Function: Top / Processes
Quick Info
- Plugin:
apps.plugin
- Type: Simple Table (real-time snapshot)
- Availability: Linux, Windows, FreeBSD, macOS
- Required Access: View Agent Config for command line visibility
System Equivalents
Operating System | Traditional Tools |
---|---|
Linux | top , htop , ps aux , pidstat |
Windows | Task Manager, tasklist , Get-Process (PowerShell) |
FreeBSD | top , ps aux , procstat |
macOS | Activity Monitor, top , ps aux |
The Netdata processes
function provides several advantages over traditional tools:
- More accurate resource accounting through child process accumulation (e.g., it can accurately provide the CPU utilization of shell scripts)
- Unified cross-platform view with consistent metrics
- Comprehensive I/O and file descriptor metrics per PID
- Direct correlation with Netdata Apps dashboard section
Purpose
The processes
function is the drill-down companion to Apps (apps.plugin
) charts, providing complete visibility into how system resources are broken down by individual processes and how they are aggregated into the categories shown in Netdata dashboards.
apps.plugin
intelligently groups processes into categories to avoid extreme cardinality issues (millions of potential PIDs). It identifies spawn managers (systemd, containerd, init, etc.) and groups process trees by their top-most parent - the direct children of these spawn managers. This creates a manageable set of categories with accumulated metrics from entire process trees, including exited children.
When users see that "Application X" consumes significant resources in the charts, they need to understand:
- Which specific processes are included in that category
- How resources are distributed among those processes
- Why certain processes are grouped together
The processes
function answers these questions by showing:
- Every running PID with its assigned
Category
(matching the chart instances) - Complete resource breakdown per individual process
- Accumulated metrics from exited children (unique capability)
Key Capabilities
- Accurate Resource Attribution: More accurate than top/htop because it includes exited children and normalizes usage to match total system resources
- Process Tree Understanding: Shows how processes are grouped into categories via the
Category
field - Comprehensive Metrics: Breaks down CPU (user/system), memory, I/O, file descriptors, threads, and more
- Leak Detection: Identify memory leaks, file descriptor leaks, socket leaks, thread leaks
- Uptime Tracking: Shows per-process uptime to spot restarts and long-running processes
Data Fields
Field | Type | Description | Filterable | Sortable | Groupable | OS Availability |
---|---|---|---|---|---|---|
PID | Integer | Process ID | ✓ | ✓ | ✓ | All |
Cmd | String | Process command name | ✓ | ✓ | - | All |
Name | String | Process friendly name (if available) | ✓ | ✓ | - | Windows only |
CmdLine | String | Full command line with arguments (requires elevated access) | ✓ | ✓ | - | Linux, FreeBSD, macOS |
PPID | Integer | Parent process ID | ✓ | ✓ | ✓ | All |
Category | String | Process category from apps_groups.conf | ✓ | ✓ | ✓ | All |
User | String | User owner of the process | ✓ | ✓ | ✓ | All |
Uid | Integer | User ID | ✓ | ✓ | - | Linux, FreeBSD, macOS |
Group | String | Group owner | ✓ | ✓ | ✓ | Linux, FreeBSD, macOS |
Gid | Integer | Group ID | ✓ | ✓ | - | Linux, FreeBSD, macOS |
CPU | Percentage | Total CPU usage (100% = 1 core) | ✓ | ✓ | - | All |
UserCPU | Percentage | User-space CPU time | ✓ | ✓ | - | All |
SysCPU | Percentage | Kernel-space CPU time | ✓ | ✓ | - | All |
GuestCPU | Percentage | Guest VM CPU time (if available) | ✓ | ✓ | - | Linux only |
CUserCPU | Percentage | Children user CPU (accumulated from exited children) | ✓ | ✓ | - | Linux, FreeBSD |
CSysCPU | Percentage | Children system CPU (accumulated from exited children) | ✓ | ✓ | - | Linux, FreeBSD |
CGuestCPU | Percentage | Children guest CPU (accumulated from exited children) | ✓ | ✓ | - | Linux only |
vCtxSwitch | Rate | Voluntary context switches per second | ✓ | ✓ | - | Linux, macOS |
iCtxSwitch | Rate | Involuntary context switches per second | ✓ | ✓ | - | Linux only |
Memory | Percentage | Memory usage as percentage of total system RAM | ✓ | ✓ | - | All |
Resident | MiB | Resident Set Size (physical memory) | ✓ | ✓ | - | All |
Shared | MiB | Shared memory pages | ✓ | ✓ | - | Linux only |
Virtual | MiB | Virtual memory size | ✓ | ✓ | - | All |
Swap | MiB | Swap memory usage | ✓ | ✓ | - | Linux, Windows |
PReads | KiB/s | Physical disk read rate | ✓ | ✓ | - | Linux only |
PWrites | KiB/s | Physical disk write rate | ✓ | ✓ | - | Linux only |
LReads | KiB/s | Logical I/O read rate (includes cache) | ✓ | ✓ | - | All |
LWrites | KiB/s | Logical I/O write rate (includes cache) | ✓ | ✓ | - | All |
