denet, A lightweight command-line tool for process monitoring in benchmarking and beyond

Ben Carrillo; Izaskun Mallona

arxiv: 2510.13818 · v2 · submitted 2025-09-24 · 💻 cs.PF

denet, A lightweight command-line tool for process monitoring in benchmarking and beyond

Ben Carrillo , Izaskun Mallona This is my paper

Pith reviewed 2026-05-18 15:07 UTC · model grok-4.3

classification 💻 cs.PF

keywords process monitoringresource profilingbenchmarkingLinux toolsCLIbioinformaticsSnakemakeJSONL output

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The pith

denet is a lightweight tool for real-time profiling of CPU, memory, disk I/O, network activity and thread usage across processes and their children.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper presents denet as a lightweight command-line tool for monitoring resource usage of running processes in real time. It tracks CPU, memory, disk I/O, network activity, and threads, including children of the target process, using adaptive sampling to minimize overhead. Output is provided via a colorized CLI or Python API in JSONL format, making the data easy to parse for further analysis. This setup is positioned as particularly helpful for benchmarking and tuning performance in bioinformatics pipelines and similar data-intensive applications on standard Linux systems.

Core claim

The paper introduces denet as an open-source Rust-based utility that provides real-time profiling of running processes. It reports on CPU utilization, memory consumption, disk and network I/O, and thread counts, while supporting recursive monitoring of child processes through adaptive sampling rates. The tool offers both a colorized command-line interface and a Python API, with all output formatted as JSONL records that include performance metrics alongside process metadata such as PID and command. This design targets applications in benchmarking and performance tuning of data-intensive pipelines, with examples including integration into Snakemake workflows in bioinformatics. Most features,,

What carries the argument

denet, a Rust implementation that collects real-time metrics from the Linux /proc filesystem with optional eBPF support, adaptive sampling, and recursive child-process tracking.

Load-bearing premise

The approach assumes that standard Linux interfaces like the /proc filesystem supply accurate and timely resource metrics for processes and children without requiring administrative privileges.

What would settle it

On a standard Linux system without root access, if denet produces missing or inaccurate disk I/O or network metrics for child processes during a test run, the claim of effective non-privileged monitoring would be falsified.

read the original abstract

Summary: denet is a lightweight process monitoring tool providing real-time resource profiling of running processes. It reports CPU, memory, disk I/O, network activity, and thread usage, including recursive child monitoring, with adaptive sampling rates. denet exposes two interfaces: a CLI with colorized output and a Python API. Output format is JSONL. Each record carries performance metrics and process metadata (PID and the executed command). Structured output makes denet suitable for benchmarking and tuning data-intensive pipelines in bioinformatics and beyond. We provide CLI and API examples, including a bioinformatics workflow in Snakemake, showcasing denet's diagnostic properties. Availability and implementation: denet is open-source software released under the GPLv3 terms, and maintained at https://github.com/btraven00/denet. It is implemented in Rust, with Python bindings provided via maturin, and installs from Cargo (cargo install denet) or PyPI (pip install denet). Most functionality does not require administrative privileges, enabling use on cloud platforms, HPC clusters, and standard Linux workstations. Advanced features such as eBPF support may require elevated permissions.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

denet is a straightforward open-source tool for process monitoring with some practical features for benchmarking, but it stays incremental without direct comparisons or overhead data.

read the letter

denet is a new Rust-based CLI and Python tool that tracks CPU, memory, disk, network, and threads on a process and its children, with adaptive sampling and JSONL output meant for benchmarking runs. The main draw is the combination of recursive child monitoring, easy install via cargo or pip, and mostly non-root operation on standard Linux setups, which fits HPC and cloud use cases well. The Snakemake bioinformatics example shows how the structured logs can plug into existing pipelines without much extra work. Releasing the code under GPLv3 on GitHub lets people verify the claims about /proc and optional eBPF access directly. That counts as real value for anyone who has scripted their own monitoring before. The paper does a clean job laying out the interfaces and intended workflow. On the soft side, there are no measurements of denet's own overhead, no accuracy checks against known tools, and no head-to-head with pidstat or similar utilities. For a performance-monitoring artifact, those numbers would make the advantages clearer instead of leaving them as stated features. The contribution is the released program itself rather than a new method or result. This is for people running repeated benchmarks who want parseable logs without heavy dependencies. A reader tuning data pipelines or working in bioinformatics might pick it up and save scripting time. It deserves a serious referee in a tools or software journal because the implementation is concrete and the use case is common, even if the evaluation stays light.

