Pueue Job Orchestration

Universal CLI telemetry layer and job management — every command routed through pueue gets precise timing, exit code capture, full stdout/stderr logs, environment snapshots, and callback-on-completion.

Overview

Pueue is a Rust CLI tool for managing shell command queues. It provides:

• Daemon persistence - Survives SSH disconnects, crashes, reboots
• Disk-backed queue - Auto-resumes after any failure
• Group-based parallelism - Control concurrent jobs per group
• Easy failure recovery - Restart failed jobs with one command
• Full telemetry - Timing, exit codes, stdout/stderr logs, env snapshots per task

When to Route Through Pueue

Operation	Route Through Pueue?	Why
Any command >30 seconds	Always	Telemetry, persistence, log capture
Batch operations (>3 items)	Always	Parallelism control, failure isolation
Build/test pipelines	Recommended	--after DAGs, group monitoring
Data processing	Always	Checkpoint resume, state management
Quick one-off commands (<5s)	Optional	Overhead is ~100ms, but you get logs
Interactive commands (editors, REPLs)	Never	Pueue can't handle stdin interaction

When to Use This Skill

Use this skill when the user mentions:

Trigger	Example
Running tasks on BigBlack/LittleBlack	"Run this on bigblack"
Long-running data processing	"Populate the cache for all symbols"
Batch/parallel operations	"Process these 70 jobs"
SSH remote execution	"Execute this overnight on the GPU server"
Cache population	"Fill the ClickHouse cache"
Pueue features	"Set up a callback", "delay this job"

Quick Reference

Check Status

# Local
pueue status

# Remote (BigBlack)
ssh bigblack "~/.local/bin/pueue status"

Queue a Job

# Local (with working directory)
pueue add -w ~/project -- python long_running_script.py

# Local (simple)
pueue add -- python long_running_script.py

# Remote (BigBlack)
ssh bigblack "~/.local/bin/pueue add -w ~/project -- uv run python script.py"

# With group (for parallelism control)
pueue add --group p1 --label "BTCUSDT@1000" -w ~/project -- python populate.py --symbol BTCUSDT

Monitor Jobs

pueue follow <id>         # Watch job output in real-time
pueue log <id>            # View completed job output
pueue log <id> --full     # Full output (not truncated)

Manage Jobs

pueue restart <id>         # ⚠ Creates NEW task (see warning below)
pueue restart --in-place <id>  # Restarts task in-place (no new ID)
pueue restart --all-failed # ⚠ Restarts ALL failed across ALL groups
pueue kill <id>            # Kill running job
pueue clean                # Remove completed jobs from list
pueue reset                # Clear all jobs (use with caution)

CRITICAL WARNING — pueue restart semantics:

pueue restart <id> does NOT restart the task in-place. It creates a brand new task with a new ID, copying the command from the original. The original stays as Done/Failed. This causes exponential task growth when used in loops or by autonomous agents. In a 2026-03-04 incident, agents calling pueue restart on failed tasks grew 60 jobs to ~12,800.

• Use --in-place if you truly need to restart: pueue restart --in-place <id>
• Verify before restart: Read pueue log <id> to check if the failure is persistent (missing data, bad args) — retrying will never help
• Never use --all-failed without --group filter — it restarts every failed task across ALL groups

Host Configuration

Host	Location	Parallelism Groups
BigBlack	~/.local/bin/pueue	p1 (16), p2 (2), p3 (3), p4 (1)
LittleBlack	~/.local/bin/pueue	default (2)
Local (macOS)	/opt/homebrew/bin/pueue	default

Core Workflows

1. Queue Single Remote Job

# Step 1: Verify daemon is running
ssh bigblack "~/.local/bin/pueue status"

# Step 2: Queue the job
ssh bigblack "~/.local/bin/pueue add --label 'my-job' -- cd ~/project && uv run python script.py"

# Step 3: Monitor progress
ssh bigblack "~/.local/bin/pueue follow <id>"

2. Batch Job Submission (Multiple Symbols)

For rangebar cache population or similar batch operations:

# Use the pueue-populate.sh script
ssh bigblack "cd ~/rangebar-py && ./scripts/pueue-populate.sh setup"   # One-time
ssh bigblack "cd ~/rangebar-py && ./scripts/pueue-populate.sh phase1"  # Queue Phase 1
ssh bigblack "cd ~/rangebar-py && ./scripts/pueue-populate.sh status"  # Check progress

