"Designing Electronics That Work" emphasizes practical design considerations often overlooked in theoretical learning. It advocates for a holistic approach, considering component tolerances, environmental factors like temperature and humidity, and the realities of manufacturing processes. The post stresses the importance of thorough testing throughout the design process, not just at the end, and highlights the value of building prototypes to identify and address unforeseen issues. It champions "design for testability" and suggests techniques like adding test points and choosing components that simplify debugging. Ultimately, the article argues that robust electronics design requires anticipating potential problems and designing circuits that are resilient to real-world conditions.
macOS historically handled null pointer dereferences by trapping them, leading to immediate application crashes. This was achieved by mapping the first page of virtual memory to an inaccessible region. Over time, increasing demands for performance, especially from Java, prompted Apple to introduce "guarded pages" in macOS 10.7 (Lion). This optimization allowed for a small window of usable memory at address zero, improving performance for frequently checked null references but introducing the risk of silent memory corruption if a true null pointer dereference occurred. While efforts were made to mitigate these risks, the behavior shifted again in macOS 12 (Monterey) and later ARM-based systems, where the entire page at zero became usable. This means null pointer dereferences now consistently result in memory corruption, potentially leading to more difficult-to-debug issues.
Hacker News users discussed the nuances of null pointer dereferences on macOS and other systems. Some highlighted that the behavior described (where dereferencing a NULL pointer doesn't always crash) isn't unique to macOS and stems from virtual memory page zero being unmapped. Others pointed out the security implications, particularly in the kernel, where such behavior could be exploited. Several commenters mentioned the trade-off between debugging ease (catching null pointer dereferences early) and performance (the overhead of checking for null every time). The history of this design choice and its evolution in different macOS versions was also a topic of conversation, along with comparisons to other operating systems' handling of null pointers. One commenter noted the irony of Apple moving away from this behavior, as it was initially designed to make things less crashy. The utility of tools like scribble for catching such errors was also mentioned.
"The Night Watch" argues that modern operating systems are overly complex and difficult to secure due to the accretion of features and legacy code. It proposes a "clean-slate" approach, advocating for simpler, more formally verifiable microkernels. This would entail moving much of the OS functionality into user space, enabling better isolation and fault containment. While acknowledging the challenges of such a radical shift, including performance concerns and the enormous effort required to rebuild the software ecosystem, the paper contends that the long-term benefits of improved security and reliability outweigh the costs. It emphasizes that the current trajectory of increasingly complex OSes is unsustainable and that a fundamental rethinking of system design is crucial to address the growing security threats facing modern computing.
HN users discuss James Mickens' humorous USENIX keynote, "The Night Watch," focusing on its entertaining delivery and insightful points about the complexities and frustrations of systems work. Several commenters praise Mickens' unique presentation style and the relatable nature of his anecdotes about debugging, legacy code, and the challenges of managing distributed systems. Some highlight specific memorable quotes and jokes, appreciating the blend of humor and technical depth. Others reflect on the timeless nature of the talk, noting how the issues discussed remain relevant years later. A few commenters express interest in seeing a video recording of the presentation.
The author recounts their experience debugging a perplexing issue with an inline eval() call within a JavaScript codebase. They discovered that an external library was unexpectedly modifying the global String.prototype, adding a custom method that clashed with the evaluated code. This interference caused silent failures within the eval(), leading to significant debugging challenges. Ultimately, they resolved the issue by isolating the eval() within a new function scope, effectively shielding it from the polluted global prototype. This experience highlights the potential dangers and unpredictable behavior that can arise when using eval() and relying on a pristine global environment, especially in larger projects with numerous dependencies.
The Hacker News comments discuss the practicality and security implications of the author's inline JavaScript evaluation solution. Several commenters express concern about the potential for XSS vulnerabilities, even with the author's implemented safeguards. Some suggest alternative approaches like using a dedicated sandbox environment or a parser that transforms the input into a safer format. Others debate the trade-offs between convenience and security, questioning whether the benefits of inline evaluation outweigh the risks. A few commenters appreciate the author's exploration of the topic and share their own experiences with similar challenges. The overall sentiment leans towards caution, with many emphasizing the importance of robust security measures when dealing with user-supplied code.
This blog post details further investigations into tracking down the source of persistent radio frequency interference (RFI) plaguing the author's software defined radio (SDR) setup. Having previously eliminated numerous potential culprits, the author focuses on isolating the signal to his house and pinpointing the frequency range using an RTL-SDR dongle and various software tools. Through meticulous testing and analysis, he narrows down the likely source to a neighbor's solar panel system, specifically the micro-inverters responsible for converting DC to AC power. The post highlights the challenges of RFI identification and the effectiveness of using readily available SDR technology for such investigations.
