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The System Metrics Plugin provides comprehensive system monitoring capabilities for {{% product-name %}}, collecting CPU, memory, disk, and network metrics from the host system. Monitor detailed performance insights including per-core CPU statistics, memory usage breakdowns, disk I/O performance, and network interface statistics. Features configurable metric collection with robust error handling and retry logic for reliable monitoring.

Configuration

Plugin parameters may be specified as key-value pairs in the --trigger-arguments flag (CLI) or in the trigger_arguments field (API) when creating a trigger. Some plugins support TOML configuration files, which can be specified using the plugin's config_file_path parameter.

If a plugin supports multiple trigger specifications, some parameters may depend on the trigger specification that you use.

Plugin metadata

This plugin includes a JSON metadata schema in its docstring that defines supported trigger types and configuration parameters. This metadata enables the InfluxDB 3 Explorer UI to display and configure the plugin.

Optional parameters

Parameter Type Default Description
hostname string localhost Hostname to tag all metrics with for system identification
include_cpu boolean true Include comprehensive CPU metrics collection (overall and per-core statistics)
include_memory boolean true Include memory metrics collection (RAM usage, swap statistics, page faults)
include_disk boolean true Include disk metrics collection (partition usage, I/O statistics, performance)
include_network boolean true Include network metrics collection (interface statistics and error counts)
max_retries integer 3 Maximum retry attempts on failure with graceful error handling

Note: This plugin has no required parameters. All parameters have sensible defaults.

TOML configuration

Parameter Type Default Description
config_file_path string none TOML config file path relative to PLUGIN_DIR (required for TOML configuration)

To use a TOML configuration file, set the PLUGIN_DIR environment variable and specify the config_file_path in the trigger arguments. This is in addition to the --plugin-dir flag when starting {{% product-name %}}.

Example TOML configuration

system_metrics_config_scheduler.toml

For more information on using TOML configuration files, see the Using TOML Configuration Files section in the influxdb3_plugins/README.md.

Software Requirements

  • {{% product-name %}}: with the Processing Engine enabled.
  • Python packages:
    • psutil (for system metrics collection)

Installation steps

  1. Start {{% product-name %}} with the Processing Engine enabled (--plugin-dir /path/to/plugins):

    influxdb3 serve \
  --node-id node0 \
  --object-store file \
  --data-dir ~/.influxdb3 \
  --plugin-dir ~/.plugins

  2. Install required Python packages:

    influxdb3 install package psutil

Trigger setup

Basic Scheduled Trigger

influxdb3 create trigger \
  --database system_monitoring \
  --path "gh:influxdata/system_metrics/system_metrics.py" \
  --trigger-spec "every:30s" \
  system_metrics_trigger

Using Configuration File

influxdb3 create trigger \
  --database system_monitoring \
  --path "gh:influxdata/system_metrics/system_metrics.py" \
  --trigger-spec "every:1m" \
  --trigger-arguments config_file_path=system_metrics_config_scheduler.toml \
  system_metrics_config_trigger

Custom Configuration

influxdb3 create trigger \
  --database system_monitoring \
  --path "gh:influxdata/system_metrics/system_metrics.py" \
  --trigger-spec "every:30s" \
  --trigger-arguments hostname=web-server-01,include_disk=false,max_retries=5 \
  system_metrics_custom_trigger

Example usage

Monitor Web Server Performance

# Create trigger for web server monitoring every 15 seconds
influxdb3 create trigger \
  --database web_monitoring \
  --path "gh:influxdata/system_metrics/system_metrics.py" \
  --trigger-spec "every:15s" \
  --trigger-arguments hostname=web-server-01,include_network=true \
  web_server_metrics

Database Server Monitoring

# Focus on CPU and disk metrics for database server
influxdb3 create trigger \
  --database db_monitoring \
  --path "gh:influxdata/system_metrics/system_metrics.py" \
  --trigger-spec "every:30s" \
  --trigger-arguments hostname=db-primary,include_disk=true,include_cpu=true,include_network=false \
  database_metrics

High-Frequency System Monitoring

# Collect all metrics every 10 seconds with higher retry tolerance
influxdb3 create trigger \
  --database system_monitoring \
  --path "gh:influxdata/system_metrics/system_metrics.py" \
  --trigger-spec "every:10s" \
  --trigger-arguments hostname=critical-server,max_retries=10 \
  high_freq_metrics

Query collected metrics

This plugin collects system metrics automatically. After the trigger runs, query to view the collected data:

influxdb3 query \
  --database system_monitoring \
  "SELECT * FROM system_cpu WHERE time >= now() - interval '5 minutes' LIMIT 5"

