DEV.co
Open-Source Observability · iipeace

guider

Guider is a comprehensive system profiling and fault detection tool for Linux and Android that monitors CPU, memory, I/O, and network resources. It provides real-time monitoring, detailed performance analysis, flame graphs, and automated event-driven reporting without requiring external infrastructure.

Source: GitHub — github.com/iipeace/guider
674
GitHub stars
103
Forks
Python
Primary language
GPL-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositoryiipeace/guider
Owneriipeace
Primary languagePython
LicenseGPL-2.0 — OSI-approved
Stars674
Forks103
Open issues26
Latest releaseversions/3.9.9 (2025-05-23)
Last updated2026-07-06
Sourcehttps://github.com/iipeace/guider

What guider is

Guider offers kernel-level tracing via ftrace/perf, continuous monitoring with threshold-based event triggers, browser-based SVG visualization (flame graphs, stacked/line graphs), and command APIs over TCP/UDS. It operates with low overhead, retains data in internal buffers, and supports x86, ARM, and RISC-V architectures across Ubuntu, CentOS, Android, and other Linux-based platforms.

Quickstart

Get the guider source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/iipeace/guider.gitcd guider# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Performance Regression Detection in CI/CD

Use Guider's continuous monitoring and threshold-based alerts to automatically capture detailed reports when CPU load, memory usage, or I/O latency exceed baselines. Event-driven profiling data enables rapid root-cause analysis without streaming overhead.

Android Device Troubleshooting

Leverage native Android logging integration (DLT, syslog) and kernel tracing to diagnose ANRs, battery drain, and thermal throttling. Browser-based flame graphs and visualizations simplify cross-domain correlation analysis.

Embedded/IoT System Optimization

Monitor resource-constrained systems (ARM, AArch64) with minimal overhead. Generate comprehensive reports on peak usage patterns, WSS (working set size), and memory fragmentation for capacity planning and optimization.

Implementation considerations

  • Requires kernel configuration for ftrace, perf events, and eBPF support; verify target kernel version and build flags before deployment.
  • Python-based CLI; dependencies (Python 3, libelf, libc debuginfo) must be pre-installed. Consider package manager availability on target systems.
  • Threshold/event configuration is custom and requires domain knowledge to tune appropriately; poorly tuned rules may generate noise or miss critical issues.
  • Output reports are SVG/browser-viewable but post-processing and integration with external dashboards requires custom tooling via APIs.
  • Memory overhead is described as 'minimal' but actual impact depends on monitoring scope (CPU, memory, I/O, network) and sampling rate; testing on target hardware is necessary.

When to avoid it — and what to weigh

  • Need Real-Time External Data Streaming — Guider is designed for local buffer retention and on-device reporting, not real-time streaming to remote monitoring platforms. If you require live dashboards or centralized metric aggregation, use Prometheus/Grafana or similar.
  • Production SaaS with GPL Compliance Concerns — GPL-2.0 requires source disclosure if modifications are distributed. Integrating Guider into proprietary commercial products may impose licensing obligations. Requires legal review for closed-source deployments.
  • Windows/macOS Primary Development — Guider explicitly lists Windows and macOS as 'Limited Support' and is kernel-dependent. Unsuitable as primary monitoring tool for non-Linux platforms.
  • Zero System Access or Containerized Isolation — Requires kernel access for tracing, ftrace facilities, and perf counters. Cannot operate effectively in restrictive sandbox environments or without CAP_SYS_ADMIN and similar privileges.

License & commercial use

Licensed under GPL-2.0 (GNU General Public License v2.0). GPL-2.0 is a copyleft OSI-approved license requiring source code disclosure and same-license distribution of modifications if software is distributed.

Internal use and evaluation are permitted under GPL-2.0. However, distributing Guider or GPL-derived modifications in proprietary products requires source disclosure and licensing compliance review. Commercial support, warranty, or liability indemnification are not evident in the data provided. Requires legal counsel before embedding in closed-source commercial offerings.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityModerate
DEV.co fitGood
Assessment confidenceHigh
Security considerations

Guider requires elevated privileges (CAP_SYS_ADMIN, ftrace access) to function, expanding the trusted compute base on target systems. Kernel tracing facilities can expose sensitive process and I/O behavior; restrict API access via TCP/UDS authentication and network controls. No explicit security audit, CVE history, or threat model disclosed in provided data. Review kernel and Python dependency versions for known vulnerabilities before production use.

Alternatives to consider

perf / linux-tools

Native kernel profiling tool; lower overhead and no GPL constraint, but less user-friendly and no integrated monitoring/visualization.

Prometheus + Grafana + Node Exporter

Industry-standard observability stack with remote storage, alerting, and dashboards. Better for distributed systems, but requires external infrastructure and lacks deep kernel tracing.

systemtap / eBPF (bpftrace)

Powerful for custom kernel-level tracing and scripting. More flexible than Guider but steeper learning curve and no built-in visualization.

Software development agency

Build on guider with DEV.co software developers

Review kernel compatibility, test threshold configuration on staging systems, and assess GPL-2.0 licensing implications before production deployment. Use Devco's technical team to validate integration points and customize event-driven monitoring workflows.

Talk to DEV.co

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guider FAQ

Can I use Guider in a proprietary product or closed-source commercial application?
GPL-2.0 permits internal use but restricts distribution of modifications without source disclosure. Commercial embedding requires legal review and likely dual licensing or fork maintenance.
Does Guider support real-time streaming to external monitoring platforms?
No. Guider retains data locally and generates on-device reports. It does expose command APIs (TCP/UDS) for integration, but real-time streaming to external servers is not a core design goal.
What kernel versions and Linux distributions are officially supported?
README lists Ubuntu, CentOS, and RHEL as primary targets and Android, webOS, Tizen as supported. Specific kernel version requirements are not detailed in provided data; requires documentation review or community channels.
How much overhead does continuous monitoring add?
Described as 'minimal' for stable continuous operation, but actual impact depends on scope (CPU, memory, I/O, network) and sampling configuration. Testing on target hardware is essential.

Work with a software development agency

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If guider is part of your open-source observability roadmap, our team can implement, customize, migrate, and maintain it.

Evaluate Guider for Your Infrastructure

Review kernel compatibility, test threshold configuration on staging systems, and assess GPL-2.0 licensing implications before production deployment. Use Devco's technical team to validate integration points and customize event-driven monitoring workflows.