google/cadvisor

Features

• Container Monitoring - Functions as a daemon that collects and exports CPU, memory, network, and disk usage statistics from containers.
• Control-Group-Based Resource Management - Analyzes the Linux control groups virtual filesystem to track CPU, memory, and filesystem statistics.
• Data Exposure - Exposes gathered resource data through a JSON REST API for integration with external monitoring tools.
• System Resource APIs - Provides an interface that exposes internal container and machine resource states as structured data.
• Statistics APIs - Provides a remote API to share raw and processed container statistics with external monitoring clients.
• Container Metric Collectors - Provides a client-facing API for retrieving resource usage statistics and health metrics from containers.
• Container Runtime Discovery - Detects active containers by scanning filesystem paths across multiple different container runtime implementations.
• Runtime Discovery - Automatically detects and monitors containers managed by various runtimes and orchestrators.
• Telemetry Tools - Discovers and monitors containers across various runtimes to track hardware and software performance.
• Cgroup Resource Analyzers - Analyzes Linux control groups to provide deep visibility into container resource consumption and limits.
• Metrics Exporters - Pushes collected telemetry and resource metrics to external backends for long-term analysis.
• Kubernetes Monitors - Provides comprehensive resource tracking and health monitoring for nodes and containers within Kubernetes clusters.
• Performance Metrics APIs - Implements a programmatic interface allowing external tools to retrieve raw and processed performance statistics.
• Telemetry Exporters - Forwards real-time container resource statistics to external storage and analysis platforms.
• Containerized Deployments - Supports execution as a container image with host volume mappings to observe system states.
• DaemonSet Deployment Controllers - Utilizes the DaemonSet deployment pattern to ensure local data collection on every cluster node.
• Kubernetes Deployments - Supports deployment across Kubernetes clusters using a DaemonSet for node-level observability.
• Standalone Binaries - Can be executed as a standalone static binary without external dependencies.
• Out-of-Memory Analysis - Monitors kernel logs and cgroup events to identify and report out-of-memory kill events.
• Recursive Data Collection - Provides the ability to aggregate resource usage for a target container and all its sub-containers recursively.
• Kernel Event Tracers - Integrates with kernel perf events to gather low-level hardware events and CPU performance counters.
• Hardware Monitoring Tools - Monitors low-level hardware events, including NUMA statistics and hugepages via core and uncore monitoring.
• Hardware Performance Monitoring - Measures low-level kernel perf events to provide aggregated or per-CPU hardware performance data.
• Host Hardware Analysis Tools - Provides an API to retrieve detailed machine metadata including CPU topology and memory capacity.
• Metrics Visualizers - Ships a built-in web interface for real-time visualization of resource usage and machine specifications.
• Prometheus-Based Metric Exporters - Exposes container and host resource data as a Prometheus-compatible metrics exporter.
• Traffic Monitoring Tools - Collects detailed network statistics including TCP and UDP metrics across various device types.
• Container Infrastructure - Tool for analyzing resource usage of running containers.
• Data Collection Agents - Analyze resource usage of running containers.
• Monitoring and Logging - Analysis of resource usage and performance for containers.
• Monitoring and Status - Analyzes resource usage and performance of containers.
• Monitoring Systems - Container resource usage and performance analyzer.
• Observability and Monitoring - Analyzes resource usage of running containers.

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