The Hacker News comments discuss the challenges and intricacies of tracking down RFI (Radio Frequency Interference). Several users share their own experiences with RFI, including frustrating hunts for intermittent interference and the difficulties of distinguishing between true RFI and other issues like faulty hardware. One compelling comment highlights the detective work involved, describing the use of directional antennas and spectrum analyzers to pinpoint the source. Another emphasizes the surprising prevalence of RFI and its ability to manifest in unexpected ways. Several commenters appreciate the author's detailed approach and methodical documentation of the process, while others offer additional tools and techniques for RFI hunting. The overall sentiment reflects a shared understanding of the often-frustrating, but sometimes rewarding, nature of tracking down these elusive signals.
Meta developed Strobelight, an internal performance profiling service built on open-source technologies like eBPF and Spark. It provides continuous, low-overhead profiling of their C++ services, allowing engineers to identify performance bottlenecks and optimize CPU usage without deploying special builds or restarting services. Strobelight leverages randomized sampling and aggregation to minimize performance impact while offering flexible filtering and analysis capabilities. This helps Meta improve resource utilization, reduce costs, and ultimately deliver faster, more efficient services to users.
Hacker News commenters generally praised Facebook/Meta's release of Strobelight as a positive contribution to the open-source profiling ecosystem. Some expressed excitement about its use of eBPF and its potential for performance analysis. Several users compared it favorably to other profiling tools, noting its ease of use and comprehensive data visualization. A few commenters raised questions about its scalability and overhead, particularly in large-scale production environments. Others discussed its potential applications beyond the initially stated use cases, including debugging and optimization in various programming languages and frameworks. A small number of commenters also touched upon Facebook's history with open source, expressing cautious optimism about the project's long-term support and development.
CodeTracer is a new, open-source, time-traveling debugger built with Nim and Rust, aiming to be a modern alternative to GDB. It allows developers to record program execution and then step forwards and backwards through the code, inspect variables, and analyze program state at any point in time. Its core functionality includes reverse debugging, function call history navigation, and variable value inspection across different execution points. CodeTracer is designed to be cross-platform and currently supports debugging C/C++, with plans to expand to other languages like Python and JavaScript in the future.
Hacker News users discussed CodeTracer's novelty, questioning its practical advantages over existing debuggers like rr and gdb. Some praised its cross-platform potential and ease of use compared to rr, while others highlighted rr's maturity and deeper system integration as significant advantages. The use of Nim and Rust also sparked debate, with some expressing concerns about the complexity of debugging a debugger written in two languages. Several users questioned the performance implications of recording every instruction, suggesting it might be impractical for complex programs. Finally, some questioned the project's open-source licensing and requested clarification on its usage restrictions.
Python's help() function provides interactive and flexible ways to explore documentation within the interpreter. It displays docstrings for objects, allowing you to examine modules, classes, functions, and methods. Beyond basic usage, help() offers several features like searching for specific terms within documentation, navigating related entries through hyperlinks (if your pager supports it), and viewing the source code of Python objects when available. It utilizes the pydoc module and works on live objects, not just names, reflecting runtime modifications like monkey-patching. While powerful, help() is best for interactive exploration and less suited for programmatic documentation access where inspect or pydoc modules provide better alternatives.
Hacker News users discussed the nuances and limitations of Python's help() function. Some found it useful for quick checks, especially for built-in functions, while others pointed out its shortcomings when dealing with more complex objects or third-party libraries, where docstrings are often incomplete or missing. The discussion touched upon the superiority of using dir() in conjunction with help(), the value of IPython's ? operator for introspection, and the frequent necessity of resorting to external documentation or source code. One commenter highlighted the awkwardness of help() requiring an object rather than a name, and another suggested the pydoc module or online documentation as more robust alternatives for exploration and learning. Several comments also emphasized the importance of well-written docstrings and recommended tools like Sphinx for generating documentation.
The Honeycomb blog post explores the optimal role of humans in AI systems, advocating for a shift from "human-in-the-loop" to "human-in-the-design" approach. While acknowledging the current focus on using humans for labeling training data and validating outputs, the post argues that this reactive approach limits AI's potential. Instead, it emphasizes the importance of human expertise in shaping the entire AI lifecycle, from defining the problem and selecting data to evaluating performance and iterating on design. This proactive involvement leverages human understanding to create more robust, reliable, and ethical AI systems that effectively address real-world needs.
