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.
The blog post details how to set up Kleene, a lightweight container management system, on FreeBSD. It emphasizes Kleene's simplicity and ease of use compared to larger, more complex alternatives like Kubernetes. The guide walks through installing Kleene, configuring a network bridge for container communication, and deploying a sample Nginx container. It also covers building custom container images with img and highlights Kleene's ability to manage persistent storage volumes, showcasing its suitability for self-hosting applications on FreeBSD servers. The post concludes by pointing to Kleene's potential as a practical container solution for users seeking a less resource-intensive option than Docker or Kubernetes.
HN commenters generally express interest in Kleene and its potential, particularly for FreeBSD users seeking lighter-weight alternatives to Docker. Some highlight its jail-based approach as a security advantage. Several commenters discuss the complexities of container management and the trade-offs between different tools, with some suggesting that a simpler approach might be preferable for certain use cases. One commenter notes the difficulty in finding clear, up-to-date documentation for FreeBSD containerization, praising the linked article for addressing this gap. There's also a brief thread discussing the benefits of ZFS for container storage. Overall, the comments paint Kleene as a promising tool worth investigating, especially for those already working within the FreeBSD ecosystem.
PgAssistant is an open-source command-line tool designed to simplify PostgreSQL performance analysis and optimization. It collects key performance indicators, configuration settings, and schema details, presenting them in a user-friendly format. PgAssistant then provides tailored recommendations for improvement based on best practices and identified bottlenecks. This allows developers to quickly diagnose issues related to slow queries, inefficient indexing, or suboptimal configuration parameters without deep PostgreSQL expertise.
HN users generally praised pgAssistant, calling it a "great tool" and highlighting its usefulness for visualizing PostgreSQL performance. Several commenters appreciated its ability to present complex information in a user-friendly way, particularly for developers less experienced with database administration. Some suggested potential improvements, such as adding support for more metrics, integrating with other tools, and providing deeper analysis capabilities. A few users mentioned similar existing tools, like pganalyze and pgHero, drawing comparisons and discussing their respective strengths and weaknesses. The discussion also touched on the importance of query optimization and the challenges of managing PostgreSQL performance in general.
"Do-nothing scripting" advocates for a gradual approach to automation. Instead of immediately trying to fully automate a complex task, you start by writing a script that simply performs the steps manually, echoing each command to the screen. This allows you to document the process precisely and identify potential issues without the risk of automated errors. As you gain confidence, you incrementally replace the manual execution of each command within the script with its automated equivalent. This iterative process minimizes disruption, allows for easy rollback, and makes the transition to full automation smoother and more manageable.
Hacker News users generally praised the "do-nothing scripting" approach as a valuable tool for understanding existing processes before automating them. Several commenters highlighted the benefit of using this technique to gain stakeholder buy-in and build trust, particularly when dealing with complex or mission-critical systems. Some shared similar experiences or suggested alternative methods like using strace or dtrace. One commenter suggested incorporating progressive logging to further refine the script's insights over time, while another cautioned against over-reliance on this approach, advocating for a move towards true automation once sufficient understanding is gained. Some skepticism was expressed regarding the practicality for highly interactive processes. Overall, the commentary reflects strong support for the core idea as a practical step toward thoughtful and effective automation.
Observability and FinOps are increasingly intertwined, and integrating them provides significant benefits. This blog post highlights the newly launched Vantage integration with Grafana Cloud, which allows users to combine cost data with observability metrics. By correlating resource usage with cost, teams can identify optimization opportunities, understand the financial impact of performance issues, and make informed decisions about resource allocation. This integration enables better control over cloud spending, faster troubleshooting, and more efficient infrastructure management by providing a single pane of glass for both technical performance and financial analysis. Ultimately, it empowers organizations to achieve a balance between performance and cost.