ROps | ops/s | Read operations per second | ✓ | ✓ | - | Linux, Windows |
WOps | ops/s | Write operations per second | ✓ | ✓ | - | Linux, Windows |
MinFlt | pgflts/s | Minor page faults per second | ✓ | ✓ | - | All |
MajFlt | pgflts/s | Major page faults per second | ✓ | ✓ | - | Linux, FreeBSD, macOS |
CMinFlt | pgflts/s | Children minor faults (accumulated) | ✓ | ✓ | - | Linux, FreeBSD |
CMajFlt | pgflts/s | Children major faults (accumulated) | ✓ | ✓ | - | Linux, FreeBSD |
FDsLimitPercent | Percentage | File descriptors usage vs limit | ✓ | ✓ | - | Linux only |
FDs | Count | Total open file descriptors | ✓ | ✓ | - | Linux, FreeBSD, macOS |
Files | Count | Open regular files | ✓ | ✓ | - | Linux, FreeBSD, macOS |
Pipes | Count | Open pipes | ✓ | ✓ | - | Linux, FreeBSD, macOS |
Sockets | Count | Open network sockets | ✓ | ✓ | - | Linux, FreeBSD, macOS |
iNotiFDs | Count | iNotify file descriptors | ✓ | ✓ | - | Linux only |
EventFDs | Count | Event file descriptors | ✓ | ✓ | - | Linux only |
TimerFDs | Count | Timer file descriptors | ✓ | ✓ | - | Linux only |
SigFDs | Count | Signal file descriptors | ✓ | ✓ | - | Linux only |
EvPollFDs | Count | Event poll descriptors | ✓ | ✓ | - | Linux only |
OtherFDs | Count | Other file descriptors | ✓ | ✓ | - | Linux, FreeBSD, macOS |
Handles | Count | Open handles (Windows compatibility) | ✓ | ✓ | - | Windows only |
Processes | Count | Number of processes (1 for single process, >1 for multi-process apps) | ✓ | ✓ | - | All |
Threads | Count | Number of threads | ✓ | ✓ | - | All |
Uptime | Seconds | Process uptime | ✓ | ✓ | - | All |
Platform-Specific Field Notes
- Linux: The most comprehensive data with all metrics including physical I/O, detailed file descriptors, child process accumulation, and resource limits
- macOS: Full process data except physical I/O, children accumulation, and some advanced metrics
- FreeBSD: Similar to macOS but includes children CPU accumulation
- Windows: Different approach using handles instead of file descriptors, includes I/O operations but lacks user/group ownership and command line access
Drill-Down Workflow
The typical workflow for drilling down to individual processes looks like this:
- Observe Chart Anomaly: Notice high resource usage in an
apps.plugin
chart category (e.g., "web" consuming 80% CPU) - Launch Processes Function: Open the function to see all processes
- Filter by Category: Use
category:web
filter to see only processes in that category - Identify Culprit: Sort by the relevant metric (CPU, Memory, etc.) to find the specific process
- Analyze Process Tree: Use PPID relationships to understand process spawning patterns
- Group Analysis: Group by User, Command, or other fields to understand patterns
Use Cases
1. Break Down System Resources into Processes
The processes function provides complete visibility into how system resources are distributed across all running processes, enabling comprehensive resource accounting and analysis.
View resource distribution across all processes
Sort by CPU
, Memory
, or I/O
metrics descending to see which processes consume the most resources. Group by Category
to understand resource allocation across application groups. This provides a complete breakdown of system resource utilization at the process level.
Understand category composition and aggregation
Filter by category:[name]
to see all processes that contribute to a specific apps.plugin chart instance. Group by Cmd
within a category to understand which different executables are grouped together. This reveals exactly how Netdata's intelligent grouping works and what's included in each category.
Analyze resource usage by user or group
Group processes by User
or Group
to understand resource consumption patterns across different users and system accounts. Sort by aggregate CPU or memory within each group to identify which users are consuming the most resources. This helps with multi-tenant resource accounting and fair-share analysis.
2. Drill Down to Identify Specific Heavy Consumer Processes
When apps.plugin charts show high resource usage in a category, the processes function enables precise identification of the specific processes responsible.
Identify CPU-intensive processes within categories
Filter by category:[name]
and sort by CPU
descending to find the exact processes causing high CPU usage in a chart category. Look at both own CPU (UserCPU
, SysCPU
) and children CPU (CUserCPU
, CSysCPU
) to understand whether the load comes from the process itself or its children.
Find memory-consuming processes in application groups
Filter by specific categories and sort by Resident
or Memory
percentage to identify which processes within an application group consume the most RAM. Compare Virtual
vs Resident
to understand memory allocation patterns and potential over-provisioning.
