Agent Scheduler Fires the Same Job Twice — Duplicate Task Execution
Symptom
- Scheduled report sent to all users twice within seconds of each other
- Daily data processing job runs twice — duplicate records in database
- Cron job on two servers both trigger at the same time
- Job scheduler restarts a job before the previous run completes
- After deploy, in-flight job and new instance both run simultaneously
- k8s CronJob creates two pods for the same schedule slot
Root Cause
Distributed schedulers run on multiple nodes. Without coordination, all nodes trigger the same job when the schedule fires. Clock skew, scheduler restarts, rolling deploys, and “at least once” job delivery guarantees all cause duplicate execution. The only reliable protection is distributed locking or database-level idempotency.
Fix
Option 1: Distributed lock using Redis
import redis
import uuid
import time
import functools
redis_client = redis.Redis(host="redis", port=6379, decode_responses=True)
class DistributedJobLock:
"""
Redis-based lock to ensure only one instance of a scheduled job runs at a time.
"""
def __init__(self, job_name: str, ttl_seconds: int = 3600):
self.job_name = job_name
self.ttl = ttl_seconds
self.lock_key = f"job_lock:{job_name}"
self.instance_id = str(uuid.uuid4())[:8]
def acquire(self) -> bool:
"""
Try to acquire the lock. Returns True if acquired, False if already running.
Uses SET NX EX for atomic acquire-with-expiry.
"""
acquired = redis_client.set(
self.lock_key,
f"{self.instance_id}:{time.time()}",
nx=True, # Only set if key doesn't exist
ex=self.ttl # Expire after TTL (prevents deadlock if job crashes)
)
if acquired:
print(f"Job '{self.job_name}' lock acquired by {self.instance_id}")
else:
existing = redis_client.get(self.lock_key)
print(f"Job '{self.job_name}' already running ({existing}) — skipping")
return bool(acquired)
def release(self):
"""Release the lock only if we own it"""
current = redis_client.get(self.lock_key)
if current and current.startswith(self.instance_id):
redis_client.delete(self.lock_key)
print(f"Job '{self.job_name}' lock released by {self.instance_id}")
else:
print(f"Job '{self.job_name}' lock not owned by us — not releasing")
def __enter__(self):
if not self.acquire():
raise RuntimeError(f"Job '{self.job_name}' is already running")
return self
def __exit__(self, *args):
self.release()
def single_instance_job(job_name: str, ttl: int = 3600):
"""Decorator: ensure job runs at most once at a time across all instances"""
def decorator(fn):
@functools.wraps(fn)
def wrapper(*args, **kwargs):
lock = DistributedJobLock(job_name, ttl)
try:
with lock:
return fn(*args, **kwargs)
except RuntimeError as e:
print(f"Skipped: {e}")
return None
return wrapper
return decorator
@single_instance_job("daily_report", ttl=7200)
def send_daily_report():
"""This job is guaranteed to run at most once at any time"""
users = get_all_users()
for user in users:
send_report_email(user)
print("Daily report sent")
Option 2: Database job execution log (idempotent by job run ID)
import sqlite3
from datetime import datetime, date
class JobExecutionLog:
"""
Track completed job runs. Reject duplicate execution for the same slot.
"""
def __init__(self, db_path: str = "job_log.db"):
self.db = sqlite3.connect(db_path, check_same_thread=False)
self.db.execute("""
CREATE TABLE IF NOT EXISTS job_runs (
job_name TEXT NOT NULL,
run_slot TEXT NOT NULL, -- e.g., "daily_report:2025-04-15"
started_at TEXT,
completed_at TEXT,
status TEXT DEFAULT 'running',
instance_id TEXT,
PRIMARY KEY (job_name, run_slot)
)
""")
self.db.commit()
def try_start(self, job_name: str, run_slot: str = None, instance_id: str = None) -> bool:
"""
Try to register this job run. Returns True if this instance should run it.
Returns False if another instance already started it.
"""
if run_slot is None:
run_slot = datetime.utcnow().strftime("%Y-%m-%dT%H:00") # Hourly slot
try:
self.db.execute("""
INSERT INTO job_runs (job_name, run_slot, started_at, instance_id)
VALUES (?, ?, ?, ?)
""", (job_name, run_slot, datetime.utcnow().isoformat(), instance_id or "unknown"))
self.db.commit()
print(f"Job '{job_name}' slot '{run_slot}' claimed")
return True
except sqlite3.IntegrityError:
# Another instance already inserted this row
existing = self.db.execute(
"SELECT instance_id, status FROM job_runs WHERE job_name=? AND run_slot=?",
(job_name, run_slot)
).fetchone()
print(f"Job '{job_name}' slot '{run_slot}' already claimed by {existing}")
return False
def mark_complete(self, job_name: str, run_slot: str, status: str = "completed"):
self.db.execute("""
UPDATE job_runs SET status=?, completed_at=?
WHERE job_name=? AND run_slot=?