HN users discuss various aspects of human involvement in AI systems. Some argue for human oversight in critical decisions, particularly in fields like medicine and law, emphasizing the need for accountability and preventing biases. Others suggest humans are best suited for defining goals and evaluating outcomes, leaving the execution to AI. The role of humans in training and refining AI models is also highlighted, with suggestions for incorporating human feedback loops to improve accuracy and address edge cases. Several comments mention the importance of understanding context and nuance, areas where humans currently outperform AI. Finally, the potential for humans to focus on creative and strategic tasks, leveraging AI for automation and efficiency, is explored.
Nut.fyi introduces a "time-travel debugger" for prompt engineering. It records the entire execution history of a large language model (LLM) call, enabling developers to step backward and forward through the generation process to understand how and why the model arrived at its output. This allows for easier identification and correction of unexpected behavior, making prompt engineering more predictable and reliable, particularly for complex or creative applications ("vibe coding"). The tool also offers features like variable inspection and prompt editing at any step, further facilitating the debugging process.
HN commenters express skepticism and amusement towards the "vibe coding" concept. Several find the demo video unconvincing, noting that the AI seems to be making simple, predictable corrections, not demonstrating any deep understanding of code or "vibes." Some question the practicality and scalability of the approach. Others joke about the vagueness of "vibe-based" debugging and the potential for misuse. A few express cautious interest, suggesting it might be useful for beginners or specific narrow tasks, but overall the sentiment is that "time-travel debugging" for "vibes" is more of a marketing gimmick than a substantial technical innovation.
Appstat is a free, open-source process monitor for Windows presented as a modern alternative to existing tools. It offers a clean and responsive UI, focusing on real-time performance monitoring with detailed metrics like CPU usage, memory consumption, I/O operations, and network activity. Appstat aims to provide a comprehensive view of system resource utilization by individual processes, enabling users to quickly identify performance bottlenecks and troubleshoot issues. It boasts features like customizable columns, sorting, filtering, process tree views, and historical data charting for deeper analysis.
HN users generally praised Appstat as a useful tool. Several pointed out its similarity to existing tools like Sysinternals Process Monitor (Procmon) while highlighting Appstat's simpler interface and easier setup as advantages. Some appreciated its focus on security-relevant events. Others suggested potential improvements, such as adding filtering capabilities, including command line arguments, and enhancing the UI with features like column sorting. A few users mentioned alternative tools they preferred, including Procmon and ETW Explorer. The developer actively responded to comments, addressing questions and acknowledging suggestions for future development.
While "hallucinations" where LLMs fabricate facts are a significant concern for tasks like writing prose, Simon Willison argues they're less problematic in coding. Code's inherent verifiability through testing and debugging makes these inaccuracies easier to spot and correct. The greater danger lies in subtle logical errors, inefficient algorithms, or security vulnerabilities that are harder to detect and can have more severe consequences in a deployed application. These less obvious mistakes, rather than outright fabrications, pose the real challenge when using LLMs for software development.
Hacker News users generally agreed with the article's premise that code hallucinations are less dangerous than other LLM failures, particularly in text generation. Several commenters pointed out the existing robust tooling and testing practices within software development that help catch errors, making code hallucinations less likely to cause significant harm. Some highlighted the potential for LLMs to be particularly useful for generating boilerplate or repetitive code, where errors are easier to spot and fix. However, some expressed concern about over-reliance on LLMs for security-sensitive code or complex logic, where subtle hallucinations could have serious consequences. The potential for LLMs to create plausible but incorrect code requiring careful review was also a recurring theme. A few commenters also discussed the inherent limitations of LLMs and the importance of understanding their capabilities and limitations before integrating them into workflows.
The blog post argues that speedrunners possess many of the same skills and mindsets as vulnerability researchers. They both meticulously analyze systems, searching for unusual behavior and edge cases that can be exploited for an advantage, whether that's saving milliseconds in a game or bypassing security measures. Speedrunners develop a deep understanding of a system's inner workings through experimentation and observation, often uncovering unintended functionality. This makes them naturally suited to vulnerability research, where finding and exploiting these hidden flaws is the primary goal. The author suggests that with some targeted training and a shift in focus, speedrunners could easily transition into security research, offering a fresh perspective and valuable skillset to the field.
HN commenters largely agree with the premise that speedrunners possess skills applicable to vulnerability research. Several highlighted the meticulous understanding of game mechanics and the ability to manipulate code execution paths as key overlaps. One commenter mentioned the "arbitrary code execution" goal of both speedrunners and security researchers, while another emphasized the creative problem-solving mindset required for both disciplines. A few pointed out that speedrunners already perform a form of vulnerability research when discovering glitches and exploits. Some suggested that formalizing a pathway for speedrunners to transition into security research would be beneficial. The potential for identifying vulnerabilities before game release through speedrunning techniques was also raised.
