Articles
Worth reading
A short take on pieces worth your time — architecture, AI, system design, and engineering careers — each one linked back to its original source.
7 articles
The Death of Microservices Hype: When Modular Monoliths Win
A sober look at the 2026 correction away from "microservices by default": teams that adopted them before they had the scale to justify the operational cost are quietly moving back toward modular monoliths — a single deployable unit with real internal module boundaries, rather than either a tangled legacy monolith or a fleet of distributed services. The honest takeaway isn't "microservices were wrong," it's that the decision needs to follow actual scale and team-topology pressure, not architecture-conference hype.
What Is RAG? How Retrieval-Augmented Generation Works
A clear, current walkthrough of retrieval-augmented generation: why it exists (grounding an LLM in your own data instead of relying on what it memorized during training), how the retrieval-then-generate pipeline actually works, and where teams run into trouble in practice — the retrieval step, not the model, is almost always the real failure point. Useful if you're deciding whether RAG is the right pattern for a project, or just want a precise mental model instead of the marketing version.
Netflix Tackles Data Deletion at Scale with Centralized Platform Architecture
InfoQ's coverage of a QCon talk on a problem almost nobody designs for up front: how do you actually delete data, correctly and completely, across dozens of heterogeneous storage systems, at a scale where 76.8 billion row deletions across 1,300 datasets is a normal workload? Netflix's centralized deletion platform is a reminder that "delete" is a distributed systems problem with its own consistency and observability requirements, not an afterthought bolted onto each service. Especially relevant if you're anywhere near GDPR or CCPA compliance work and have been treating deletion as someone else's problem.
Designing robust and predictable APIs with idempotency
The article that made idempotency keys a standard expectation for any payments-adjacent API: pass a client-generated key with a request, and retries — from a flaky network, a timeout, a naive retry loop — become safe instead of a double-charge waiting to happen. It's a deceptively simple pattern that solves a real and expensive class of production bugs, and this writeup is still one of the clearest explanations of why "just retry on failure" is dangerous without it. Essential if you're designing any API that touches money or triggers a side effect that can't be undone.
Online migrations at scale
Stripe's playbook for the unglamorous but high-stakes work of migrating a live, heavily-used data model — hundreds of millions of Subscriptions objects, no downtime, no data loss allowed — without ever pausing the business to do it. The dual-write-then-backfill-then-cutover pattern they describe is the one I reach for on every schema migration of consequence, because it's the only approach I've seen actually survive production edge cases. Read this before your next "just add a migration" turns into an incident.