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Why We Migrated from Microservices Back to a Monolith

After three years of operating a microservices architecture with 47 services, our team made the controversial decision to consolidate back into a modular monolith. The operational overhead of managing service-to-service communication, distributed tracing, and deployment orchestration had exceeded the organizational benefits we initially sought.

The turning point came when we calculated that our infrastructure team was spending 60% of their time on platform maintenance — keeping service meshes updated, managing certificate rotation across services, and debugging distributed transaction failures. Our actual business logic represented less than 30% of the total codebase.

The migration took four months. We used a strangler fig pattern in reverse, gradually routing traffic from individual services to modules within the monolith. Module boundaries enforce the same isolation contracts as service boundaries, but without the network overhead. Our deployment pipeline went from 45 minutes for a full rollout to 3 minutes.

SQLite as Your Production Database: A 2026 Perspective

The narrative around SQLite has shifted dramatically. With tools like LiteFS providing transparent replication and Litestream offering continuous backup to S3, SQLite is now a legitimate choice for production workloads serving thousands of concurrent users. The elimination of client-server overhead means queries that took 5ms with PostgreSQL complete in under 50 microseconds.

The key insight is that most web applications don't need distributed databases. They need fast, reliable data access on a single node. SQLite's WAL mode provides excellent concurrent read performance, and for most SaaS products, a single powerful server handles more traffic than teams realize. We've been running SQLite in production for 18 months serving 50,000 daily active users with a p99 latency of 2ms.

The Disappearing Frontend Framework

A new generation of frameworks is emerging that compile away at build time, leaving behind only the minimal JavaScript needed for interactivity. Astro's islands architecture, Qwik's resumability model, and Svelte 5's runes all represent different approaches to the same insight: ship less JavaScript, make the browser do less work.

We benchmarked a typical e-commerce product page across frameworks. The Astro version shipped 42KB of JavaScript total. The equivalent React SPA shipped 287KB. Time to Interactive was 0.8s versus 3.2s on a mid-range mobile device. For content-heavy sites, the framework that sends the least JavaScript wins the performance race by default.

This doesn't mean React or Vue are dead — they remain excellent choices for highly interactive applications like dashboards, editors, and real-time collaboration tools. But for marketing sites, blogs, documentation, and e-commerce storefronts, the compile-to-vanilla approach delivers measurably better user experiences.

Type Safety Across the Full Stack with tRPC

End-to-end type safety used to be an aspirational goal. With tRPC, it's a practical reality. Define your API procedures with Zod schemas on the server, and TypeScript automatically infers the types on the client. No code generation, no OpenAPI specs to maintain, no runtime type mismatches. When you change a procedure's input schema, the client-side call sites light up with type errors immediately.

The developer experience improvement is dramatic. Autocompletion works across the network boundary. Refactoring an API shape is as safe as refactoring a local function signature. Our team's API-related bugs dropped by 80% after adopting tRPC, and onboarding time for new developers decreased because the API surface is self-documenting through types.