A recent Linux kernel change inadvertently broke eBPF programs relying on PT_REGS_RC(regs). Intended to optimize register access for x86, this change accidentally cleared the return value register before eBPF programs using kprobe and kretprobe could access it. This resulted in eBPF tools like bpftrace and bcc showing garbage data instead of expected return values. The issue primarily affects x86 systems running kernel versions 6.5 and later and has already been fixed in 6.5.1, 6.4.12, and 6.1.38. Users of affected kernels should update to receive the fix.
The Hacker News comments discuss the complexities and nuances of the issue presented in the article about pt_regs returning garbage in recent Linux kernels due to changes introduced by "Fred." Several commenters express sympathy for Fred, highlighting the challenging trade-offs inherent in kernel development, especially when balancing performance optimizations with backward compatibility. Some point out the difficulties of maintaining eBPF programs across kernel versions and the lack of clear documentation or warnings about these breaking changes. Others delve into the technical specifics, discussing register context, stack unwinding, and the implications for debuggers and profiling tools. The overall sentiment seems to be one of acknowledging the difficulty of the situation and the need for better communication and tooling to navigate such kernel-level changes. A few users also suggest potential workarounds and debugging strategies.
Troubleshooting is a perpetually valuable skill applicable across various domains, from software development to everyday life. It involves a systematic approach of identifying the root cause of a problem, not just treating symptoms. This process relies on observation, critical thinking, research, and testing potential solutions, often involving a cyclical process of refining hypotheses based on results. Mastering troubleshooting empowers individuals to solve problems independently, fostering resilience and adaptability in a constantly evolving world. It's a crucial skill for learning effectively, especially in self-directed learning, by encouraging active engagement with challenges and promoting deeper understanding through the process of overcoming them.
HN users largely praised the article for its clear and concise explanation of troubleshooting methodology. Several commenters highlighted the importance of the "binary search" approach to isolating problems, while others emphasized the value of understanding the system you're working with. Some users shared personal anecdotes about troubleshooting challenges they'd faced, reinforcing the article's points. A few commenters also mentioned the importance of documentation and logging for effective troubleshooting, and the article's brief touch on "pre-mortem" analysis was also appreciated. One compelling comment suggested the article should be required reading for all engineers. Another highlighted the critical skill of translating user complaints into actionable troubleshooting steps.
The author meticulously debugged a mysterious issue where transferring Apple DOS 3.3 system files to a blank diskette sometimes resulted in a bootable disk, and sometimes a non-bootable one, despite seemingly identical procedures. Through painstaking analysis of the DOS 3.3 source code and assembly-level debugging, they discovered the culprit: a timing-sensitive bug within the SYS.COM program related to how it handled track zero formatting. Specifically, SYS.COM occasionally failed to wait for the drive head to settle after seeking to track zero before writing, resulting in corrupted data on the disk. This timing issue was sensitive to drive mechanics and environmental factors, explaining the intermittent nature of the problem. The author's fix involved adding a small delay within SYS.COM to ensure the drive head had stabilized before writing, resolving the frustrating bug and guaranteeing consistent creation of bootable disks.
Several Hacker News commenters praised the author's clear and detailed write-up of the bug hunt, appreciating the methodical approach and the insights into early DOS development. Some shared their own experiences with similar bugs and debugging processes in other systems. One commenter pointed out the historical significance of relying on undocumented behavior, a common practice at the time due to limited documentation. Others discussed the challenges of working with older hardware and software, and the satisfaction of successfully solving such intricate problems. The overall sentiment reflects admiration for the detective work involved and nostalgia for the era of simpler, yet more opaque, computing.
Combining Tokio's asynchronous runtime with prctl(PR_SET_PDEATHSIG) in a multi-threaded Rust application can lead to a subtle and difficult-to-debug issue. PR_SET_PDEATHSIG causes a signal to be sent to a child process when its parent terminates. If a thread in a Tokio runtime calls prctl to set this signal and then that thread's parent exits, the signal can be delivered to a different thread within the runtime, potentially one that is unprepared to handle it and is holding critical resources. This can result in resource leaks, deadlocks, or panics, as the unexpected signal disrupts the normal flow of the asynchronous operations. The blog post details a specific scenario where this occurred and provides guidance on avoiding such issues, emphasizing the importance of carefully considering signal handling when mixing Tokio with prctl.