HN commenters generally express skepticism about the purported synergy between FinOps and observability. Several suggest that while cost visibility is important, integrating FinOps directly into observability platforms like Grafana might be overkill, creating unnecessary complexity and vendor lock-in. They argue for maintaining separate tools and focusing on clear cost allocation tagging strategies instead. Some also point out potential conflicts of interest, with engineering teams prioritizing performance over cost and finance teams lacking the technical expertise to interpret complex observability data. A few commenters see some value in the integration for specific use cases like anomaly detection and right-sizing resources, but the prevailing sentiment is one of cautious pragmatism.
The GNU Make Standard Library (GMSL) offers a collection of reusable Makefile functions designed to simplify common build tasks and promote best practices in GNU Make projects. It provides functions for tasks like finding files, managing dependencies, working with directories, handling shell commands, and more. By incorporating GMSL, Makefiles can become more concise, readable, and maintainable, reducing boilerplate and improving consistency across projects. The library is designed to be modular, allowing users to include only the functions they need.
Hacker News users discussed the GNU Make Standard Library (GMSL), mostly focusing on its potential usefulness and questioning its necessity. Some commenters appreciated the idea of standardized functions for common Make tasks, finding it could improve readability and reduce boilerplate. Others argued that existing solutions like shell scripts or including Makefiles suffice, viewing GMSL as adding unnecessary complexity. The discussion also touched upon the discoverability of such a library and whether the chosen license (GPLv3) would limit its adoption. Some expressed concern about the potential for GPLv3 to "infect" projects using the library. Finally, a few users pointed out alternatives like using a higher-level build system or other scripting languages to replace Make entirely.
Perforator is an open-source, cluster-wide profiling tool developed by Yandex for analyzing performance in large data centers. It uses hardware performance counters to collect low-overhead, detailed performance data across thousands of machines simultaneously, aiming to identify performance bottlenecks and optimize resource utilization. The tool offers a web interface for visualization and analysis, and allows users to drill down into specific nodes and processes for deeper investigation. Perforator supports various profiling modes, including CPU, memory, and I/O, and can be integrated with existing monitoring systems.
Several commenters on Hacker News expressed interest in Perforator, particularly its ability to profile at scale and its low overhead. Some questioned the choice of Python for the agent, citing potential performance issues, while others appreciated its ease of use and integration with existing Python-based infrastructure. A few commenters compared it favorably to existing tools like BCC and eBPF, highlighting Perforator's distributed nature as a key differentiator. The discussion also touched on the challenges of profiling in production environments, with some sharing their experiences and suggesting potential improvements to Perforator. Overall, the comments indicated a positive reception to the tool, with many eager to try it in their own environments.
Distr is an open-source platform designed to simplify the distribution and management of containerized applications within on-premises environments. It provides a streamlined way to package, deploy, and update applications across a cluster of machines, abstracting away the complexities of Kubernetes. Distr aims to offer a user-friendly experience, allowing developers to focus on building and shipping their applications without needing deep Kubernetes expertise. It achieves this through a declarative configuration approach and built-in features for rolling updates, versioning, and rollback capabilities.
Hacker News users generally expressed interest in Distr, praising its focus on simplicity and GitOps approach for on-premise deployments. Several commenters compared it favorably to more complex tools like ArgoCD, highlighting its potential for smaller-scale deployments where a lighter-weight solution is desired. Some raised questions about specific features like secrets management and rollback capabilities, along with its ability to handle more complex deployment scenarios. Others expressed skepticism about the need for a new tool in this space, questioning its differentiation from existing solutions and expressing concerns about potential vendor lock-in, despite it being open-source. There was also discussion around the limited documentation and the project's early stage of development.
Actionate brings the power of GitHub Actions directly into JetBrains IDEs like IntelliJ IDEA and PyCharm. It allows developers to run and debug individual workflow jobs locally, simplifying the development and testing process for GitHub Actions. This eliminates the need for constant commits and push cycles to verify workflow changes, streamlining development and providing a more efficient workflow within the familiar IDE environment. By leveraging the local development environment, Actionate helps catch errors early and accelerates the iteration cycle for creating and refining GitHub Actions workflows.
