The blog post "IO Devices and Latency" explores the significant impact of I/O operations on overall database performance, emphasizing that optimizing queries alone isn't enough. It breaks down the various types of latency involved in storage systems, from the physical limitations of different storage media (like NVMe drives, SSDs, and HDDs) to the overhead introduced by the operating system and file system layers. The post highlights the performance benefits of using direct I/O, which bypasses the OS page cache, for predictable, low-latency access to data, particularly crucial for database workloads. It also underscores the importance of understanding the characteristics of your storage hardware and software stack to effectively minimize I/O latency and improve database performance.
Bcvi allows running a full-screen vi editor session over a limited bandwidth or high-latency connection, such as a serial console or SSH connection with significant lag. It achieves this by using a "back-channel" to send screen updates efficiently. Instead of redrawing the entire screen for every change, bcvi only transmits the differences, leading to a significantly more responsive experience. This makes editing files remotely over constrained connections practical, providing a near-native vi experience even with limited bandwidth. The back-channel can be another SSH connection or even a separate serial port, providing flexibility in setup.
Hacker News users discuss the cleverness and potential uses of bcvi, particularly for embedded systems debugging. Some express admiration for the ingenuity of using the back channel for editing, highlighting its usefulness when other methods are unavailable. Others question the practicality due to potential slowness and limitations, suggesting alternatives like ed. A few commenters reminisce about using similar techniques in the past, emphasizing the historical context of this approach within resource-constrained environments. Some discuss potential security implications, pointing out that the back channel could be vulnerable to manipulation. Overall, the comments appreciate the technical ingenuity while acknowledging the niche appeal of bcvi.
Stats is a free and open-source macOS menu bar application that provides a comprehensive overview of system performance. It displays real-time information on CPU usage, memory, network activity, disk usage, battery health, and fan speeds, all within a customizable and compact menu bar interface. Users can tailor the displayed modules and their appearance to suit their needs, choosing from various graph styles and refresh rates. Stats aims to be a lightweight yet powerful alternative to larger system monitoring tools.
Hacker News users generally praised Stats' minimalist design and useful information display in the menu bar. Some suggested improvements, including customizable refresh rates, more detailed CPU information (like per-core usage), and GPU temperature monitoring for M1 Macs. Others questioned the need for another system monitor given existing options, with some pointing to iStat Menus as a more mature alternative. The developer responded to several comments, acknowledging the suggestions and clarifying current limitations and future plans. Some users appreciated the open-source nature of the project and the developer's responsiveness. There was also a minor discussion around the chosen license (GPLv3).
Summary of Comments ( 128 )
https://news.ycombinator.com/item?id=43355031
Hacker News users discussed the challenges of measuring and mitigating I/O latency. Some questioned the blog post's methodology, particularly its reliance on
fioand the potential for misleading results due to caching effects. Others offered alternative tools and approaches for benchmarking storage performance, emphasizing the importance of real-world workloads and the limitations of synthetic tests. Several commenters shared their own experiences with storage latency issues and offered practical advice for diagnosing and resolving performance bottlenecks. A recurring theme was the complexity of the storage stack and the need to understand the interplay of various factors, including hardware, drivers, file systems, and application behavior. The discussion also touched on the trade-offs between performance, cost, and complexity when choosing storage solutions.The Hacker News post titled "IO Devices and Latency" (linking to a PlanetScale blog post) generated a moderate amount of discussion with several insightful comments.
A recurring theme in the comments is the importance of understanding the different types of latency and how they interact. One commenter points out that the blog post focuses mainly on device latency, but that other forms of latency, such as software overhead and queueing delays, often play a larger role in overall performance. They emphasize that optimizing solely for device latency might not yield significant improvements if these other bottlenecks are not addressed.
Another commenter delves into the complexities of measuring I/O latency, highlighting the differences between average, median, and tail latency. They argue that focusing on average latency can be misleading, as it obscures the impact of occasional high-latency operations, which can significantly degrade user experience. They suggest paying closer attention to tail latency (e.g., 99th percentile) to identify and mitigate the worst-case scenarios.
Several commenters discuss the practical implications of the blog post's findings, particularly in the context of database performance. One commenter mentions the trade-offs between using faster storage devices (like NVMe SSDs) and optimizing database design to minimize I/O operations. They suggest that, while faster storage can help, efficient data modeling and indexing are often more effective for reducing overall latency.
One comment thread focuses on the nuances of different I/O scheduling algorithms and their impact on latency. Commenters discuss the pros and cons of various schedulers (e.g., noop, deadline, cfq) and how they prioritize different types of workloads. They also touch upon the importance of tuning these schedulers to match the specific characteristics of the application and hardware.
Another interesting point raised by a commenter is the impact of virtualization on I/O performance. They explain how virtualization layers can introduce additional latency and variability, especially in shared environments. They suggest carefully configuring virtual machine settings and employing techniques like passthrough or dedicated I/O devices to minimize the overhead.
Finally, a few commenters share their own experiences with optimizing I/O performance in various contexts, offering practical tips and recommendations. These anecdotes provide valuable real-world insights and complement the more theoretical discussions in other comments.