Erlang's defining characteristics aren't lightweight processes and message passing, but rather its error handling philosophy. The author argues that Erlang's true power comes from embracing failure as inevitable and providing mechanisms to isolate and manage it. This is achieved through the "let it crash" philosophy, where individual processes are allowed to fail without impacting the overall system, combined with supervisor hierarchies that restart failed processes and maintain system stability. The lightweight processes and message passing are merely tools that facilitate this error handling approach by providing isolation and a means for asynchronous communication between supervised components. Ultimately, Erlang's strength lies in its ability to build robust and fault-tolerant systems.
pg-mcp is a cloud-ready Postgres Minimum Controllable Postgres (MCP) server designed for testing and experimentation. It simplifies Postgres setup and management by providing a pre-built, containerized environment that can be easily deployed with Docker. This allows developers to quickly spin up a disposable Postgres instance for tasks like testing migrations, experimenting with different configurations, or reproducing bugs, without the overhead of managing a full-fledged database server.
HN commenters generally expressed interest in the project, praising its potential for simplifying multi-primary PostgreSQL setups. Several users questioned the performance implications, particularly regarding conflict resolution and latency. Some pointed out existing solutions like BDR and Patroni, suggesting comparisons would be beneficial. The discussion also touched on the complexities of handling schema changes in a multi-primary environment and the need for robust conflict resolution strategies. A few commenters expressed concerns about the project's early stage of development, emphasizing the importance of thorough testing and documentation. The overall sentiment leaned towards cautious optimism, acknowledging the project's ambition while recognizing the inherent challenges of multi-primary databases.
CyanView, a company specializing in camera control and color processing for live broadcasts, used Elixir to manage the complex visual setup for Super Bowl LIX. Their system, leveraging Elixir's fault tolerance and concurrency capabilities, coordinated multiple cameras, lenses, and color settings, ensuring consistent image quality across the broadcast. This allowed operators to dynamically adjust parameters in real-time and maintain precise visual fidelity throughout the high-stakes event, despite the numerous cameras and dynamic nature of the production. The robust Elixir application handled critical color adjustments, matching various cameras and providing a seamless viewing experience for millions of viewers.
HN commenters generally praised Elixir's suitability for soft real-time systems like CyanView's video processing application. Several noted the impressive scale and low latency achieved. One commenter questioned the actual role of Elixir, suggesting it might be primarily for the control plane rather than the core video processing. Another highlighted the importance of choosing the right tool for the job and how Elixir fit CyanView's needs. Some discussion revolved around the meaning of "soft real-time" and the nuances of different latency requirements. A few commenters expressed interest in learning more about the underlying NIFs and how they interact with the BEAM VM.
DiceDB is a decentralized, verifiable, and tamper-proof database built on the Internet Computer. It leverages blockchain technology to ensure data integrity and transparency, allowing developers to build applications with enhanced trust and security. It offers familiar SQL queries and ACID transactions, making it easy to integrate into existing workflows while providing the benefits of decentralization, including censorship resistance and data immutability. DiceDB aims to eliminate single points of failure and vendor lock-in, empowering developers with greater control over their data.
Hacker News users discussed DiceDB's novelty and potential use cases. Some questioned its practical applications beyond niche scenarios, doubting the need for a specialized database for dice rolling mechanics. Others expressed interest in its potential for game development, simulations, and educational tools, praising its focus on a specific problem domain. A few commenters delved into technical aspects, discussing the implementation of probability distributions and the efficiency of the chosen database technology. Overall, the reception was mixed, with some intrigued by the concept and others skeptical of its broader relevance. Several users requested clarification on the actual implementation details and performance benchmarks.
The blog post "An epic treatise on error models for systems programming languages" explores the landscape of error handling strategies, arguing that current approaches in languages like C, C++, Go, and Rust are insufficient for robust systems programming. It criticizes unchecked exceptions for their potential to cause undefined behavior and resource leaks, while also finding fault with error codes and checked exceptions for their verbosity and tendency to hinder code flow. The author advocates for a more comprehensive error model based on "algebraic effects," which allows developers to precisely define and handle various error scenarios while maintaining control over resource management and program termination. This approach aims to combine the benefits of different error handling mechanisms while mitigating their respective drawbacks, ultimately promoting greater reliability and predictability in systems software.