The Hacker News comments discuss the surprising interaction between Tokio and prctl(PR_SET_PDEATHSIG). Several commenters express surprise at the behavior, noting that it's non-intuitive and potentially dangerous for multi-threaded programs using Tokio. Some point out the complexities of signal handling in general, and the specific challenges when combined with asynchronous runtimes. One commenter highlights the importance of understanding the underlying system calls and their implications, especially when mixing different programming paradigms. The discussion also touches on the difficulty of debugging such issues and the lack of clear documentation or warnings about this particular interaction. A few commenters suggest potential workarounds or mitigations, including avoiding PR_SET_PDEATHSIG altogether in Tokio-based applications. Overall, the comments underscore the subtle complexities that can arise when combining asynchronous programming with low-level system calls.
The post contrasts "war rooms," reactive, high-pressure environments focused on immediate problem-solving during outages, with "deep investigations," proactive, methodical explorations aimed at understanding the root causes of incidents and preventing recurrence. While war rooms are necessary for rapid response and mitigation, their intense focus on the present often hinders genuine learning. Deep investigations, though requiring more time and resources, ultimately offer greater long-term value by identifying systemic weaknesses and enabling preventative measures, leading to more stable and resilient systems. The author argues for a balanced approach, acknowledging the critical role of war rooms but emphasizing the crucial importance of dedicating sufficient attention and resources to post-incident deep investigations.
HN commenters largely agree with the author's premise that "war rooms" for incident response are often ineffective, preferring deep investigations and addressing underlying systemic issues. Several shared personal anecdotes reinforcing the futility of war rooms and the value of blameless postmortems. Some questioned the author's characterization of Google's approach, suggesting their postmortems are deep investigations. Others debated the definition of "war room" and its potential utility in specific, limited scenarios like DDoS attacks where rapid coordination is crucial. A few commenters highlighted the importance of leadership buy-in for effective post-incident analysis and the difficulty of shifting organizational culture away from blame. The contrast between "firefighting" and "fire prevention" through proper engineering practices was also a recurring theme.
The author explores several programming language design ideas centered around improving developer experience and code clarity. They propose a system for automatically managing borrowed references with implicit borrowing and optional explicit lifetimes, aiming to simplify memory management. Additionally, they suggest enhancing type inference and allowing for more flexible function signatures by enabling optional and named arguments with default values, along with improved error messages for type mismatches. Finally, they discuss the possibility of incorporating traits similar to Rust but with a focus on runtime behavior and reflection, potentially enabling more dynamic code generation and introspection.
Hacker News users generally reacted positively to the author's programming language ideas. Several commenters appreciated the focus on simplicity and the exploration of alternative approaches to common language features. The discussion centered on the trade-offs between conciseness, readability, and performance. Some expressed skepticism about the practicality of certain proposals, particularly the elimination of loops and reliance on recursion, citing potential performance issues. Others questioned the proposed module system's reliance on global mutable state. Despite some reservations, the overall sentiment leaned towards encouragement and interest in seeing further development of these ideas. Several commenters suggested exploring existing languages like Factor and Joy, which share some similarities with the author's vision.
Spice86 is an open-source x86 emulator specifically designed for reverse engineering real-mode DOS programs. It translates original x86 code to C# and dynamically recompiles it, allowing for easy code injection, debugging, and modification. This approach enables stepping through original assembly code while simultaneously observing the corresponding C# code. Spice86 supports running original DOS binaries and offers features like memory inspection, breakpoints, and code patching directly within the emulated environment, making it a powerful tool for understanding and analyzing legacy software. It focuses on achieving high accuracy in emulation rather than speed, aiming to facilitate deep analysis of the original code's behavior.
Hacker News users discussed Spice86's unique approach to x86 emulation, focusing on its dynamic recompilation for real mode and its use in reverse engineering. Some praised its ability to handle complex scenarios like self-modifying code and TSR programs, features often lacking in other emulators. The project's open-source nature and stated goal of aiding reverse engineering efforts were also seen as positives. Several commenters expressed interest in trying Spice86 for analyzing older DOS programs and games. There was also discussion comparing it to existing tools like DOSBox and QEMU, with some suggesting Spice86's targeted focus on real mode might offer advantages for specific reverse engineering tasks. The ability to integrate custom C# code for dynamic analysis was highlighted as a potentially powerful feature.
The Elastic blog post details how optimistic concurrency control in Lucene can lead to infrequent but frustrating "document missing" exceptions. These occur when multiple processes try to update the same document simultaneously. Lucene employs versioning to detect these conflicts, preventing data corruption, but the rejected update manifests as the exception. The post outlines strategies for handling this, primarily through retrying the update operation with the latest document version. It further explores techniques for identifying the conflicting processes using debugging tools and log analysis, ultimately aiding in preventing frequent conflicts by optimizing application logic and minimizing the window of contention.
