April 10, 2024

Kubernetes CrashLoopBackoff: An Ultimate Guide

Omkar Kulkarni
QA Engineer

CrashLoopBackOff errors slowing your Kubernetes deployments? In this article, you will learn what causes pods to get stuck restarting, see an example, and apply fixes to get out of the CrashLoopBackOff state for good. No more wasted cycles or downtime.

Understanding the pod phases in Kubernetes

In general, when you submit the YAML configuration file to create a pod (resource) in Kubernetes the Kube API Server validates the YAML configuration and makes it available. Simultaneously, the Kube-Scheduler watches for new pods for scheduling to nodes based on resource requirements. 

Fig - Kubernetes Pod status values

You can simply check the above pod phases with the below command:

$ kubectl get pod

Understanding various container states in a pod 

As mentioned above, there are different phases of the pod, similarly, Kubernetes tracks the status of each container inside the pod. There are three states while creating and tracking the status of the pod’s containers “Waiting”, “Running”, and “Terminated”. When the Kubernetes scheduler starts scheduling pods to the nodes, the Kubelet starts creating containers for specific pods using a container runtime. 

You can check the container state using: 

$ kubectl describe pod <name-of-pod>  

Fig - Kubernetes container states descriptive

What is the Kubernetes CrashLoopBackOff?

In Kubernetes, the “CrashLoopBackOff” state indicates that the pod is stuck in a restart loop. It means that one or more containers in a pod fail to start successfully.

In general, in a pod, the container starts then it crashes and restarts over and over again this is called a “CrashLoop”. 

What does it mean BackOff time and why is it important?

The BackOff algorithm is a simple technique that is used in the networking and computer science field to retry tasks in case of failure. Imagine you’re trying to send a simple message to your friend but it fails due to some reason, in case of try immediately the algorithm says just wait a little bit before we try again. 

So basically, for the first time you try and fail, the second time you wait for some short period and then try again. If it still fails, you wait a bit longer period and then try again. The ‘backoff’ term explains that the waiting period gradually increases each time with the loop. This gives the system or network time to recover from the error and prevents overwhelming responses. 

The “BackOff” time is delayed after the pod is terminated and trying to restart. This back-off time gives the pod the time to recover and resolve the error. This means a set of backoff intervals delays restart. 

For example, If a pod fails to start running by default (kubelet configuration)   restart time is 10 seconds. It’ll increase to multiply by 2 usually. 

So initial backoff duration is 10 seconds, if a pod fails after that the next attempt of retry will be 20 seconds then 40 seconds then 80 seconds, and so on.  This increased time is used by kubelet and sends new API requests to start a container inside a pod.

A quick understanding of Kubernetes restart policy

As you read above, Kubernetes tries to restart a pod when it fails. In Kubernetes, pods are designed to be self-healing entities. This means they can automatically restart containers that encounter errors or crashes.

This behavior is controlled by a configuration called the "restartPolicy" within the pod's specification. By defining the restart policy, you dictate how Kubernetes handles container failures. The possible values are “Always", “OnFailure”, and “Never”. The default value is “Always”.

K8s restart policy configuration

apiVersion: v1
kind: Pod
  name: my-nginx
  - name: nginx
    image: nginx:latest
    - containerPort: 80
  restartPolicy: Always    #restart policy

How you can detect the Kubernetes CrashLoopBackOff

You can check the status of your pod using simply the kubectl command. 

As far as you execute this command you’ll see an output similar to the above details. You can see the my-nginx pod is 

  1. Not in `Ready` state
  2. It has the status “CrashLoopBackOff” 
  3. The number of restarts is one or more

As we discussed above the same condition happening here. The pod is failing and tries several times to start again. This period is described here as CrashLoopBackOff status. You may find the reason for restarts or failure during this back-off time. 

If you’re using PerfectScale you can see the Alerts tab in which you can get critical alerts regarding your Kubernetes resources to inform you about the unusual system activity. 

You can simply go to the “Alerts tab” and monitor and deal with specific alerts. Also, you can see the detailed alert summary regarding single tenant. 

Common reasons for a K8s CrashLoopBackOff

1. Kubernetes Resource constraints 

Memory allocation plays a crucial role in ensuring the smooth functioning of your Kubernetes deployments. If a pod's memory constraints aren't carefully considered, you might encounter the dreaded CrashLoopBackOff state.  

For example, if your application requires more memory than what’s allocated, it can lead to OOM (Out Of Memory). This can create Kubernetes CrashLoopBackOff. 

2. Image related issues

  •  Insufficient permissions - If you are using a container image that does not have the necessary permissions to access your resources, the container may crash. 
  • Incorrect container Image - If your pod pulls an incorrect container image to start a container, it leads to crashes and restarts again & again. 

The above conditions lead to the Kubernetes CrashLoopBackOff error.

3. Configuration Errors

  • Syntax error or Typos - While configuring the Pod spec, there may be mistakes such as typos in container names, image names, and environment variables, which can prevent containers from starting correctly.
  • Incorrect Resource Requests & Limits - Mistakes in configuring Requested resources (minimum amount needed) & limits (Maximum amount allowed) may lead to container crashes and not started correctly. 
  • Missing dependencies - In your Pod spec file, if any services need dependencies that are missing can lead to the failure of the container. 

