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Why one replica becomes several schedulers
An in-process scheduler is a loop or timer started when the process boots. It has no knowledge of other copies of the same application. With one replica, the loop fires once per trigger. With three, the image starts three loops, and nothing asks whether another loop already claimed the run. The scheduler is replicated along with the code, which is why the duplicate feels like a surprise even though the design does exactly what it was written to do.
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The symptom usually appears after a scale-up, during a rolling deployment that briefly overlaps old and new Pods, or when a crashed replica restarts while its siblings keep running. A nightly invoice run, an email digest, or a cache rebuild then executes several times, and the logs show near-identical timestamps from different instances.
Three layers that are easy to confuse
Most of the confusion comes from treating “scheduling” as one thing. In a Kubernetes cluster, three components are involved, and each does a different job.
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| Layer | What it does | What it does not do |
|---|---|---|
| Application replica (your code, including any in-process cron library) | Runs its own timer and executes the task when the timer fires | Know that other replicas exist, unless you add coordination |
| CronJob controller | Creates a Job object on the schedule defined in a CronJob resource | Run your code inside your web or API Pods |
| Job controller | Creates and tracks the Pods belonging to each Job, and creates replacements when Pods fail or are deleted | Decide when a schedule fires |
| kube-scheduler | Assigns Pods to Nodes | Decide whether an application’s internal cron loop should run in each replica |
Moving work from the application into a CronJob removes the timer from every replica, but it adds a new object you must configure correctly. The kube-scheduler is rarely the cause of duplicate runs: it places Pods, and a duplicate-run bug is almost always about which component starts the work.
What a Kubernetes CronJob does and does not guarantee
The Kubernetes CronJob documentation, checked on 7 October 2026, is explicit about two limits. First, scheduling is approximate: in some circumstances the controller can create more than one Job for a single scheduled time, or none. Second, it states that “the Jobs that you define should be idempotent.” A CronJob is a better home for scheduled work than a timer in every replica, but it does not turn a scheduled task into an exactly-once operation.
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Job retries are a second source of repeats. A Kubernetes Job can start another Pod when a Pod fails or is deleted, so a task that partly completed before failing may run again. The task has to tolerate retries, whichever component started it.
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Option A: the work is a batch operation and you run on Kubernetes
This is usually the cleanest route. Move the schedule out of the application into a batch/v1 CronJob, and use the application image as the Job’s container. A minimal manifest looks like this:
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apiVersion: batch/v1
kind: CronJob
metadata:
name: nightly-invoice-run
spec:
schedule: "0 2 * * *"
timeZone: "Europe/Berlin"
concurrencyPolicy: Forbid
startingDeadlineSeconds: 600
jobTemplate:
spec:
backoffLimit: 2
template:
spec:
restartPolicy: Never
containers:
- name: invoice-run
image: registry.example.com/billing:1.8.2
args: ["--task", "nightly-invoice-run"]Apply it with kubectl apply -f nightly-invoice-run.yaml, then confirm the schedule with kubectl get cronjob nightly-invoice-run and watch Job creation with kubectl get jobs --watch. Remove the in-process timer in the same release, or the duplicate will persist.
Three fields need deliberate choices:
- timeZone: set
spec.timeZoneexplicitly. Without it, the controller interprets the schedule in its own local zone, which may not match what your team means. The field is stable from Kubernetes v1.27. - concurrencyPolicy: choose it from the table below.
- startingDeadlineSeconds: limits how late a missed run may still start. Without a deadline, a long outage can lead the controller to try to catch up on many missed runs.
Choosing a concurrencyPolicy
| Policy | Behavior when the previous Job is still running | Use it when |
|---|---|---|
Allow (default) |
Starts a new Job, so runs can overlap | Runs are independent and idempotent, and overlap is harmless |
Forbid |
Skips the new occurrence until the earlier Job finishes | Overlap would corrupt data or double-send messages, and skipping one run is acceptable |
Replace |
Cancels the running Job and starts a new one | Only the latest run matters and a stale run should be discarded |
These policies apply only among Jobs created by the same CronJob resource. Forbid is not a cluster-wide lock. If two CronJob objects, or two clusters, can run the same logical task, you need a lock or unique key in your own system.