Several commenters on Hacker News discussed the challenges and nuances of optimistic locking, the strategy used by Lucene. One pointed out the inherent trade-off between performance and consistency, noting that optimistic locking prioritizes speed but risks conflicts when multiple writers access the same data. Another commenter suggested using a different concurrency control mechanism like Multi-Version Concurrency Control (MVCC), citing its potential to avoid the update conflicts inherent in optimistic locking. The discussion also touched on the importance of careful implementation, highlighting how overlooking seemingly minor details can lead to difficult-to-debug concurrency issues. A few users shared their personal experiences with debugging similar problems, emphasizing the value of thorough testing and logging. Finally, the complexity of Lucene's internals was acknowledged, with one commenter expressing surprise at the described issue existing within such a mature project.
The blog post "It is not a compiler error (2017)" explores a subtle bug related to floating-point comparisons in C++. The author demonstrates how seemingly innocuous code, involving comparing a floating-point value against zero after decrementing it in a loop, can lead to unexpected infinite loops. This arises because floating-point numbers have limited precision, and repeated subtraction of a small value from a larger one might never exactly reach zero. The post emphasizes the importance of understanding floating-point limitations and suggests using alternative comparison methods, like checking if the value is within a small tolerance of zero (epsilon comparison), or restructuring the loop condition to avoid direct equality checks with floating-point numbers.
HN users discuss integer overflow in C/C++, focusing on its undefined behavior and the security implications. Some highlight the dangers, especially in situations where the compiler optimizes away overflow checks based on the assumption that it can't happen. Others point out that -fwrapv can enforce predictable wrapping behavior, making code safer but potentially slower. The discussion also touches on how static analyzers can help catch these issues, and the inherent difficulties in ensuring complete safety in C/C++ due to the language's flexibility. A few commenters mention alternatives like Rust, which offer stricter memory safety and overflow handling. One commenter shares a personal anecdote about an integer underflow vulnerability they found in a C++ program, emphasizing the real-world impact of these seemingly theoretical problems.
The blog post details troubleshooting a Hetzner server experiencing random reboots. The author initially suspected power issues, utilizing powerstat to monitor power consumption and sensors to check temperature readings, but these revealed no anomalies. Ultimately, dmidecode identified a faulty RAM module, which, after replacement, resolved the instability. The post highlights the importance of systematic hardware diagnostics when dealing with seemingly inexplicable server issues, emphasizing the usefulness of these specific tools for identifying the root cause.
The Hacker News comments generally praise the author's detailed approach to debugging hardware issues, particularly appreciating the use of readily available tools like ipmitool and dmidecode. Several commenters share similar experiences with Hetzner, mentioning frequent hardware failures, especially with older hardware. Some discuss the complexities of diagnosing such issues, highlighting the challenges of distinguishing between software and hardware problems. One commenter suggests Hetzner's older hardware might be the root cause of the instability, while another offers advice on using dedicated IPMI hardware for better remote management. The thread also touches on the pros and cons of Hetzner's pricing compared to its reliability, with some feeling the price doesn't justify the frequency of issues. A few commenters question the author's conclusion about PSU failure, suggesting other potential culprits like RAM or motherboard issues.
The author dramatically improved the debug build speed of their C++ project, achieving up to 100x faster execution. The primary culprit was excessive logging, specifically the use of a logging library with a slow formatting implementation, exacerbated by unnecessary string formatting even when logs weren't being written. By switching to a faster logging library (spdlog), deferring string formatting until after log level checks, and optimizing other minor inefficiencies, they brought their debug build performance to a usable level, allowing for significantly faster iteration times during development.
Commenters on Hacker News largely praised the author's approach to optimizing debug builds, emphasizing the significant impact build times have on developer productivity. Several highlighted the importance of the described techniques, like using link-time optimization (LTO) and profile-guided optimization (PGO) even in debug builds, challenging the common trade-off between debuggability and speed. Some shared similar experiences and alternative optimization strategies, such as using pre-compiled headers (PCH) and unity builds, or employing tools like ccache. A few also pointed out potential downsides, like increased memory usage with LTO, and the need to balance optimization with the ability to effectively debug. The overall sentiment was that the author's detailed breakdown offered valuable insights and practical solutions for a common developer pain point.
The post "Debugging an Undebuggable App" details the author's struggle to debug a performance issue in a complex web application where traditional debugging tools were ineffective. The app, built with a framework that abstracted away low-level details, hid the root cause of the problem. Through careful analysis of network requests, the author discovered that an excessive number of API calls were being made due to a missing cache check within a frequently used component. Implementing this check dramatically improved performance, highlighting the importance of understanding system behavior even when convenient debugging tools are unavailable. The post emphasizes the power of basic debugging techniques like observing network traffic and understanding the application's architecture to solve even the most challenging problems.
