Best of Elixir — December 2024

1. 1
   Article

   ElixirStatus·1y

   agentjido/jido: A foundational framework for building autonomous, distributed agent systems in Elixir.

   Jido is a foundational framework for building autonomous, distributed agent systems in Elixir. It allows for the creation of smart, composable workflows that can adapt to their environment. Key features include composable actions, real-time sensors, adaptive learning, and built-in telemetry. It is designed for multi-node Elixir clusters and includes robust testing tools. Jido is currently under active development, with the stable API encompassing Actions, Workflows, Agents, and Sensors.

   20
2. 2
   Video

   YouTube·1y

   Elixir vs Go (Golang) Performance (Latency - Throughput - Saturation - Availability)

   The post compares the performance of Elixir and Go, focusing on latency, throughput, saturation, and availability. Benchmark tests are conducted on AWS EC2 instances, using Kubernetes for deployment and Prometheus for monitoring. Go consistently outperforms Elixir in all metrics, handling more requests with lower latency and better resource usage. The post details the setup and results of the tests, highlighting the differences in performance and providing graphs for a visual comparison.

   13
3. 3
   Article

   Awesome Elixir·1y

   Learning Elixir with writing a small CLI

   A Java developer shares his experience of learning Elixir by building a small CLI project. He discusses his motivation, decision to use a hands-on approach, the challenges faced, and the strategies adopted including using a mock API, implementing custom command frameworks, and handling errors. The post also covers his insights on testing philosophies, documenting code, and the overall learning benefits. It concludes with general takeaways about project-based learning and the enjoyable aspects of Elixir.

   12
4. 4
   Article

   ElixirStatus·1y

   Elixir 1.18's new “auto_reload” option in IEx

   Elixir 1.18 introduces an auto_reload option for IEx, allowing automatic code reloading without needing to manually call recompile(). This guide details setting up a new Mix project, configuring auto_reload, and integrating with tools like entr for automatic recompilation. The new feature aims to improve the developer experience, particularly when using multiple OS processes.

   11
5. 5
   Article

   AppSignal·1y

   Distributed Phoenix: Deployment and Scaling

   Effective deployment and scaling strategies for Phoenix applications are crucial as they evolve to meet growing demands. Key topics include single-node and multi-node deployment strategies, horizontal scaling with load balancers, and clustering for high availability. Best practices for monitoring telemetry, error tracking, and maintaining distributed systems are also covered, ensuring performant and resilient applications.

   10