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thresh metrics

Show resource usage, performance statistics, and operational metrics for environments.

Synopsis​

# Show all environments
thresh metrics

# Show specific environment
thresh metrics <environment-name>

# Watch metrics in real-time
thresh metrics <environment-name> --watch

Description​

The metrics command displays resource consumption and performance data for thresh environments:

  • CPU usage (percentage and time)
  • Memory usage (RSS, cache, swap)
  • Disk I/O (read/write operations and bytes)
  • Network I/O (transmitted/received bytes)
  • Process counts and states
  • Uptime and container lifecycle

Metrics are collected from the container runtime and updated in real-time with --watch mode.

Options​

OptionDescription
--watch, -wContinuously update metrics (1-second interval)
--jsonOutput in JSON format
--interval <seconds>Update interval for watch mode (default: 1)
--no-streamDisable streaming, show current snapshot only
--help, -hShow help information

Examples​

Show All Environments​

# Display metrics for all environments
thresh metrics

Output:

Environment Metrics:

python-dev (running)
  CPU:     12.5% (2.3s total)
  Memory:  256 MB / 8 GB (3.2%)
  Disk:    15 MB read, 8 MB written
  Network: 1.2 MB sent, 850 KB received
  Uptime:  2h 15m

node-dev (stopped)
  Status:  Not running
  Last:    Stopped 45m ago

Monitor Specific Environment​

# Show metrics for one environment
thresh metrics python-dev

Output:

python-dev

CPU Usage:
  Current:  12.5%
  Average:  8.3%
  Total:    2.3s

Memory:
  RSS:      256 MB
  Cache:    128 MB
  Swap:     0 MB
  Limit:    8 GB
  Usage:    3.2%

Disk I/O:
  Read:     15.2 MB (125 ops)
  Write:    8.4 MB (89 ops)

Network I/O:
  Sent:     1.2 MB
  Received: 850 KB

Processes:
  Total:    12
  Running:  3
  Sleeping: 9

Container:
  Status:   Running
  Uptime:   2h 15m 34s
  Restarts: 0

Watch Mode (Real-Time)​

# Live-updating metrics (Ctrl+C to exit)
thresh metrics python-dev --watch

Output (updates every second):

python-dev (live updates - press Ctrl+C to exit)

CPU:     14.2% ████████░░░░░░░░░░░░  Memory: 268 MB  Disk: 15.3 MB  Net: ↑ 1.3 MB ↓ 912 KB

Updated: 2026-02-12 14:35:22

JSON Output​

# Get structured metrics
thresh metrics python-dev --json

Output:

{
  "environment": "python-dev",
  "status": "running",
  "timestamp": "2026-02-12T14:35:22Z",
  "uptime_seconds": 8134,
  "cpu": {
    "usage_percent": 12.5,
    "total_seconds": 2.3,
    "system_seconds": 0.8,
    "user_seconds": 1.5
  },
  "memory": {
    "rss_bytes": 268435456,
    "cache_bytes": 134217728,
    "swap_bytes": 0,
    "limit_bytes": 8589934592,
    "usage_percent": 3.2
  },
  "disk_io": {
    "read_bytes": 15925248,
    "write_bytes": 8808038,
    "read_ops": 125,
    "write_ops": 89
  },
  "network_io": {
    "sent_bytes": 1258291,
    "received_bytes": 870400,
    "sent_packets": 1024,
    "received_packets": 896
  },
  "processes": {
    "total": 12,
    "running": 3,
    "sleeping": 9,
    "stopped": 0,
    "zombie": 0
  }
}

Custom Watch Interval​

# Update every 5 seconds
thresh metrics python-dev --watch --interval 5

Compare Environments​

# Export metrics for all environments
thresh metrics --json | jq '.[] | {name: .environment, cpu: .cpu.usage_percent, mem: .memory.usage_percent}'

Output:

{
  "name": "python-dev",
  "cpu": 12.5,
  "mem": 3.2
}
{
  "name": "node-dev",
  "cpu": 0,
  "mem": 0
}

Metric Definitions​

CPU Metrics​

MetricDescription
Current UsageCPU percentage over last sampling period
Average UsageMean CPU usage since container start
Total TimeCumulative CPU seconds consumed
User TimeCPU time in user mode
System TimeCPU time in kernel mode

Memory Metrics​

MetricDescription
RSSResident Set Size - physical RAM used
CachePage cache memory (can be reclaimed)
SwapSwap space used
LimitMaximum memory container can use
Usage %RSS / Limit percentage

Disk I/O Metrics​

MetricDescription
Read BytesTotal bytes read from disk
Write BytesTotal bytes written to disk
Read OpsNumber of read operations
Write OpsNumber of write operations

Network I/O Metrics​

MetricDescription
Sent BytesTotal bytes transmitted
Received BytesTotal bytes received
Sent PacketsTotal packets transmitted
Received PacketsTotal packets received

Use Cases​

Resource Optimization​

Identify memory-hungry environments:

# Find environments using >50% memory
thresh metrics --json | jq '.[] | select(.memory.usage_percent > 50)'

Performance Monitoring​

Track CPU usage during development:

# Watch CPU during intensive task
thresh metrics node-dev --watch
# In another terminal:
# Run build process in environment

Capacity Planning​

Determine resource requirements:

# Run typical workload, collect metrics
thresh metrics python-dev --json > metrics-baseline.json

# Analyze peak usage
jq '.memory.rss_bytes' metrics-baseline.json | numfmt --to=iec

Health Checks​

Verify environment is within bounds:

# Check if CPU or memory is excessive
$metrics = thresh metrics app-env --json | ConvertFrom-Json
if ($metrics.cpu.usage_percent -gt 80) {
  Write-Warning "High CPU usage detected"
}

Integration with Monitoring​

Prometheus Exporter​

Export metrics in Prometheus format:

# Create custom exporter script
thresh metrics --json | jq -r '
  .[] | 
  "thresh_cpu_percent{env=\"\(.environment)\"} \(.cpu.usage_percent)\n" +
  "thresh_memory_bytes{env=\"\(.environment)\"} \(.memory.rss_bytes)"
'

Output:

thresh_cpu_percent{env="python-dev"} 12.5
thresh_memory_bytes{env="python-dev"} 268435456

Grafana Dashboard​

Collect metrics periodically:

#!/bin/bash
# metrics-collector.sh

while true; do
  thresh metrics --json >> /var/log/thresh-metrics.jsonl
  sleep 60
done

Import into Grafana using JSON API data source.

Alerting​

Monitor for anomalies:

# Simple alerting script
$metrics = thresh metrics production --json | ConvertFrom-Json

if ($metrics.memory.usage_percent -gt 90) {
  # Send alert (email, Slack, PagerDuty, etc.)
  Send-Alert "High memory usage: $($metrics.memory.usage_percent)%"
}

Container Runtime Sources​

Metrics are sourced from:

Windows (WSL): /sys/fs/cgroup/ interfaces via WSL 2
Linux (Docker): docker stats API
macOS (containerd): containerd metrics API

Performance Impact​

Metrics collection is lightweight:

  • Less than 1% CPU overhead
  • Less than 5 MB memory overhead
  • Non-invasive polling (no ptrace)

Watch mode impact:

  • 1-second interval: negligible
  • 0.1-second interval: ~2% CPU overhead

Limitations​

Stopped Environments​

Metrics are not available for stopped environments - only status and last activity.

Historical Data​

thresh does not persist metrics history. For historical analysis, export to external monitoring tools.

Nested Containers​

Metrics reflect the container, not nested processes if running Docker-in-Docker or similar.

Exit Codes​

CodeMeaning
0Success
1General error
2Environment not found
3Container runtime unavailable

See Also​