Hacker News users discussed various aspects of debugging "undebuggable" systems, particularly in the context of distributed systems. Several commenters highlighted the importance of robust logging and tracing infrastructure as a primary tool for understanding these complex environments. The idea of designing systems with observability in mind from the outset was emphasized. Some users suggested techniques like synthetic traffic generation and chaos engineering to proactively identify potential failure points. The discussion also touched on the challenges of debugging in production, the value of experienced engineers in such situations, and the potential of emerging tools like eBPF for dynamic tracing. One commenter shared a personal anecdote about using printf debugging effectively in a complex system. The overall sentiment seemed to be that while perfectly debuggable systems are likely impossible, prioritizing observability and investing in appropriate tools can significantly reduce debugging pain.
The Flea-Scope is a low-cost, open-source USB oscilloscope, logic analyzer, and arbitrary waveform generator. Designed with affordability and accessibility in mind, it utilizes a Cypress FX2LP microcontroller and features a minimalist design detailed in a comprehensive, publicly available PDF. The document covers hardware schematics, firmware, software, and usage instructions, enabling users to build, modify, and understand the device completely. The Flea-Scope aims to be a practical tool for hobbyists, students, and professionals seeking a basic, yet versatile electronic test instrument.
Commenters on Hacker News generally praised the Flea-Scope for its affordability and open-source nature, finding it a compelling option for hobbyists and those needing a basic tool. Several pointed out its limitations compared to professional equipment, particularly regarding bandwidth and sample rate. Some discussed potential improvements, including using a faster microcontroller and enhancing the software. The project's use of a Cypress FX2 chip was highlighted, with some expressing nostalgia for it. A few users shared personal experiences using similar DIY oscilloscopes, and others questioned the practicality of its low bandwidth for certain applications. The overall sentiment was positive, viewing the Flea-Scope as a valuable educational tool and a testament to what can be achieved with limited resources.
The blog post details troubleshooting high CPU usage attributed to the writeback process in a Linux kernel. After initial investigations pointed towards cgroups and specifically the cpu.cfs_period_us parameter, the author traced the issue to a tight loop within the cgroup writeback mechanism. This loop was triggered by a large number of cgroups combined with a specific workload pattern. Ultimately, increasing the dirty_expire_centisecs kernel parameter, which controls how long dirty data stays in memory before being written to disk, provided the solution by significantly reducing the writeback activity and lowering CPU usage.
Commenters on Hacker News largely discuss practical troubleshooting steps and potential causes of the high CPU usage related to cgroups writeback described in the linked blog post. Several suggest using tools like perf to profile the kernel and pinpoint the exact function causing the issue. Some discuss potential problems with the storage layer, like slow I/O or a misconfigured RAID, while others consider the possibility of a kernel bug or an interaction with specific hardware or drivers. One commenter shares a similar experience with NFS and high CPU usage related to writeback, suggesting a potential commonality in networked filesystems. Several users emphasize the importance of systematic debugging and isolation of the problem, starting with simpler checks before diving into complex kernel analysis.
This project introduces an experimental VS Code extension that allows Large Language Models (LLMs) to actively debug code. The LLM can set breakpoints, step through execution, inspect variables, and evaluate expressions, effectively acting as a junior developer aiding in the debugging process. The extension aims to streamline debugging by letting the LLM analyze the code and runtime state, suggest potential fixes, and even autonomously navigate the debugging session to identify the root cause of errors. This approach promises a potentially more efficient and insightful debugging experience by leveraging the LLM's code understanding and reasoning capabilities.
Hacker News users generally expressed interest in the LLM debugger extension for VS Code, praising its innovative approach to debugging. Several commenters saw potential for expanding the tool's capabilities, suggesting integration with other debuggers or support for different LLMs beyond GPT. Some questioned the practical long-term applications, wondering if it would be more efficient to simply improve the LLM's code generation capabilities. Others pointed out limitations like the reliance on GPT-4 and the potential for the LLM to hallucinate solutions. Despite these concerns, the overall sentiment was positive, with many eager to see how the project develops and explores the intersection of LLMs and debugging. A few commenters also shared anecdotes of similar debugging approaches they had personally experimented with.
VS Code's remote SSH functionality can lead to unexpected and frustrating behavior due to its complex key management. The editor automatically adds keys to its internal SSH agent, potentially including keys you didn't intend to use for a particular connection. This often results in authentication failures, especially when using multiple keys for different servers. Even manually removing keys from the agent within VS Code doesn't reliably solve the issue because the editor might re-add them. The blog post recommends disabling VS Code's agent and using the system SSH agent instead for more predictable and manageable SSH connections.