Expected output

+------+--------+-------+--------+------+--------+-------+--------+-------+-------+------------+------------------+ | host | cpu | user | system | idle | iowait | nice | irq | load1 | load5 | load15 | time | +------+--------+-------+--------+------+--------+-------+--------+-------+-------+------------+------------------+ | srv1 | total | 12.5 | 5.3 | 81.2 | 0.8 | 0.0 | 0.2 | 0.85 | 0.92 | 0.88 | 2024-01-15 10:00 | | srv1 | total | 13.1 | 5.5 | 80.4 | 0.7 | 0.0 | 0.3 | 0.87 | 0.93 | 0.88 | 2024-01-15 10:01 | | srv1 | total | 11.8 | 5.1 | 82.0 | 0.9 | 0.0 | 0.2 | 0.83 | 0.91 | 0.88 | 2024-01-15 10:02 | | srv1 | total | 14.2 | 5.8 | 79.0 | 0.8 | 0.0 | 0.2 | 0.89 | 0.92 | 0.88 | 2024-01-15 10:03 | | srv1 | total | 12.9 | 5.4 | 80.6 | 0.9 | 0.0 | 0.2 | 0.86 | 0.92 | 0.88 | 2024-01-15 10:04 | +------+--------+-------+--------+------+--------+-------+--------+-------+-------+------------+------------------+

Code overview

Main Functions

process_scheduled_call()

The main entry point for scheduled triggers. Collects system metrics based on configuration and writes them to InfluxDB.

def process_scheduled_call(influxdb3_local, call_time, args):
    # Parse configuration
    config = parse_config(args)
    
    # Collect metrics based on configuration
    if config['include_cpu']:
        collect_cpu_metrics(influxdb3_local, config['hostname'])
    
    if config['include_memory']:
        collect_memory_metrics(influxdb3_local, config['hostname'])
    
    # ... additional metric collections

Measurements and Fields

system_cpu

Overall CPU statistics and metrics:

  • Tags: host, cpu=total
  • Fields: user, system, idle, iowait, nice, irq, softirq, steal, guest, guest_nice, frequency_current, frequency_min, frequency_max, ctx_switches, interrupts, soft_interrupts, syscalls, load1, load5, load15

system_cpu_cores

Per-core CPU statistics:

  • Tags: host, core (core number)
  • Fields: usage, user, system, idle, iowait, nice, irq, softirq, steal, guest, guest_nice, frequency_current, frequency_min, frequency_max

system_memory

System memory statistics:

  • Tags: host
  • Fields: total, available, used, free, active, inactive, buffers, cached, shared, slab, percent

system_swap

Swap memory statistics:

  • Tags: host
  • Fields: total, used, free, percent, sin, sout

system_memory_faults

Memory page fault information (when available):

  • Tags: host
  • Fields: page_faults, major_faults, minor_faults, rss, vms, dirty, uss, pss

system_disk_usage

Disk partition usage:

  • Tags: host, device, mountpoint, fstype
  • Fields: total, used, free, percent

system_disk_io

Disk I/O statistics:

  • Tags: host, device
  • Fields: reads, writes, read_bytes, write_bytes, read_time, write_time, busy_time, read_merged_count, write_merged_count

system_disk_performance

Calculated disk performance metrics:

  • Tags: host, device
  • Fields: read_bytes_per_sec, write_bytes_per_sec, read_iops, write_iops, avg_read_latency_ms, avg_write_latency_ms, util_percent

system_network

Network interface statistics:

  • Tags: host, interface
  • Fields: bytes_sent, bytes_recv, packets_sent, packets_recv, errin, errout, dropin, dropout

Troubleshooting

Common issues

Issue: Permission errors for disk I/O metrics

Solution: The plugin will continue collecting other metrics even if some require elevated permissions. Run InfluxDB with appropriate permissions if disk I/O metrics are required.

Issue: Missing psutil library

Solution: Install the psutil package:

influxdb3 install package psutil

Issue: High CPU usage from plugin

Solution: Increase the trigger interval (for example, from every:10s to every:30s). Disable unnecessary metric types. Reduce the number of disk partitions monitored.

Viewing Logs

Logs are stored in the trigger's database in the system.processing_engine_logs table:

influxdb3 query \
  --database YOUR_DATABASE \
  "SELECT * FROM system.processing_engine_logs WHERE trigger_name = 'system_metrics_trigger' ORDER BY event_time DESC LIMIT 10"

Verifying Data Collection

Check that metrics are being collected:

# List all system metric measurements
influxdb3 query \
  --database system_monitoring \
  "SHOW MEASUREMENTS WHERE measurement =~ /^system_/"

# Check recent CPU metrics
influxdb3 query \
  --database system_monitoring \
  "SELECT COUNT(*) FROM system_cpu WHERE time >= now() - interval '1 hour'"

Logging

Logs are stored in the _internal database (or the database where the trigger is created) in the system.processing_engine_logs table. To view logs:

influxdb3 query --database _internal "SELECT * FROM system.processing_engine_logs WHERE trigger_name = 'your_trigger_name'"

Log columns:

  • event_time: Timestamp of the log event
  • trigger_name: Name of the trigger that generated the log
  • log_level: Severity level (INFO, WARN, ERROR)
  • log_text: Message describing the action or error

Report an issue

For plugin issues, see the Plugins repository issues page.

Find support for {{% product-name %}}

The InfluxDB Discord server is the best place to find support for InfluxDB 3 Core and InfluxDB 3 Enterprise. For other InfluxDB versions, see the Support and feedback options.