title: Celery Does Not Process Task in Kubernetes with Redis
body: <p>I'm running a Kubernetes cluster with three Celery pods, using a single Redis pod as the message queue. Celery version 4.1.0, Python 3.6.3, standard Redis pod from helm.</p>
  
  <p>At a seemingly quick influx of tasks, the Celery pods to stop processing tasks whatsoever. They will be fine for the first few tasks, but then eventually stop working and my tasks hang.</p>
  
  <p>My tasks follow this format:</p>
  
  <pre><code>@app.task(bind=True)
  def my_task(some_param):
      result = get_data(some_param)
  
      if result != expectation:
          task.retry(throw=False, countdown=5)
  </code></pre>
  
  <p>And are generally queued as follows:</p>
  
  <pre><code>from my_code import my_task
  my_task.apply_async(queue='worker', kwargs=celery_params)
  </code></pre>
  
  <p>The relevant portion of my <code>deployment.yaml</code>:</p>
  
  <pre><code>command: ["celery", "worker", "-A", "myapp.implementation.celery_app", "-Q", "http"]
  </code></pre>
  
  <p>The only difference between this cluster and my local cluster, which I use <code>docker-compose</code> to manage, is that the cluster is running a <code>prefork</code> pool and locally I run <code>eventlet</code> pool to be able to put together a code coverage report. I've tried running <code>eventlet</code> on the cluster but I see no difference in the results, the tasks still hang.</p>
  
  <p>Is there something I'm missing about running a Celery worker in Kubernetes? Is there a bug that could be affecting my results? Are there any good ways to break into the cluster to see what's actually happening with this issue?</p>