HN users generally agree that VS Code's remote SSH behavior is confusing and frustrating. Several commenters point out that the "agent forwarding" option doesn't work as expected, leading to issues with key-based authentication. Some suggest the core problem stems from VS Code's reliance on its own SSH implementation instead of leveraging the system's SSH, causing conflicts and unexpected behavior. Workarounds like using the Remote - SSH: Kill VS Code Server on Host... command or configuring VS Code to use the system SSH are mentioned, along with the observation that the VS Code team seems aware of the issues and is working on improvements. A few commenters share similar struggles with other IDEs and remote development tools, suggesting this isn't unique to VS Code.
The blog post argues for a more holistic approach to debugging and performance analysis by combining various tools and data sources. It emphasizes the limitations of isolated tools like memory profilers, call graphs, exception reports, and telemetry, advocating instead for integrating them to provide "system-wide context." This richer context allows developers to understand not only what went wrong, but also why and how, enabling more effective and efficient troubleshooting. The post uses a fictional scenario involving a slow web service to illustrate how correlating data from different tools can pinpoint the root cause of a performance issue, which in their example turns out to be an unexpected interaction between a third-party library and the application's caching strategy.
Hacker News users discussed the blog post about system-wide context, focusing primarily on the practical challenges of implementing such a system. Several commenters pointed out the difficulty of handling circular dependencies and the potential performance overhead, particularly in garbage-collected languages. Some suggested alternative approaches like structured logging and distributed tracing, while others questioned the overall value proposition compared to existing debugging tools. The complexity of integrating with different programming languages and the potential for information overload were also raised as concerns. A few commenters expressed interest in the idea but acknowledged the significant engineering effort required to make it a reality. One compelling comment highlighted the potential benefits for debugging complex, distributed systems, where understanding the interplay of different components is crucial.
Summary of Comments ( 43 )
https://news.ycombinator.com/item?id=43401179
HN commenters largely praised the article for its practical, experience-driven advice. Several highlighted the importance of understanding component tolerances and derating, echoing the author's emphasis on designing for real-world conditions, not just theoretical values. Some shared their own anecdotes about failures caused by overlooking these factors, reinforcing the article's points. A few users also appreciated the focus on simple, robust designs, emphasizing that over-engineering can introduce unintended vulnerabilities. One commenter offered additional resources on grounding and shielding, further supplementing the article's guidance on mitigating noise and interference. Overall, the consensus was that the article provided valuable insights for both beginners and experienced engineers.
The Hacker News post "Designing Electronics That Work" has generated several interesting comments discussing the linked article's perspective on robust electronic design.
One commenter highlights the importance of designing for the "nominal plus variation" rather than just the nominal value, emphasizing that components will deviate from their ideal specifications. They also suggest considering how components age and drift over time, adding another layer of complexity to robust design. This comment underscores the practical challenges of ensuring consistent performance in real-world applications.
Another commenter discusses the critical aspect of power supply filtering, pointing out that noise and ripple on power rails can significantly impact circuit behavior. They emphasize the necessity of understanding the power distribution network (PDN) and using appropriate filtering techniques to mitigate these issues. This comment reinforces the importance of considering the entire system, not just individual components, when designing for reliability.
One user shares a personal anecdote about a design flaw discovered late in the production process, emphasizing the significant cost savings that could have been achieved with earlier testing. They highlight the trade-off between the expense of thorough testing and the potentially much larger costs associated with fixing issues later on. This comment serves as a practical reminder of the economic benefits of robust design practices.
The topic of "worst-case analysis" also arises in the comments, with users debating its merits and limitations. Some argue that a purely worst-case approach can lead to over-designed and expensive circuits. Others point out that defining the "worst-case" scenario can be challenging and that unforeseen factors can still cause problems. This discussion underscores the need for a balanced approach, combining worst-case analysis with other design and testing methodologies.
Another comment emphasizes the importance of thermal considerations in electronic design, pointing out that temperature variations can significantly impact component performance and reliability. They advocate for careful thermal management, including proper heatsinking and airflow, to ensure long-term stability. This comment highlights yet another critical aspect of designing robust electronics.
Finally, there's a discussion about the value of simulation tools in the design process. Commenters generally agree that simulation can be helpful, but caution against relying on it exclusively. They stress the importance of real-world testing and prototyping to validate simulation results and identify unforeseen issues. This discussion reinforces the idea that a combination of theoretical analysis and practical experimentation is crucial for successful electronic design.
In summary, the comments on the Hacker News post offer valuable insights into the complexities of designing robust electronics. They highlight the importance of considering component variations, power supply integrity, thermal management, and the limitations of simulation, emphasizing a practical and holistic approach to design.