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Option B: the process must remain the scheduler
Sometimes the schedule depends on application state, or the team cannot move it. In that case, keep the timer but let only one replica act on it. The Kubernetes Lease documentation describes Leases as a way to “select or elect a leader” among controller replicas, and the same mechanism works for custom workloads. The lease records its current holder and renewal time. If the holder stops renewing, another candidate can take over once the lease expires.
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A workable pattern:
- Create a dedicated Lease name for this scheduler, such as
billing-invoice-scheduler, tied to the component so unrelated installations do not collide. - Grant the application’s ServiceAccount permission to get, create, and update that Lease in its namespace, through a Role and RoleBinding.
- Have every replica attempt to acquire the lease on each tick. Only the holder runs the scheduled work; the others return without acting.
- Keep the renewal interval well below the lease duration so a healthy leader does not lose the lease by accident.
Leader election reduces duplicates but does not make a side effect happen once. A leader can lose connectivity or stop partway through a write, and its successor can retry the same run. Use the lease to choose the active scheduler, and protect the work itself as described next.
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Option C: the runtime is not Kubernetes
The principle is the same on any platform. Either elect one scheduler across replicas through a coordination store you already run, or move the schedule into a single dedicated scheduling service. The right primitive depends on your database, your deployment model, and how you want the system to behave during a network partition. Some teams accept a skipped run during a partition; others prefer a delayed run after recovery. Decide that before choosing a tool.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Make the work safe to run twice
Whichever option you choose, the task should produce the same result when it runs more than once for the same logical period. Three techniques cover most cases:
- Idempotency key per run: derive a key from the task name and the scheduled period, for example
nightly-invoice-run:2026-10-09, and pass it to every external call that accepts one. - Durable run record with a unique constraint: insert a row before doing the work, so a second attempt fails on the constraint.
- Transaction boundary: where your database allows it, write the business effect and the run record in the same transaction.
CREATE TABLE scheduled_runs (
task_name text NOT NULL,
run_period date NOT NULL,
started_at timestamptz NOT NULL DEFAULT now(),
PRIMARY KEY (task_name, run_period)
);
-- Each replica or retry attempts this first.
-- Zero rows returned means another run already claimed the period.
INSERT INTO scheduled_runs (task_name, run_period)
VALUES ('nightly-invoice-run', '2026-10-09')
ON CONFLICT DO NOTHING
RETURNING task_name;This guard also covers cases the scheduling mechanisms miss: a second CronJob object, a manual re-run, or a retry after a timeout. The database does not care which scheduler asked.
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- Duplicates appear only after a scale-up: an in-process timer is still active in the new replicas. Log the scheduler start message with the Pod name and check whether every replica prints it.
- Duplicates appear during a rolling update: old and new versions overlap briefly. Keep the timer in only one version of the workload, or gate it behind the leader lease for the whole rollout.
- Two Jobs appear for one scheduled time: this is the approximate-creation behavior described in the CronJob documentation. Make the Job idempotent rather than trying to stop the controller from creating it.
- A run is missing: check
startingDeadlineSeconds, whetherconcurrencyPolicy: Forbidskipped it because a previous Job was still active, and whether the time zone matches your expectation. - A Job retried after partial success: the task is not idempotent. Add the run-record guard before changing the schedule.
Sources and check dates
The Kubernetes statements in this article come from the official documentation pages for CronJob, Jobs, Leases, Coordinated Leader Election, and the Kubernetes scheduler, as checked on 7 October 2026. Version-specific fields and behavior can change, so confirm them against the documentation for your cluster version before relying on them.
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