3. Configure Parallelism Groups

# Create groups with different parallelism limits
pueue group add fast      # Create 'fast' group
pueue parallel 4 --group fast  # Allow 4 parallel jobs

pueue group add slow
pueue parallel 1 --group slow  # Sequential execution

# Queue jobs to specific groups
pueue add --group fast -- echo "fast job"
pueue add --group slow -- echo "slow job"

4. Handle Failed Jobs

# Check what failed
pueue status | grep Failed

# View error output FIRST (distinguish transient vs persistent)
pueue log <id>

# Restart specific job IN-PLACE (no new task created)
pueue restart --in-place <id>

# ⚠ NEVER blindly restart all failed — classify failures first
# pueue restart --all-failed  # DANGEROUS: no group filter, creates duplicates

Failure classification before restart: Exit code 1 (app error) may be persistent (missing data, bad args — will never succeed). Exit code 137 (OOM) or 143 (SIGTERM) may be transient. Always read pueue log before restarting.

Troubleshooting

Issue	Cause	Solution
pueue: command not found	Not in PATH	Use full path: ~/.local/bin/pueue
Connection refused	Daemon not running	Start with pueued -d
Jobs stuck in Queued	Group paused or at limit	Check pueue status, pueue start
SSH disconnect kills jobs	Not using Pueue	Queue via Pueue instead of direct SSH
Job fails immediately	Wrong working directory	Use pueue add -w /path or cd /path && pueue add

Priority Scheduling (--priority)

Higher priority number = runs first when a queue slot opens:

# Urgent validation (runs before queued lower-priority jobs)
pueue add --priority 10 -- python validate_critical.py

# Normal compute (default priority is 0)
pueue add -- python train_model.py

# Low-priority background task
pueue add --priority -5 -- python cleanup_logs.py

Priority only affects queued jobs waiting for an open slot. Running jobs are not preempted.

Per-Task Environment Override (pueue env)

Inject or override environment variables on stashed or queued tasks:

# Create a stashed job
JOB_ID=$(pueue add --stashed --print-task-id -- python train.py)

# Set environment variables (NOTE: separate args, NOT KEY=VALUE)
pueue env set "$JOB_ID" BATCH_SIZE 64
pueue env set "$JOB_ID" LEARNING_RATE 0.001

# Enqueue when ready
pueue enqueue "$JOB_ID"

Syntax: pueue env set <id> KEY VALUE -- the key and value are separate positional arguments.

Constraint: Only works on stashed/queued tasks. Cannot modify environment of running tasks.

Relationship to mise.toml [env]: mise [env] remains the SSoT for default environment. Use pueue env set only for one-off overrides (e.g., hyperparameter sweeps) without modifying config files.

Blocking Wait (pueue wait)

Block until tasks complete -- simpler than polling loops for scripts:

# Wait for specific task
pueue wait 42

# Wait for all tasks in a group
pueue wait --group mygroup

# Wait for ALL tasks across all groups
pueue wait --all

# Wait quietly (no progress output)
pueue wait 42 --quiet

# Wait for tasks to reach a specific status
pueue wait --status queued

Script Integration Pattern

# Queue -> wait -> process results
TASK_ID=$(pueue add --print-task-id -- python etl_pipeline.py)
pueue wait "$TASK_ID" --quiet
EXIT_CODE=$(pueue status --json | jq -r ".tasks[\"$TASK_ID\"].status.Done.result" 2>/dev/null)
if [ "$EXIT_CODE" = "Success" ]; then
    echo "Pipeline succeeded"
    pueue log "$TASK_ID" --full
else
    echo "Pipeline failed"
    pueue log "$TASK_ID" --full >&2
fi

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Companion CLI Tools (bigblack)

Four lightweight CLI tools complement pueue for monitoring and notifications. All installed on bigblack at /usr/local/bin/ (noti, mprocs) or via apt (ntfy, task-spooler).

noti — Wrap Any Command with Telegram Notification

Best for one-off "notify me when this finishes" workflows. Native Telegram support.