Hacker News users generally expressed interest in Actionate, finding the concept intriguing and useful for automating tasks within JetBrains IDEs. Some questioned the practical advantages over existing solutions like using the command line directly or scripting within the IDEs. Concerns were raised about performance overhead and potential instability due to relying on Docker. A suggestion was made to support background execution for improved usability. Others pointed out that IDE features like macros and built-in task runners could often fulfill similar automation needs. The security implications of running arbitrary code pulled from GitHub Actions were also discussed. Overall, while acknowledging the tool's potential, many commenters advocated for simpler solutions for common IDE automation tasks.
Bunster is a tool that compiles Bash scripts into standalone, statically-linked executables. This allows for easy distribution and execution of Bash scripts without requiring a separate Bash installation on the target system. It achieves this by embedding a minimal Bash interpreter and necessary dependencies within the generated executable. This makes scripts more portable and user-friendly, especially for scenarios where installing dependencies or ensuring a specific Bash version is impractical.
Hacker News users discussed Bunster's novel approach to compiling Bash scripts, expressing interest in its potential while also raising concerns. Several questioned the practical benefits over existing solutions like shc or containers, particularly regarding dependency management and debugging complexity. Some highlighted the inherent limitations of Bash as a scripting language compared to more robust alternatives for complex applications. Others appreciated the project's ingenuity and suggested potential use cases like simplifying distribution of simple scripts or bypassing system-level restrictions on scripting. The discussion also touched upon the performance implications of this compilation method and the challenges of handling Bash's dynamic nature. A few commenters expressed curiosity about the inner workings of the compilation process and its handling of external commands.
Writing Kubernetes controllers can be deceptively complex. While the basic control loop seems simple, achieving reliability and robustness requires careful consideration of various pitfalls. The blog post highlights challenges related to idempotency and ensuring actions are safe to repeat, handling edge cases and unexpected behavior from the Kubernetes API, and correctly implementing finalizers for resource cleanup. It emphasizes the importance of thorough testing, covering various failure scenarios and race conditions, to avoid unintended consequences in a distributed environment. Ultimately, successful controller development necessitates a deep understanding of Kubernetes' eventual consistency model and careful design to ensure predictable and resilient operation.
HN commenters generally agree with the author's points about the complexities of writing Kubernetes controllers. Several highlight the difficulty of reasoning about eventual consistency and distributed systems, emphasizing the importance of idempotency and careful error handling. Some suggest using higher-level tools and frameworks like Metacontroller or Operator SDK to simplify controller development and avoid common pitfalls. Others discuss specific challenges like leader election, garbage collection, and the importance of understanding the Kubernetes API and its nuances. A few commenters shared personal experiences and anecdotes reinforcing the article's claims about the steep learning curve and potential for unexpected behavior in controller development. One commenter pointed out the lack of good examples, highlighting the need for more educational resources on this topic.
HyperDX, a Y Combinator-backed company, is hiring engineers to build an open-source observability platform. They're looking for individuals passionate about open source, distributed systems, and developer tools to join their team and contribute to projects involving eBPF, Wasm, and cloud-native technologies. The roles offer the opportunity to shape the future of observability and work on a product used by a large community. Experience with Go, Rust, or C++ is desired, but a strong engineering background and a willingness to learn are key.
Hacker News users discuss HyperDX's open-source approach, questioning its viability given the competitive landscape. Some express skepticism about building a sustainable business model around open-source observability tools, citing the dominance of established players and the difficulty of monetizing such products. Others are more optimistic, praising the team's experience and the potential for innovation in the space. A few commenters offer practical advice regarding specific technologies and go-to-market strategies. The overall sentiment is cautious interest, with many waiting to see how HyperDX differentiates itself and builds a successful business.
Sigstore aims to solve the problem of software supply chain security by making it easy to sign software artifacts and verify those signatures. It provides free tooling and a public good transparency log, enabling developers to sign releases with short-lived certificates tied to their identities (e.g., GitHub and email). This allows users to easily verify the provenance and integrity of software, ensuring that it hasn't been tampered with and genuinely originates from the claimed source. Sigstore simplifies the complex process of code signing, removing the need for managing long-lived keys and complicated infrastructure. This makes it significantly more practical for developers to secure their software supply chains and builds trust with end users.
