN) search and HNSW make similarity search fast at scale, and when you actually need a dedicated vector DB versus pgvector or plain brute force.
AI Models in 2025 — Cost, Capabilities, and Which One to Use
A comparison of AI models from Anthropic, OpenAI, Google, Meta, Mistral, and DeepSeek — pricing, capabilities, and the best fit per use case.
AI Video Generation in 2025 — Models, Costs, and How to Build a Cost-Effective Pipeline
A guide to AI video models — Sora, Veo 2, Kling, Runway, Pika — per-second pricing, quality tradeoffs, and pipelines that cut costs by 80%.
AI Image Generation in 2025 — Models, Costs, and How to Optimize Spend
A guide to AI image generation models — DALL-E 3, Imagen 3, Stable Diffusion, FLUX, Midjourney — pricing, quality, and how to cut costs 10-20x.
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Observability & Production Debugging — From the Three Pillars to Debugging a Live Incident
A practical course on seeing into production systems and debugging them fast: monitoring vs observability, the three pillars (logs, metrics, traces) and how they work together, structured logging, metric types with RED/USE and the four golden signals, distributed tracing and the trace waterfall, OpenTelemetry, dashboards that aren't noise, alerting without fatigue, SLOs and error budgets, a repeatable incident-debugging workflow, performance debugging (percentiles, tail amplification, flame graphs), and the cost/cardinality engineering that keeps the observability bill sane. Grounded in real measurements.
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AI Coding Assistants in 2025 — Every Tool Compared, and Which One to Actually Use
A deep comparison of AI coding assistants — Copilot, Cursor, Claude Code, Aider, Windsurf, and more — features, pricing, and which wins per workflow.
AI Agents Demystified — It's Just Automation With a Better Brain
A no-hype take on AI agents: the same automation patterns we've built for decades, except the if/else decision engine is replaced by an LLM.
Supply Chain Security — Protecting Your Software Pipeline
A guide to software supply chain security — the SLSA framework, dependency pinning, provenance verification, and lessons from the xz attack.
Security Ticketing and Incident Response
Build an effective security incident response process — incident classification, runbooks, ticketing workflows, and post-incident reviews.
Security Mindset for Engineers — Think Like an Attacker
How to adopt a security-first mindset as a software engineer — threat modeling, attack surfaces, defense in depth, and least privilege.
Secrets Management — Vault, SSM, and Secrets Manager
A practical guide to secrets management in the cloud — comparing HashiCorp Vault, AWS SSM, and Secrets Manager, with rotation strategies.
Penetration Testing Basics for Developers
A developer-friendly intro to penetration testing — reconnaissance, common attack vectors, tools like Burp Suite and OWASP ZAP, and test cases.
OWASP Top 10 for Cloud Applications
The OWASP Top 10 through the lens of cloud-native apps — how each vulnerability manifests in AWS/GCP/Azure, with serverless-specific defenses.
Dependency Vulnerability Detection at Scale
How to detect and manage vulnerable dependencies across hundreds of repos — SCA tools, SBOM generation, and automated remediation pipelines.
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