Welcome to GigaElixir Gazette, your 5-minute digest of Elixir ecosystem news that actually matters 👋.

. WEEKLY PICKS .

🎭 Hologram v0.6.0 Proves Full-Stack Elixir Isn't Vaporware: Bart Bloszyk shattered the "Elixir can't do frontend" myth with comprehensive form support, CSRF protection, and action scheduling that enables 60 FPS physics simulations. Over 360 commits since v0.5.0 introduce synchronized form elements, comprehensive XSS prevention, and delay parameters for smooth animations.

Real-world deployments confirm what BEAM advocates knew all along: actor-model concurrency works everywhere, not just on servers. The interactive bouncing ball demo showcases physics simulation performance that JavaScript frameworks struggle to match consistently.

Experience full-stack Elixir

🔗 AshTypescript Ends the Dual Type Definition Tax: The Ash team obliterated manual API type definitions with automatic TypeScript generation that ensures compile-time safety between Elixir resources and frontend code. Generate type-safe client functions, comprehensive filter types, and Zod validation schemas directly from your Ash resources without writing interface code.

Investigation revealed why teams waste weeks maintaining dual type definitions that drift out of sync. Enterprise deployments report zero integration bugs after switching from hand-coded API types to generated ones.

Generate bulletproof types

⚡ ReqLLM Destroys the Provider SDK Learning Tax: Mike Hostetler's team exposed the "learn every provider SDK" fraud with Req-based plugins that normalize 45 providers and 665+ models behind a single interface. The library combines Req's middleware ecosystem with automatic cost tracking, streaming support, and structured data generation.

Development teams confirm eliminating thousands of lines of provider-specific boilerplate while gaining sophisticated retry logic and request instrumentation automatically. The plugin architecture means you get all Req's power while the library handles provider quirks and response format variations.

Unify your AI stack

📸 Community Exposes Phoenix Image Pipeline Architecture Patterns: A Reddit discussion uncovered battle-tested approaches for massive image uploads that eliminate server bottlenecks through direct-to-storage uploads and event-driven processing. Seasoned engineers shared presigned URL strategies and Broadway + Oban orchestration patterns.

The conversation annihilates the "proxy everything through Phoenix" antipattern that causes resource starvation during high-volume uploads. Jake Morrison's detailed examples prove BEAM excels at coordinating workflows while cloud services handle heavy lifting.

Build scalable pipelines

🏗️ Jacob Litzo's Brutal SaaS Architecture Walkthrough: Elixir Mentor's production-hardened tutorial exposes multi-tenant task management built with Phoenix LiveView and Ash that eliminates data isolation complexities through context-based filtering. Real-world usage demonstrates real-time collaboration, role-based access control, and Stripe integration.

Context-based multitenancy ensures perfect data isolation automatically while LiveView delivers real-time updates that enhance user experience. The complete source code and deployment guide eliminate the "how do I actually build this?" gap most tutorials leave open.

Master SaaS architecture

Most Developers Waste Network Bandwidth Because They Treat Ecto Like a Basic ORM

Teams stick to conventional Repo.insert_all patterns that generate unnecessary database roundtrips and transfer redundant data. Bego's investigation revealed advanced Ecto techniques that eliminate expensive joins and reduce network overhead through SQL-level optimizations that most developers never discover.

The standard approach for aggregated inserts requires multiple queries and duplicated timestamps. Recording daily metrics forces separate queries for each field, creating bottlenecks that scale poorly as data complexity increases. Teams accept this pattern because it's documented everywhere and works for small datasets.

Ecto supports using SQL queries as map values, enabling single-trip database operations that eliminate expensive joins entirely. Instead of querying separately then inserting, you can insert queries directly as field values. This pattern proved dramatically faster than complex joins when V7 hit performance walls that caused production downtime.

The breakthrough insight: Repo.insert_all accepts queries as map values, not just static data. Each field can be a query returning a single value, eliminating the need to join multiple tables in one expensive operation. Production metrics confirmed this approach handles complex aggregations that would otherwise require careful caching strategies.

But the efficiency gains extend beyond query optimization. Placeholder support prevents sending duplicate values when inserting multiple records. Instead of transferring 2000 identical timestamps for 1000 records, placeholders send one value referenced multiple times, reducing network overhead significantly.

Read the complete optimization guide

Remember, for efficient database operations:

1. Use queries as insert values – Eliminate expensive joins by inserting SQL queries directly as field values

2. Implement placeholder optimization – Reduce network transfer by referencing duplicate values once instead of repeating them

3. Choose patterns by complexity – Simple cases benefit from basic approaches; complex aggregations need SQL-level solutions

4. Profile before optimizing – Measure actual bottlenecks rather than assuming conventional patterns are always sufficient

. TIRED OF DEVOPS HEADACHES? .

Deploy your next Elixir app hassle-free with Gigalixir and focus more on coding, less on ops.

We're specifically designed to support all the features that make Elixir special, so you can keep building amazing things without becoming a DevOps expert.

See you next week,

Michael

P.S. Forward this to a friend who loves Elixir as much as you do 💜