HN commenters largely praised the article for its thoroughness and clarity in explaining error handling strategies. Several appreciated the author's balanced approach, presenting the tradeoffs of each model without overtly favoring one. Some highlighted the insightful discussion of checked exceptions and their limitations, particularly in relation to algebraic error types and error-returning functions. A few commenters offered additional perspectives, including the importance of distinguishing between recoverable and unrecoverable errors, and the potential benefits of static analysis tools in managing error handling. The overall sentiment was positive, with many thanking the author for providing a valuable resource for systems programmers.
AtomixDB is a new open-source, embedded, distributed SQL database written in Go. It aims for high availability and fault tolerance using a Raft consensus algorithm. The project features a SQL-like query language, support for transactions, and a focus on horizontal scalability. It's intended to be embedded directly into applications written in Go, offering a lightweight and performant database solution without external dependencies.
HN commenters generally expressed interest in AtomixDB, praising its clean Golang implementation and the choice to avoid Raft. Several questioned the performance implications of using gRPC for inter-node communication, particularly for write-heavy workloads. Some users suggested benchmarks comparing AtomixDB to established databases like etcd or FoundationDB would be beneficial. The project's novelty and apparent simplicity were seen as positive aspects, but the lack of real-world testing and operational experience was noted as a potential concern. There was some discussion around the chosen consensus protocol and its trade-offs compared to Raft.
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.
Researchers have demonstrated that antimony atoms implanted in silicon can function as qubits with impressive coherence times—a key factor for building practical quantum computers. Antimony's nuclear spin is less susceptible to noise from the surrounding silicon environment compared to electron spins typically used in silicon qubits, leading to these longer coherence times. This increased stability could simplify error correction procedures, making antimony-based qubits a promising candidate for scalable quantum computing. The demonstration used a scanning tunneling microscope to manipulate individual antimony atoms and measure their quantum properties, confirming their potential for high-fidelity quantum operations.
Hacker News users discuss the challenges of scaling quantum computing, particularly regarding error correction. Some express skepticism about the feasibility of building large, fault-tolerant quantum computers, citing the immense overhead required for error correction and the difficulty of maintaining coherence. Others are more optimistic, pointing to the steady progress being made and suggesting that specialized, error-resistant qubits like those based on antimony atoms could be a promising path forward. The discussion also touches upon the distinction between logical and physical qubits, with some emphasizing the importance of clearly communicating this difference to avoid hype and unrealistic expectations. A few commenters highlight the resource intensiveness of current error correction methods, noting that thousands of physical qubits might be needed for a single logical qubit, raising concerns about scalability.
Kronotop is a new open-source database designed as a Redis-compatible, transactional document store built on top of FoundationDB. It aims to offer the familiar interface and ease-of-use of Redis, combined with the strong consistency, scalability, and fault tolerance provided by FoundationDB. Kronotop supports a subset of Redis commands, including string, list, set, hash, and sorted set data structures, along with multi-key transactions ensuring atomicity and isolation. This makes it suitable for applications needing both the flexible data modeling of a document store and the robust guarantees of a distributed transactional database. The project emphasizes performance and is actively under development.
HN commenters generally expressed interest in Kronotop, praising its use of FoundationDB for its robustness and the project's potential. Some questioned the need for another database when Redis already exists, suggesting the value proposition wasn't entirely clear. Others compared it favorably to Redis' JSON support, highlighting Kronotop's transactional nature and ACID compliance as significant advantages. Performance concerns were raised, with a desire for benchmarks to compare it to existing solutions. The project's early stage was acknowledged, leading to discussions about potential feature additions like secondary indexes and broader API compatibility. The choice of Rust was also lauded for its performance and safety characteristics.
rqlite's testing strategy employs a multi-layered approach. Unit tests cover individual components and functions. Integration tests, leveraging Docker Compose, verify interactions between rqlite nodes in various cluster configurations. Property-based tests, using Hypothesis, automatically generate and run diverse test cases to uncover unexpected edge cases and ensure data integrity. Finally, end-to-end tests simulate real-world scenarios, including node failures and network partitions, focusing on cluster stability and recovery mechanisms. This comprehensive testing regime aims to guarantee rqlite's reliability and robustness across diverse operating environments.
