The Dashbit blog post explores the practicality of embedding Python within an Elixir application using the erlport
library. It demonstrates how to establish a connection to a Python process, execute Python code, and handle the results within Elixir. The author highlights the ease of setup and basic interaction, while acknowledging the performance limitations inherent in this approach, particularly the serialization overhead. While suitable for specific use cases like leveraging existing Python libraries or integrating with Python-based services, the post cautions against using it for performance-critical tasks. Instead, it recommends exploring alternative solutions like dedicated Python services or rewriting performance-sensitive code in Elixir for optimal integration.
This blog post demonstrates how to build an agent-less system monitoring tool using Elixir and Broadway. It leverages SSH to remotely execute commands on target machines, collecting metrics like CPU usage, memory consumption, and disk space. Broadway manages the concurrent execution of these commands across multiple hosts, providing scalability and fault tolerance. The collected data is then processed and displayed, offering a centralized overview of system performance. The author highlights the benefits of this approach, including simplified deployment (no agent installation required) and the inherent robustness of Elixir and its ecosystem. This method offers a lightweight yet powerful solution for monitoring server infrastructure.
Hacker News users discussed the practicality and benefits of the agentless approach to system monitoring described in the linked blog post. Several commenters appreciated the simplicity and reduced overhead of not needing to install agents on monitored machines. Some raised concerns about potential security implications of running commands remotely via SSH and the potential performance bottlenecks of doing so. Others questioned the scalability of this method, particularly for large numbers of monitored systems. The discussion also touched on alternative approaches like using message queues and the potential benefits of Elixir's concurrency features for this type of monitoring system. A compelling comment suggested exploring the use of OSquery for efficient data gathering, which prompted further discussion on its pros and cons. Finally, some commenters expressed interest in the author's open-sourcing of their project.
Summary of Comments ( 29 )
https://news.ycombinator.com/item?id=43171239
Hacker News users discuss the practicality and potential benefits of embedding Python within Elixir applications. Several commenters highlight the performance implications, questioning whether the overhead introduced by the bridge outweighs the advantages of using Python libraries. One user suggests that using a separate Python service accessed via HTTP might be a simpler and more performant solution in many cases. Another points out that the real advantage lies in gradually integrating Python for specific tasks within an existing Elixir application, rather than building an entire system around this approach. Some discuss the potential usefulness for data science tasks, leveraging existing Python tools and libraries within an Elixir system. The maintainability and debugging aspects of such hybrid systems are also brought up as potential challenges. Several commenters also share their experiences with similar integration approaches using other languages.
The Hacker News post "Embedding Python in Elixir, It's Fine" generated several comments discussing the merits and drawbacks of integrating Python and Elixir.
One commenter questioned the long-term viability of such an approach, expressing concern about the added complexity of managing two different runtime environments and the potential difficulties in debugging and profiling. They argued that if a project requires significant Python integration, it might be more sensible to simply use Python for the entire project.
Another commenter pointed out that Python's rich ecosystem of scientific and machine learning libraries is often the primary motivator for such integrations. They highlighted the benefit of leveraging existing Python code and tools within an Elixir application, especially in domains where Python excels.
A counterpoint to this argument arose from a commenter who suggested that rewriting Python code in Elixir, while potentially time-consuming, could lead to better performance and maintainability in the long run. They acknowledged the initial investment required but emphasized the potential benefits of a unified codebase and the ability to fully leverage Elixir's concurrency features.
Several commenters shared their own experiences with integrating Python and other languages into Elixir applications. One user recounted their successful implementation using Ports, a mechanism in Elixir for inter-process communication. Another commenter mentioned using a similar strategy for integrating R with Elixir, demonstrating that this concept is applicable beyond just Python.
The discussion also touched on the performance implications of embedding Python. Some users cautioned that the overhead of inter-process communication could negate the performance advantages of Elixir, especially for high-throughput applications. Others suggested that the impact would vary depending on the specific use case and the nature of the interaction between Elixir and Python.
One commenter mentioned alternative approaches to language integration, such as using a message queue like RabbitMQ. This approach could decouple the Elixir and Python components, potentially simplifying development and deployment, while also offering scalability benefits.
Finally, there was some discussion around the tooling available for debugging and profiling mixed-language applications. One commenter lamented the relative lack of mature tools in this area, emphasizing the importance of robust logging and monitoring strategies when working with such integrations.
Overall, the comments on Hacker News reflected a nuanced perspective on embedding Python in Elixir. While acknowledging the potential benefits of leveraging Python's libraries and existing code, commenters also highlighted the potential challenges related to complexity, performance, and debugging. The discussion emphasized the importance of carefully considering the trade-offs involved and choosing the right approach for each specific situation.