# Wrap any command — sends Telegram when it finishes
noti -g mise run kintsugi:catchup

# With execution time in message
noti -g -e python long_script.py

# Custom title/message
noti -g -t "Deploy done" -m "bigblack updated" mise run deploy:bigblack

Config: ~/.config/noti/noti.yaml + env vars NOTI_TELEGRAM_TOKEN, NOTI_TELEGRAM_CHAT_ID, NOTI_DEFAULT=telegram in ~/.bashrc.

ntfy — Push Notifications from Scripts/Callbacks

Best for programmatic notifications from scripts, pueue callbacks, or curl one-liners.

# One-liner from any script
ntfy pub --title "Backfill done" odb-alerts "BTCUSDT@500 complete"

# With priority and tags
ntfy pub --priority high --tags "warning" odb-alerts "Job failed"

# curl variant (works anywhere, no binary needed)
curl -d "Backup finished" ntfy.sh/my-topic

# Subscribe to topic (poll mode)
ntfy sub --poll odb-alerts

Pueue callback integration — add to ~/.config/pueue/pueue.yml:

callback: 'ntfy pub --title "pueue: {{label}}" --tags "{{status}}" odb-alerts "Task #{{id}} {{status}} ({{command}})"'

mprocs — Multi-Process TUI

Best for interactive SSH sessions watching multiple processes side-by-side.

# Watch multiple pueue jobs in split panes
mprocs "pueue follow 3" "pueue follow 7" "pueue follow 8"

# Monitor services
mprocs "journalctl -fu opendeviationbar-sidecar" "journalctl -fu opendeviationbar-kintsugi"

Requires interactive TTY (SSH directly, not via scripts).

task-spooler (tsp) — Simplest Job Queue

Best for quick ad-hoc sequential/parallel tasks without pueue group setup.

# Queue tasks (default: 1 parallel)
tsp python train.py
tsp python validate.py

# Set parallel slots
tsp -S 3

# List queue
tsp -l

# View job output
tsp -c 0

# Combine with noti
tsp bash -c 'python train.py && noti -g -m "training done"'

Tool Selection Guide

Need to...
├── Get notified when a command finishes? → noti -g <command>
├── Send notification from a script/callback? → ntfy pub topic "msg"
├── Watch multiple logs/processes live? → mprocs "cmd1" "cmd2"
├── Quick sequential queue (no groups needed)? → tsp <command>
└── Persistent queue with groups, priorities? → pueue add <command>

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Deep-Dive References

Topic	Reference
Installation (macOS, Linux, systemd, launchd)	Installation Guide
Production lessons: --after chaining, forensic audit, per-year parallelization, pipeline monitoring	Production Lessons
State bloat prevention, bulk xargs -P submission, two-tier architecture (300K+ jobs), crash recovery	State Management & Bulk Submission
ClickHouse thread tuning, parallelism sizing formula, live tuning	ClickHouse Tuning
Callback hooks, template variables, delayed scheduling (--delay)	Callbacks & Scheduling
python-dotenv secrets pattern, rangebar-py integration	Environment & Secrets
Claude Code integration, synchronous wrapper, telemetry queries	Claude Code Integration
All pueue.yml settings (shared, client, daemon, profiles)	Pueue Config Reference

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Pueue vs Temporal: When to Use Which

For structured, repeatable workflows needing durability and dedup, consider Temporal (pip install temporalio, brew install temporal):

Dimension	Pueue	Temporal
Best for	Ad-hoc shell commands, SSH remote jobs	Structured, repeatable workflows
Setup	Single binary, zero infra	Server + database (dev: temporal server start-dev)
Dedup	None — restart creates new tasks	Workflow ID uniqueness (built-in)
Retry policy	None — manual or external agent	Per-activity: max attempts, backoff, non-retryable errors
Parallelism	pueue parallel N --group G	max_concurrent_activities=N on worker
Visibility	pueue status (text, scales poorly)	Web UI with pagination, search, event history

Recommendation: Keep pueue for ad-hoc work. Migrate structured pipelines to Temporal when dedup and retry policies matter. See devops-tools:distributed-job-safety for invariants that apply to both.

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Related

• Hook: itp-hooks/posttooluse-reminder.ts - Reminds to use Pueue for detected long-running commands
• Reference: Pueue GitHub
• Companion tools: noti (command wrapper → Telegram), ntfy (pub-sub notifications), mprocs (multi-process TUI), task-spooler (minimal job queue)
• SOTA Alternative: Temporal — durable workflow orchestration with built-in dedup, retry, visibility
• Issue: rangebar-py#77 - Original implementation
• Issue: rangebar-py#88 - Production deployment lessons