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

. WEEKLY PICKS .

🚀 Elixir 1.19 RC Delivers 4x Faster Build Times on Large Projects: José Valim dropped the performance bombshell everyone missed at ElixirConf US. Lazy module loading alone yields 2x compilation improvements by eliminating code server bottlenecks, while parallel dependency compilation can deliver 4x faster builds. Companies document CI times dropping from 20 minutes to 6 minutes with one environment variable.

The insight emerged when Alex at Remote diagnosed what should have been obvious: why load compiled modules immediately when you can lazy load them? Set MIX_DEPS_COMPILE_PARTITION_COUNT to half your core count and watch your build pipeline stop wasting developer time.

Skip the build bottlenecks

🤖 Chris McCord Declares Elixir the Accidental Perfect Language for Agents: The Phoenix creator's ElixirConf keynote annihilated the "LLMs favor JavaScript" fatalism that's been poisoning community discussions. McCord demonstrated live coding a Slack clone with Claude Code using Phoenix 1.8's agents.md file, proving that proper tooling beats training data volume. The outcome: complete real-time applications with GenServers, PubSub, and presence in minutes.

BEAM's actor model solves agent orchestration problems that other ecosystems spend months architecting around. The agents.md standardization and usage_rules integration means your entire dependency tree contributes to LLM education automatically.

Own the agent space

⚡ Endurance Stack Pattern Demolishes Microservices Complexity Tax: Zeo Super App obliterated "just use microservices" advice with battle-tested architecture that eliminates infrastructure overhead. Elixir + Phoenix handle I/O-bound realtime work, Rust + Axum manage CPU-intensive algorithms, with gRPC or message buses connecting them. The payoff: systems that scale horizontally while maintaining memory safety.

Production deployments show proper concern separation at the right abstraction level instead of forcing one runtime to handle everything. YugabyteDB for distributed ACID, ScyllaDB for extreme throughput, Meilisearch for tenant-aware search – each tool optimized for specific workloads.

Build the endurance stack

🔧 Htmd Rust NIF Obliterates HTML-to-Markdown Conversion Hell: Kasvith shipped what the ecosystem needed but nobody wanted to build – a fast, reliable HTML-to-Markdown converter that actually handles complex markup correctly. Built on Rust's htmd crate with Rustler bindings, it eliminates the parsing edge cases that make pure-Elixir solutions frustrating for production use.

The approach reveals why wrapping proven Rust libraries eliminates weeks of debugging: stop reimplementing algorithms in Elixir. Enterprise users confirm markdown edge cases that Rust's ecosystem solved years ago continue breaking homegrown parsers.

End the conversion pain

📚 AppSignal Investigation Reveals Embedded Schema Power Beyond Databases: Nikola Begedin's comprehensive guide uncovers how embedded schemas enable API input validation, LiveView form handling, and command pattern implementation without database overhead. The tutorial covers struct enforcement, changeset integration, and type safety patterns that most teams discover by accident.

Organizations using them for API commands and form validation report cleaner separation between web concerns and business logic. The pattern works especially well for fail-fast input validation before expensive database operations.

Harness schema power

Published Benchmarks Lie About System Limits, and Round Numbers Expose the Fraud

A developer's relentless investigation demolished the dangerous myth that published benchmarks represent actual limits. After documenting 16,000 concurrent connections as a "system-level resource limit," something felt wrong. The number was too convenient, too round. Real limits don't usually land on neat multiples.

The revelation hit during a documentation deep-dive that had nothing to do with WebSockets. MacOS default ephemeral port range: 49,152 to 65,535. That's exactly 16,383 available ports – the "system limit" that had been carefully documented and published as comprehensive research.

One configuration change exposed the real potential: sudo sysctl -w net.inet.ip.portrange.first=1024. Suddenly the same optimized code that had been "limited" to 16,000 connections scaled to 50,000 with perfect reliability. The WebSocket handler hadn't changed. The BEAM VM hadn't changed. The hardware hadn't changed. Only the artificial ceiling disappeared.

The corrected results paint a different picture: 50,000 concurrent connections with 44,573 messages per second sustained throughput. Zero errors, zero crashes, same MacBook Pro. The "comprehensive benchmark" that compared Elixir and Go had tested both platforms against the same artificial constraint, making the comparison meaningless.

Read the full investigation

Remember, for bulletproof performance research:

1. Question round numbers – Real system limits rarely land on convenient multiples

2. Investigate the full stack – Application optimization means nothing if infrastructure is misconfigured

3. Challenge published findings – First bottleneck doesn't equal final bottleneck

4. Document configuration dependencies – "System limits" often hide default settings that can be changed

. 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 💜