Hacker News commenters generally expressed strong support for Sigstore and its mission of improving software supply chain security. Several praised its ease of use and integration with existing tools, noting the significantly lowered barrier to entry for signing releases compared to traditional methods. Some highlighted the importance of key transparency and the clever use of OpenID Connect for identity verification. A few commenters discussed the potential impact on various ecosystems like Debian and Python, expressing hope for wider adoption and speculating on the future development of the project. Concerns were raised about the reliance on centralized services and potential single points of failure, but these were often met with counter-arguments about the federated nature of OpenID and the transparency of the log. Some users questioned the long-term viability of free certificate issuance, and others debated the nuances of different signing models and their relative security implications.
JReleaser simplifies and automates project releases across various platforms. It streamlines the process of creating release artifacts, generating checksums, and publishing them to a variety of distribution channels, including package managers like Homebrew, SDKMAN!, and Chocolatey, as well as artifact repositories like Maven Central, and GitHub Releases. JReleaser supports multiple project types (Java, Go, Kotlin, etc.) and offers flexible configuration through its declarative approach, allowing developers to define release logic in a centralized manner and avoid tedious manual steps. This frees up developers to focus on coding rather than deployment logistics.
Hacker News users generally reacted positively to JReleaser, praising its simplicity and ease of use compared to more complex tools. Several commenters appreciated its support for various platforms and package managers, finding it particularly useful for Java projects but also applicable to other languages. Some pointed out potential alternatives like goreleaser, while others discussed the benefits of standardizing release processes. A few users inquired about specific features, such as signing and checksum generation, while others shared their personal experiences using JReleaser for their own projects. The overall sentiment leaned towards JReleaser being a valuable tool for streamlining and automating the release process.
The author details a frustrating experience with GitHub Actions where a seemingly simple workflow to build and deploy a static website became incredibly complex and time-consuming due to caching issues. Despite attempting various caching strategies and workarounds, builds remained slow and unpredictable, ultimately leading to increased costs and wasted developer time. The author concludes that while GitHub Actions might be suitable for straightforward tasks, its caching mechanism's unreliability makes it a poor choice for more complex projects, especially those involving static site generation. They ultimately opted to migrate to a self-hosted solution for improved control and predictability.
Hacker News users generally agreed with the author's sentiment about GitHub Actions' complexity and unreliability. Many shared similar experiences with flaky builds, obscure error messages, and difficulty debugging. Several commenters suggested exploring alternatives like GitLab CI, Drone CI, or self-hosted runners for more control and predictability. Some pointed out the benefits of GitHub Actions, such as its tight integration with GitHub and the availability of pre-built actions, but acknowledged the frustrations raised in the article. The discussion also touched upon the trade-offs between convenience and control when choosing a CI/CD solution, with some arguing that the ease of use initially offered by GitHub Actions can be overshadowed by the difficulties encountered as projects grow more complex. A few users offered specific troubleshooting tips or workarounds for common issues, highlighting the community-driven nature of problem-solving around GitHub Actions.
isd is an interactive command-line tool designed to simplify working with systemd units. It provides a TUI (terminal user interface) that allows users to browse, filter, start, stop, restart, enable, disable, and edit unit files, as well as view their logs and status in real-time, all within an intuitive and interactive environment. This aims to offer a more user-friendly alternative to traditional command-line tools for managing systemd, streamlining common tasks and reducing the need to memorize complex commands.
Hacker News users generally praised the Interactive systemd (ISD) project for its intuitive and user-friendly approach to managing systemd units. Several commenters highlighted the benefits of its visual representation and the ease with which it allows users to start, stop, and restart services, especially compared to the command-line interface. Some expressed interest in specific features like log viewing and real-time status updates. A few users questioned the necessity of a TUI for systemd management, suggesting existing tools like systemctl are sufficient. Others raised concerns about potential security implications and the project's dependency on Python. Despite some reservations, the overall sentiment towards ISD was positive, with many acknowledging its potential as a valuable tool for both novice and experienced Linux users.
