RunpodR
Runpod•4w ago
ivanychev

Pod restarts container instead of termination

TL;DR: Pod always restarts Docker command, never leaves RUNNING state. Company blog claims otherwise.

Hi there! I was trying to implement running a one-off job using ECR-based Docker image on RunPod.

I'd like to create a Pod that uses a Docker container from AWS ECR, run the command, let the Pod finish the commant. Using polling I want to poll the Pod status and terminate the pod as soon as it finishes

Basically, this approach described in the company blog: https://www.runpod.io/articles/guides/ai-on-a-schedule

Design your container or job to exit when finished. If it’s a one-off batch job, ensure the container’s command will naturally terminate (and not linger).

Problem: a created pod doesn't terminate, it restarts the container command and never actually finishes. What I did:

  1. Created a template that points to a container in my AWS ECR
  2. Ran a pod
  3. I observe the following logs:
start container for ***.dkr.ecr.us-east-1.amazonaws.com/***:jenkins-7264_env.gpu: begin
start container for ***.dkr.ecr.us-east-1.amazonaws.com/***:jenkins-7264_env.gpu: begin
start container for ***.dkr.ecr.us-east-1.amazonaws.com/***:jenkins-7264_env.gpu: begin


get_pod(...) call returns

{'id': '45bdrcye8ykr8w', 'containerDiskInGb': 10, 'costPerHr': 0.4, 'desiredStatus': 'RUNNING', 'dockerArgs': 'echo hello RunPod', 'dockerId': None, 'env': [...], 'gpuCount': 1, 'imageName': '***.dkr.ecr.us-east-1.amazonaws.com/***:jenkins-7264_env.gpu', 'lastStatusChange': 'Rented by User: Thu Nov 27 2025 18:21:59 GMT+0000 (Coordinated Universal Time)', 'machineId': 'eqqacoug796e', 'memoryInGb': 50, 'name': 'sergey-test-3', 'podType': 'RESERVED', 'port': None, 'ports': '', 'uptimeSeconds': 0, 'vcpuCount': 9, 'volumeInGb': 0, 'volumeMountPath': '/runpod-volume', 'runtime': {'ports': None}, 'machine': {'gpuDisplayName': 'A40'}}


The command I run is echo "Hello RunPod".

The pod always restart the command and never leaves RUNNING state. What am I missing?
Runpod
AI on a Schedule: Using Runpod’s API to Run Jobs Only When Needed
Explains how to use Runpod’s API to run AI jobs on a schedule or on-demand, so GPUs are active only when needed. Demonstrates how scheduling GPU tasks can reduce costs by avoiding idle time while ensuring resources are available for peak workloads.
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