cAdvisor: Container resource usage analysis tool
Daemon for monitoring container resource usage and metrics.
Learn more about cAdvisor
cAdvisor is a container monitoring daemon that gathers resource utilization data from running containers. It operates by collecting metrics on CPU, memory, network, and disk usage, then processes and stores this information in a hierarchical container model. The tool maintains resource isolation parameters, historical usage data, and complete histograms for analysis. cAdvisor is commonly deployed as a standalone daemon, within Docker containers, or as a Kubernetes daemonset to monitor container performance across individual machines or entire clusters.
Hierarchical Container Abstraction
Native lmctfy-based container model represents nested container structures without runtime-specific code. Supports Docker, containerd, and other runtimes through a unified interface that preserves container relationships and resource hierarchies.
Multi-Interface Metric Export
Exposes metrics through web UI, versioned REST API, and pluggable storage backends simultaneously. Integrates with Prometheus, InfluxDB, or custom pipelines without choosing a single monitoring stack.
Dual-Scope Resource Tracking
Monitors both per-container metrics and aggregate host-level statistics simultaneously. Correlate container behavior with system-wide resource pressure for comprehensive performance analysis.
import requests
# Query cAdvisor HTTP API for container stats
response = requests.get('http://localhost:8080/api/v1.3/docker/<container_id>')
container_stats = response.json()
cpu_usage = container_stats['stats'][0]['cpu']['usage']['total']
memory_usage = container_stats['stats'][0]['memory']['usage']
print(f"CPU: {cpu_usage}, Memory: {memory_usage}")This patch release fixes a critical nil pointer dereference bug in the Docker integration when GraphDriver is nil.
- –docker: fix nil pointer dereference when GraphDriver is nil
This patch release fixes issues with the entrypoint and healthcheck scripts in the cadvisor container.
- –Fixing entrypoint- and healthcheck script in container
This release drops support for older Docker versions, adds s390x CPU topology exposure, and improves container registry references.
- –docker versions older than 25.0 are no longer supported
- –Expose s390x CPU Topology to Prometheus
- –Replace references to docker registry gcr.io with ghcr.io
- –fix: docker working even without containerd
- –feat: add standard deviation in derived metrics
Related Repositories
Discover similar tools and frameworks used by developers
AWX
Django-based control plane for centralized Ansible management.
ProxmoxVE
Bash scripts for automated Proxmox LXC/VM provisioning.
Setup Node
Node.js version management and dependency caching for workflows.
Uptime Kuma
Node.js application monitoring HTTP, TCP, DNS, and ping endpoints.
Podman
Daemonless OCI container management with Docker-compatible CLI and rootless execution support.
Related Reading
Guides and comparisons from the Greptile content library
Best AI Code Review Tools for GitHub
Top-rated AI code review tools for GitHub teams in 2025. Compare features, pricing, and accuracy to find the perfect fit for faster PR reviews and bulletproof code quality.
Best Developer Productivity Tools in 2026
The best developer productivity tools in 2026, compared by the workflow problem they solve: code review, autocomplete, AI-native editing, terminal agents, code search, observability, and security.
10 Powerful Code Quality Tools That Catch Bugs Before Deployment
We tested 10 code quality tools that catch bugs before production. Detailed comparison with real-world examples, pricing, and ROI analysis for dev teams.
Choosing the Right Code Review Tool: Better Alternatives to Graphite AI
A breakdown of the best alternatives to Graphite for code reviews. Compare AI tools like Trag, open-source solutions like Gerrit, and database-focused platforms like Visual Expert.