Referee Report

1 major / 2 minor

Summary. The paper introduces denet, a lightweight open-source command-line tool and Python API for real-time process monitoring. It provides detailed resource profiling including CPU usage, memory consumption, disk I/O, network activity, and thread usage, with features for recursive child process monitoring and adaptive sampling rates. Output is in JSONL format to facilitate integration with benchmarking and data analysis workflows, such as in bioinformatics using Snakemake. The tool is implemented in Rust, with Python bindings, and is installable via Cargo or PyPI under the GPLv3 license. Most features operate without administrative privileges using standard Linux interfaces.

Significance. Should the implementation match the description, denet offers a practical solution for structured process monitoring in environments where low overhead and non-privileged access are important, such as shared HPC systems and cloud instances. The dual CLI and API design, combined with machine-readable output, positions it well for use in automated benchmarking pipelines. The open-source release enables verification and potential community contributions. Its significance lies in providing an accessible tool rather than in novel theoretical contributions.

major comments (1)

[Abstract] The claim that denet is 'suitable for benchmarking and tuning data-intensive pipelines' would be strengthened by including at least basic quantitative information on the tool's own resource overhead or validation of metric accuracy against known values, as this is central to its proposed use case in performance analysis.

minor comments (2)

Adding citations to related monitoring tools (e.g., pidstat, perf, or psutil) would help readers understand how denet differs from or improves upon existing options.
The availability statement is clear, but specifying the minimum Linux kernel version or dependencies for eBPF support would improve reproducibility.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the thoughtful and constructive comment. We agree that quantitative evidence of denet's low overhead would strengthen the abstract's claim about suitability for benchmarking data-intensive pipelines. We will incorporate basic measurements of the tool's own resource consumption in the revised manuscript.

read point-by-point responses

Referee: [Abstract] The claim that denet is 'suitable for benchmarking and tuning data-intensive pipelines' would be strengthened by including at least basic quantitative information on the tool's own resource overhead or validation of metric accuracy against known values, as this is central to its proposed use case in performance analysis.

Authors: We appreciate this suggestion and will address it directly. In the revised version we will add a short 'Overhead Evaluation' subsection (or paragraph in Results) that reports denet's CPU and memory usage while actively monitoring sample processes of varying intensity. These measurements will be obtained by running denet against itself or against a controlled workload and comparing to baseline /proc readings. This provides concrete support for the 'lightweight' description without requiring new theoretical contributions. Regarding validation of metric accuracy, we note that denet relies on standard Linux interfaces (procfs, sysfs) whose accuracy is documented elsewhere; we will add a brief statement referencing this and inviting users to cross-validate with pidstat or perf, but we consider full independent validation beyond the scope of a tool-description paper. revision: yes

Circularity Check

0 steps flagged

No significant circularity; tool description paper with no derivation chain

full rationale

The manuscript describes a concrete software artifact (denet CLI/Python tool for real-time process monitoring via /proc and optional eBPF) rather than any mathematical derivation, prediction, or fitted result. No equations, self-citations used as load-bearing premises, uniqueness theorems, or ansatzes are present. The central claim is the existence and described functionality of the released open-source tool itself, which is self-contained and externally verifiable by inspecting the GitHub repository and running the software. This matches the default expectation for non-circular tool papers.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The work rests on standard Linux system interfaces for process information and the Rust programming language for implementation; no free parameters, invented entities, or ad-hoc axioms are introduced beyond domain-standard assumptions about OS monitoring APIs.

axioms (1)

domain assumption Linux provides accessible interfaces such as the /proc filesystem for retrieving process metrics without elevated privileges.
Core monitoring functionality depends on these standard OS features being available and reliable across target platforms.

pith-pipeline@v0.9.0 · 5722 in / 1197 out tokens · 54656 ms · 2026-05-18T15:07:40.779183+00:00 · methodology

denet, A lightweight command-line tool for process monitoring in benchmarking and beyond

Core claim

What carries the argument

Load-bearing premise

What would settle it

discussion (0)