A deep technical guide to designing a robust, provider-agnostic billing pipeline for usage-based SaaS. Covers subscription state machines, idempotent event processing, automated dunning logic, credit notes, and metered invoice generation with full SQL schemas, Mermaid diagrams, and Go snippets.

A practical field guide to Couchbase indexing. Covers primary vs GSI indexes, composite key ordering, index-order sorting, covering and partial indexes, array indexes (including replacing OR and LIKE), IntersectScan and UnionScan avoidance, replication and partitioning, projection selectivity, the ADVISE and INFER tools, scan consistency, and pagination, all with runnable SQL++ (N1QL) examples against the travel-sample dataset.

A practical, opinionated guide to designing backend APIs. Covers request and response schema, offset and keyset pagination, BFF, server-driven UI, caching, versioning, naming, the new HTTP QUERY verb, WebSocket vs SSE, API security (auth headers, server-to-server auth, webhook receivers), and bulk data load APIs. Built around Relay, the same AI proxy system from the multi-tenant SaaS post, with REST and JSON as the running example and Go code throughout.

How to use cache to prevent your database from getting hammered. Understanding cache mechanics, types, strategies, and when each one wins.

A full system design of a production rate limiter. Covers every major algorithm (token bucket, sliding window, leaky bucket, fixed window), their tradeoffs, how they break in a distributed system, how Redis fixes them, and how Stripe, Cloudflare, and API gateways actually deploy this in production.

A complete system design of Relay, a multi-tenant AI API gateway. Covers multi-tenant database architecture (silo vs pool vs bridge), API key authentication, provider routing with failover, dual-layer rate limiting, token-based billing, response caching, row-level security, tenant provisioning, and observability. Full Postgres schemas, mermaid diagrams, and Go snippets included.

Learn how to build production-ready Python background workers that scale under load. Covers worker pools, queue architecture, retry strategies, idempotency, and graceful shutdown.