""", (status, datetime.utcnow().isoformat(), job_name, run_slot))
self.db.commit()
log = JobExecutionLog()
def idempotent_job(job_name: str, slot_fn=None):
"""Decorator: skip job if already run for this time slot"""
def decorator(fn):
@functools.wraps(fn)
def wrapper(*args, **kwargs):
slot = slot_fn() if slot_fn else datetime.utcnow().strftime("%Y-%m-%dT%H:00")
if not log.try_start(job_name, slot):
print(f"Skipping '{job_name}' — already ran for slot {slot}")
return None
try:
result = fn(*args, **kwargs)
log.mark_complete(job_name, slot, "completed")
return result
except Exception as e:
log.mark_complete(job_name, slot, f"failed: {e}")
raise
return wrapper
return decorator
@idempotent_job("daily_report", slot_fn=lambda: date.today().isoformat())
def send_daily_report():
pass # Runs at most once per day regardless of how many instances trigger it
Option 3: Kubernetes CronJob — single concurrency policy
# k8s CronJob with Forbid concurrency — guaranteed no duplicates
apiVersion: batch/v1
kind: CronJob
metadata:
name: agent-daily-report
spec:
schedule: "0 9 * * *" # 9 AM daily
concurrencyPolicy: Forbid # Skip if previous job still running (NOT Replace)
startingDeadlineSeconds: 300 # Give up if can't start within 5 min of schedule
successfulJobsHistoryLimit: 3
failedJobsHistoryLimit: 1
jobTemplate:
spec:
# Retry on failure but don't duplicate:
backoffLimit: 2
activeDeadlineSeconds: 7200 # Max 2 hours
template:
spec:
restartPolicy: OnFailure
containers:
- name: agent
image: my-agent:latest
env:
- name: JOB_NAME
value: daily-report
- name: JOB_SLOT
value: "$(date +%Y-%m-%d)"
# concurrencyPolicy options:
# Allow: Multiple jobs can run simultaneously (dangerous for most agent tasks)
# Forbid: Skip new job if previous still running (safest)
# Replace: Cancel previous, start new (use only for idempotent jobs)
Option 4: Atomic job claim with PostgreSQL advisory locks
import psycopg2
def run_with_pg_advisory_lock(job_id: int, fn, *args, **kwargs):
"""
Use PostgreSQL advisory lock — integer ID per job.
Lock is released automatically when session closes.
Works across all processes connected to same DB.
"""
conn = psycopg2.connect(os.environ["DATABASE_URL"])
cur = conn.cursor()
# Try advisory lock — non-blocking
cur.execute("SELECT pg_try_advisory_lock(%s)", (job_id,))
acquired = cur.fetchone()[0]
if not acquired:
print(f"Job {job_id} already locked — skipping")
conn.close()
return None
try:
print(f"Job {job_id} lock acquired")
return fn(*args, **kwargs)
finally:
cur.execute("SELECT pg_advisory_unlock(%s)", (job_id,))
conn.commit()
conn.close()
print(f"Job {job_id} lock released")
# Usage:
DAILY_REPORT_JOB_ID = 1001 # Stable integer ID for this job
run_with_pg_advisory_lock(DAILY_REPORT_JOB_ID, send_daily_report)
Option 5: Heartbeat lock — handles job crashes gracefully
import threading
import time
class HeartbeatLock:
"""
Redis lock with heartbeat — prevents lock expiry during long jobs,
but releases if job crashes (heartbeat stops).
"""
def __init__(self, key: str, ttl: int = 30):
self.key = key
self.ttl = ttl
self.instance = str(uuid.uuid4())[:8]
self._heartbeat_thread = None
self._running = False
def acquire(self) -> bool:
acquired = redis_client.set(self.key, self.instance, nx=True, ex=self.ttl)
if acquired:
self._start_heartbeat()
return bool(acquired)
def _start_heartbeat(self):
"""Renew lock every TTL/2 seconds — keeps lock alive during long jobs"""
self._running = True
def heartbeat():
while self._running:
time.sleep(self.ttl // 2)
if self._running:
# Renew only if we still own the lock
current = redis_client.get(self.key)
if current == self.instance:
redis_client.expire(self.key, self.ttl)
self._heartbeat_thread = threading.Thread(target=heartbeat, daemon=True)
self._heartbeat_thread.start()
def release(self):
self._running = False
current = redis_client.get(self.key)
if current == self.instance:
redis_client.delete(self.key)
def __enter__(self):
if not self.acquire():
raise RuntimeError(f"Lock {self.key} already held")
return self
def __exit__(self, *args):
self.release()
Scheduler Duplicate Execution Causes
| Cause | Description | Fix |
|---|---|---|
| Multiple scheduler nodes | 2+ servers run cron on same schedule | Distributed lock |
| Rolling deploy overlap | Old + new instance both start at schedule time | Lock + job log |
| k8s CronJob default | concurrencyPolicy: Allow by default |
Set to Forbid |
| Scheduler restart | Missed-then-caught-up jobs fire twice | startingDeadlineSeconds |
| At-least-once delivery | Job queue delivers same job twice | Database idempotency key |
| Clock skew | Two servers’ clocks differ by seconds | Lock with TTL tolerance |
Expected Token Savings
Duplicate job sends 10,000 emails twice → incident + rollback: ~200,000 tokens + reputation Distributed lock prevents duplicates: 0 wasted
Environment
- Any distributed agent deployment with scheduled jobs; critical for email, billing, and data processing agents
- Source: direct experience; scheduler duplicates are the most common cause of double-email and double-charge incidents
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