Werk is a new build tool designed for simplicity and speed, focusing on task automation and project management. Written in Rust, it uses a declarative TOML configuration file to define commands and dependencies, offering a straightforward alternative to more complex tools like Make, Ninja, or just shell scripts. Werk aims for minimal overhead and predictable behavior, featuring parallel execution, a human-readable configuration format, and built-in dependency management to ensure efficient builds. It's intended to be a versatile tool suitable for various tasks from simple build processes to more complex workflows.
HN users generally praised Werk's simplicity and speed, particularly for smaller projects. Several compared it favorably to tools like Taskfile, Just, and Make, highlighting its cleaner syntax and faster execution. Some expressed concerns about its reliance on Deno and potential lack of Windows support, though the creator clarified that Windows compatibility is planned. Others questioned the long-term viability of Deno itself. Despite some skepticism, the overall reception was positive, with many appreciating the "fresh take" on build tools and its potential as a lightweight alternative to more complex systems. A few users also offered suggestions for improvements, including better error handling and more comprehensive documentation.
The paper "A Taxonomy of AgentOps" proposes a structured classification system for the emerging field of Agent Operations (AgentOps). It defines AgentOps as the discipline of deploying, managing, and governing autonomous agents at scale. The taxonomy categorizes AgentOps challenges across four key dimensions: Agent Lifecycle (creation, deployment, operation, and retirement), Agent Capabilities (perception, planning, action, and communication), Operational Scope (individual, collaborative, and systemic), and Management Aspects (monitoring, control, security, and ethics). This framework aims to provide a common language and understanding for researchers and practitioners, enabling them to better navigate the complex landscape of AgentOps and develop effective solutions for building and managing robust, reliable, and responsible agent systems.
Hacker News users discuss the practicality and scope of the proposed "AgentOps" taxonomy. Some express skepticism about its novelty, arguing that many of the described challenges are already addressed within existing DevOps and MLOps practices. Others question the need for another specialized "Ops" category, suggesting it might contribute to unnecessary fragmentation. However, some find the taxonomy valuable for clarifying the emerging field of agent development and deployment, particularly highlighting the focus on autonomy, continuous learning, and complex interactions between agents. The discussion also touches upon the importance of observability and debugging in agent systems, and the need for robust testing frameworks. Several commenters raise concerns about security and safety, particularly in the context of increasingly autonomous agents.
Summary of Comments ( 16 )
https://news.ycombinator.com/item?id=43090167
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.
The Hacker News post titled "Agent-Less System Monitoring with Elixir Broadway" sparked a small but focused discussion with 5 comments. No single comment overwhelmingly dominated the conversation, but several offered interesting perspectives on the article's topic.
One commenter questioned the term "agent-less," pointing out that while the system described doesn't require installing dedicated agent software on monitored machines, it still relies on SSH access, which functionally acts like an agent. They argued that this approach trades one set of tradeoffs (agent installation and maintenance) for another (managing SSH keys and potential security concerns).
Another comment focused on the choice of Erlang/Elixir for this type of task. They acknowledged the platform's strengths in concurrency and distributed systems but expressed concern about the operational overhead and debugging complexity compared to simpler scripting solutions, especially for smaller deployments. They suggested that the benefits of Elixir might become more pronounced with larger and more complex monitoring setups.
A third commenter praised the article's clear explanation and the elegant approach to building a robust monitoring system with Broadway. They highlighted the benefits of leveraging Elixir's OTP framework for handling failures and ensuring reliability.
The remaining comments were shorter and less substantive. One simply expressed appreciation for the article, while another briefly mentioned using a similar approach with a different technology.
Overall, the comments section, while brief, provided some thoughtful critiques and perspectives on the advantages and disadvantages of the proposed agent-less monitoring approach using Elixir and Broadway. The discussion centered on the practical implications of SSH as an "agent" substitute and the suitability of Elixir/OTP for this kind of task in different scales of deployment.