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The System Metrics Plugin provides comprehensive system monitoring capabilities for InfluxDB 3, 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

Required parameters

No required parameters - all system metrics are collected by default with sensible defaults.

System monitoring 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

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 InfluxDB 3.

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.

Installation steps

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

  2. Install required Python packages:

    • psutil (for system metrics collection)
    influxdb3 install package psutil

Trigger setup

Basic scheduled trigger

Monitor system performance every 30 seconds:

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

Custom configuration

Monitor specific metrics with custom hostname:

influxdb3 create trigger \
  --database system_monitoring \
  --plugin-filename 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

Example 1: Web server monitoring

Monitor web server performance every 15 seconds with network statistics:

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

# Query recent CPU metrics
influxdb3 query \
  --database web_monitoring \
  "SELECT * FROM system_cpu WHERE time >= now() - interval '5 minutes' LIMIT 5"

Expected output

+---------------+-------+------+--------+------+--------+-------+-------+-----------+------------------+
| host          | cpu   | user | system | idle | iowait | nice  | load1 | load5     | time             |
+---------------+-------+------+--------+------+--------+-------+-------+-----------+------------------+
| web-server-01 | total | 12.5 | 5.3    | 81.2 | 0.8    | 0.0   | 0.85  | 0.92      | 2024-01-15 10:00 |
| web-server-01 | total | 13.1 | 5.5    | 80.4 | 0.7    | 0.0   | 0.87  | 0.93      | 2024-01-15 10:01 |
| web-server-01 | total | 11.8 | 5.1    | 82.0 | 0.9    | 0.0   | 0.83  | 0.91      | 2024-01-15 10:02 |
+---------------+-------+------+--------+------+--------+-------+-------+-----------+------------------+

Example 2: Database server monitoring

Focus on CPU and disk metrics for database server:

# Create trigger for database server
influxdb3 create trigger \
  --database db_monitoring \
  --plugin-filename 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

# Query disk usage
influxdb3 query \
  --database db_monitoring \
  "SELECT * FROM system_disk_usage WHERE host = 'db-primary'"

Example 3: High-frequency monitoring

Collect all metrics every 10 seconds with higher retry tolerance:

# Create high-frequency monitoring trigger
influxdb3 create trigger \
  --database system_monitoring \
  --plugin-filename gh:influxdata/system_metrics/system_metrics.py \
  --trigger-spec "every:10s" \
  --trigger-arguments hostname=critical-server,max_retries=10 \
  high_freq_metrics

Code overview

Files

  • system_metrics.py: The main plugin code containing system metrics collection logic
  • system_metrics_config_scheduler.toml: Example TOML configuration file for scheduled triggers

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

Main functions

process_scheduled_call(influxdb3_local, call_time, args)

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

Key operations:

  1. Parses configuration from arguments
  2. Collects CPU, memory, disk, and network metrics based on configuration
  3. Writes metrics to InfluxDB with proper error handling and retry logic

collect_cpu_metrics(influxdb3_local, hostname)

Collects CPU utilization and performance metrics including per-core statistics and system load averages.

collect_memory_metrics(influxdb3_local, hostname)

Collects memory usage statistics including RAM, swap, and page fault information.

collect_disk_metrics(influxdb3_local, hostname)

Collects disk usage and I/O statistics for all mounted partitions.

collect_network_metrics(influxdb3_local, hostname)

Collects network interface statistics including bytes transferred and error counts.

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 on disk I/O metrics

Some disk I/O metrics may require elevated permissions.

Solution: The plugin will continue collecting other metrics even if some require elevated permissions. Consider running InfluxDB 3 with appropriate permissions if disk I/O metrics are critical.

Issue: Missing psutil library

ERROR: No module named 'psutil'

Solution: Install the psutil package:

influxdb3 install package psutil

Issue: High CPU usage from plugin

If the plugin causes high CPU usage, consider:

  • Increasing the trigger interval (for example, from every:10s to every:30s)
  • Disabling unnecessary metric types
  • Reducing the number of disk partitions monitored

Issue: No data being collected

Solution:

  1. Check that the trigger is active: 
    influxdb3 query --database _internal "SELECT * FROM system.processing_engine_logs WHERE trigger_name = 'your_trigger_name'"
  2. Verify system permissions allow access to system metrics
  3. Check that the psutil package is properly installed

Debugging tips

  1. Check recent metrics collection:

    # 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'"

  2. Monitor plugin logs:

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

  3. Test metric collection manually:

    influxdb3 test schedule_plugin \
  --database system_monitoring \
  --schedule "0 0 * * * ?" \
  system_metrics.py

Performance considerations

  • The plugin collects comprehensive system metrics efficiently using the psutil library
  • Metric collection is optimized to minimize system overhead
  • Error handling and retry logic ensure reliable operation
  • Configurable metric types allow focusing on relevant metrics only

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.