Locate I/O-heavy processes causing disk bottlenecks
Sort by PReads + PWrites
for physical I/O or LReads + LWrites
for logical I/O to find processes generating the most disk activity. Filter by category to drill down from chart-level I/O metrics to specific process-level I/O patterns.
3. Detect Leaks of Multiple Kinds
The processes function excels at identifying various types of resource leaks by correlating resource usage with process uptime.
Memory leak detection in long-running processes
Filter processes with Uptime > 3600
(one hour) and sort by Resident
memory descending. Look for processes where memory consumption is disproportionately high relative to their uptime. Track specific PIDs over time to observe continuously growing memory usage patterns.
File descriptor leak identification
Sort by FDs
count or filter for FDsLimitPercent > 50
to find processes approaching their file descriptor limits. Examine the breakdown of descriptor types (Files
, Sockets
, Pipes
, etc.) to understand what type of resources are leaking. Correlate high FD counts with process uptime to identify gradual leaks.
Socket and network connection leaks
Sort by Sockets
count to identify processes with abnormally high network connections. Compare socket counts against expected application behavior and uptime to detect connection leaks. Group by Category
to see if entire application groups are affected by socket exhaustion.
Thread leak monitoring
Sort by Threads
count and correlate with Uptime
to find processes creating threads without proper cleanup. Look for processes where thread count grows continuously over time. Filter by category to identify applications with thread pool management issues.
4. Monitor Crashes or Abnormal Events via Uptime
Process uptime tracking enables detection of crashes, restarts, and abnormal process lifecycle events.
Detect recent process restarts and crashes
Sort by Uptime
ascending to immediately see which processes have recently started or restarted. Filter by specific categories or command names to monitor critical services for unexpected restarts. Compare process start times with known maintenance windows to identify unplanned restarts.
Identify unstable applications with frequent restarts
Group processes by Cmd
and look for multiple PIDs with similar names but different uptimes, indicating repeated restarts. Track specific application categories over time to identify patterns of instability. Correlate low uptimes with high child CPU accumulation to detect crash loops.
Monitor process lifecycle and stability patterns
Filter by category and examine uptime distribution to understand application stability. Look for processes that should be long-running but have short uptimes. Use PPID relationships to identify parent processes that frequently spawn short-lived children.
5. Security Monitoring
The processes function provides critical security visibility by exposing process ownership, privileges, and behavior patterns.
Detect unauthorized or suspicious processes
Filter by Category:other
to find uncategorized processes that may be suspicious. Sort by User
to identify processes running under unexpected accounts. Search for unusual command names or paths that don't match normal system behavior.
Monitor privilege escalation and root processes
Filter by Uid:0
or User:root
to track all processes running with root privileges. Group root processes by Cmd
to understand what's running with elevated permissions. Look for unexpected processes running as root that shouldn't require privileges.
Analyze network activity and connection patterns
Sort by Sockets
count to identify processes with unusual network activity. Filter by specific users or categories to detect abnormal network behavior patterns. Correlate high socket counts with process names to identify potential backdoors or data exfiltration.
Track command line arguments for security forensics
Use full-text search in CmdLine
to find processes launched with specific parameters or scripts. Group by command line patterns to identify potentially malicious execution patterns. Filter by user and examine command lines to detect privilege abuse or policy violations.
Special Features
- Child Process Accumulation: Uniquely captures resources from exited children - critical for accurate measurement of shell scripts and applications that spawn many short-lived processes (even 100+ commands/second)
- Category Correlation: The
Category
field directly matches the instance names inapps.plugin
charts, enabling drill-down from chart to process level - Intelligent Grouping: Understands spawn managers (systemd, containerd, init) and groups by top-most parent to create manageable categories
- Normalized Metrics: All per-process usage is normalized to accurately match total system resource usage
- Real-time Updates: Data refreshes every few seconds showing current process state
- Custom Grouping:
apps_groups.conf
allows defining custom spawn managers and individual processes of interest - Comprehensive FD Breakdown: Detailed categorization of all file descriptor types for leak detection
Performance Considerations
- Function executes with minimal overhead using efficient process enumeration
- Large process counts (>1000) may increase response time
- Command line access requires additional security permissions
- No historical data - shows current snapshot only
Requirements and Limitations
- Operating System: Linux, Windows, FreeBSD, macOS
- Permissions: Standard user can see basic data; elevated access needed for command lines
- Data Type: Real-time snapshot (no historical data)
- Child Processes: Only terminated children are accumulated; running children appear separately
- Platform Variations: Some fields may not be available on all operating systems (e.g., certain I/O metrics on macOS)
Related Functions
systemd-services
: Aggregated view of processes grouped by systemd servicecontainers-vms
: Container and VM-specific process informationnetwork-connections
: Network connections per processsystemd-journal
: Process logs and events
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