HN commenters generally praised the rqlite testing approach for its simplicity and reliance on real-world SQLite. Several noted the clever use of Docker to orchestrate a realistic distributed environment for testing. Some questioned the level of test coverage, particularly around edge cases and failure scenarios, and suggested adding property-based testing. Others discussed the benefits and drawbacks of integration testing versus unit testing in this context, with some advocating for a more balanced approach. The author of rqlite also participated, responding to questions and clarifying details about the testing strategy and future plans. One commenter highlighted the educational value of the article, appreciating its clear explanation of the testing process.
The Canva outage highlighted the challenges of scaling a popular service during peak demand. The surge in holiday season traffic overwhelmed Canva's systems, leading to widespread disruptions and emphasizing the difficulty of accurately predicting and preparing for such spikes. While Canva quickly implemented mitigation strategies and restored service, the incident underscored the importance of robust infrastructure, resilient architecture, and effective communication during outages, especially for services heavily relied upon by businesses and individuals. The event serves as another reminder of the constant balancing act between managing explosive growth and maintaining reliable service.
Several commenters on Hacker News discussed the Canva outage, focusing on the complexities of distributed systems. Some highlighted the challenges of debugging such systems, particularly when saturation and cascading failures are involved. The discussion touched upon the difficulty of predicting and mitigating these types of outages, even with robust testing. Some questioned Canva's architectural choices, suggesting potential improvements like rate limiting and circuit breakers, while others emphasized the inherent unpredictability of large-scale systems and the inevitability of occasional failures. There was also debate about the trade-offs between performance and resilience, and the difficulty of achieving both simultaneously. A few users shared their personal experiences with similar outages in other systems, reinforcing the widespread nature of these challenges.
Summary of Comments ( 164 )
https://news.ycombinator.com/item?id=43655221
Hacker News users discussed the meaning and significance of "lightweight processes and message passing" in Erlang. Several commenters argued that the author missed the point, emphasizing that the true power of Erlang lies in its fault tolerance and the "let it crash" philosophy enabled by lightweight processes and isolation. They argued that while other languages might technically offer similar concurrency mechanisms, they lack Erlang's robust error handling and ability to build genuinely fault-tolerant systems. Some commenters pointed out that immutability and the single assignment paradigm are also crucial to Erlang's strengths. A few comments focused on the challenges of debugging Erlang systems and the potential performance overhead of message passing. Others highlighted the benefits of the actor model for concurrency and distribution. Overall, the discussion centered on the nuances of Erlang's design and whether the author adequately captured its core value proposition.
The Hacker News post titled "Erlang's not about lightweight processes and message passing (2023)" generated several comments discussing the author's viewpoint on Erlang's core strengths.
Several commenters agreed with the author's assertion that immutability is a crucial aspect of Erlang, enabling easier reasoning about code and simplifying debugging. One commenter highlighted the benefits of immutability in concurrent programming, suggesting that it allows developers to avoid many of the pitfalls associated with shared mutable state. Another emphasized the significance of immutability by drawing a parallel to functional programming paradigms and their advantages.
The discussion also explored the concept of "behavior" as a core component of Erlang. Some commenters saw this as a powerful abstraction for building concurrent systems, allowing developers to define patterns of interaction between processes in a structured way. This view was further supported by a commenter who pointed out the similarities between Erlang's behaviors and the actor model, where actors communicate through message passing.
The notion of lightweight processes and message passing, while acknowledged as part of Erlang, was not considered the primary defining characteristic by several commenters. They argued that these features, while important for concurrency, are mechanisms to achieve higher-level goals like fault tolerance and scalability, which are ultimately what make Erlang unique. One commenter specifically stated that the real strength of Erlang lies in its ability to build robust and resilient systems, rather than just its implementation details.
There was also discussion about the learning curve associated with Erlang and its suitability for different types of projects. While some commenters acknowledged its complexity, others emphasized the value of the robustness and reliability it offers, especially for critical systems.
Some commenters also drew comparisons between Erlang and other languages like Smalltalk, highlighting similarities in their approach to message passing and concurrency. This comparison prompted further discussion about the historical context and influences on Erlang's design.
Finally, a few comments touched upon alternative approaches to concurrency, such as using shared memory and mutexes, and discussed their trade-offs compared to Erlang's message-passing model. These comments offered a broader perspective on concurrency models and their applicability in different scenarios.