4. External service issues

  • Network Issue - If your container relies on any external service for example database, and that external service is not reachable at that point or is unavailable this can lead to k8s CrashLoopBackOff. 
  • If one of the external services is down itself and your container in a pod relies on that can lead to container failure due to the container failing to connect.  

5. Uncaught Application Exceptions

When a containerized application encounters an error or exception during runtime, it may cause the application to crash. These errors could be due to various reasons such as invalid input, resource constraints, network issues, file permission issues, misconfiguration of secrets, and environmental variables or bugs in the code. If the application code does not have proper error-handling mechanisms to catch and handle these exceptions gracefully, can trigger the CrashLoopBackOff state in Kubernetes. 

6. Misconfigured Liveness Probes

Liveness probes exist to ensure that the process in your container isn’t stuck in a deadlock. If it is - the container will get killed and restarted (if the Pod’s restartPolicy defines so). A common mistake is configuring a liveness probe so that it causes a container to restart because of a temporary slowness (which can happen if the pod is under heavy load) which can only exacerbate the problem instead of resolving it.

How to troubleshoot & fix CrashLoopBackOff? 

From the previous section, you understand that there are several reasons why Pod ends in CrashLoopBackOff state. Now, let’s dive into how you can troubleshoot Kubernetes CrashLoopBackOff with various methods. 

The common thing for troubleshooting is first finding potential scenarios and finding the root cause by debugging and eliminating them one by one. 

When you execute the ` kubectl get pods ` command you can see the status of the pod is CrashLoopBackOff 

$ kubectl get pods 
NAME                        READY   STATUS             RESTARTS         AGE
app                         1/1     Running            1 (3d12h ago)    8d
busybox                     0/1     CrashLoopBackOff   18 (2m12s ago)   70m 
hello-8n746                 0/1     Completed          0                8d
my-nginx-5c9649898b-ccknd   0/1     CrashLoopBackOff   17 (4m3s ago)    71m
my-nginx-7548fdb77b-v47wc   1/1     Running            0                71m

Let’s go one by one - 

1. Check the description of the Pod - 

The command `kubectl describe pod pod-name` gives detailed information about specific pods and containers. 

$ kubectl describe pod pod-name 

Name:           pod-name
Namespace:      default
Priority:       0
State:         Waiting
Reason:        CrashLoopBackOff
Last State:    Terminated
Reason:        StartError
Warning  Failed   41m (x13 over 81m)   kubelet  Error: container init was OOM-killed (memory limit too low?): unknown

When you execute kubectl describe pod you can extract meaningful information from the output such as, 

State - waiting 

Reason -CrashLoopbackOff

Reason - StartError

From this, we can figure out the reasons behind CrashLoopBackOff. From the final lines of the output “ kubelet  Error: container init was OOM-killed (memory limit too low?)” you can understand that the container is not starting due to Out Of Memory. 

2. Check Pod logs

Logs are detailed information related to a specific resource in Kubernetes from the starting container, any obstacle, termination, or even successful completion.

Check pod logs using these specific commands 

` $ kubectl logs pod-name `  - extract the logs of the pod having only one container.

Check logs of the pod having multiple containers.

` $ kubectl logs pod-name --all-conainers=true

You can check pod logs for a particular time interval. For example, if you want to check logs from the last 1 hour simply execute the -

` $ kubectl logs pod-name --since=1h ` 

3. Check events

Events are the most recent information about your Kubernetes resources. You can request events for a specific namespace or filter to any particular workload.  

$ kubectl events 
LAST SEEN               TYPE      REASON    OBJECT                          MESSAGE
4h43m (x9 over 10h)     Normal    BackOff   Pod/my-nginx-5c9649898b-ccknd   Back-off pulling image "nginx:latest"
3h15m (x11 over 11h)    Normal    BackOff   Pod/busybox                     Back-off pulling image "busybox"
40m (x26 over 13h)      Warning   Failed    Pod/my-nginx-5c9649898b-ccknd   Error: failed to create containerd task: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: container init was OOM-killed (memory limit too low?): unknown

You can easily see all events related to resources as in the above output. 

  • List all recent events in all namespaces. 
$ kubectl get events --all-namespaces 
  • List all events for a specific pod 
$   kubectl events --for pod/pod-name

4. Check deployment logs 

$ kubectl logs deployment deployment-name 

Found 2 pods, using pod/my-nginx-7548fdb77b-v47wc
/docker-entrypoint.sh: /docker-entrypoint.d/ is not empty, will attempt to perform configuration
/docker-entrypoint.sh: Looking for shell scripts in /docker-entrypoint.d/
/docker-entrypoint.sh: Launching /docker-entrypoint.d/10-listen-on-ipv6-by-default.sh
10-listen-on-ipv6-by-default.sh: info: Getting the checksum of /etc/nginx/conf.d/default.conf
10-listen-on-ipv6-by-default.sh: info: Enabled listen on IPv6 in /etc/nginx/conf.d/default.conf
/docker-entrypoint.sh: Sourcing 

You can debug the deployment using deployment logs and may figure out the reasons for crashing the containers and why the pod ends in the CrashLoopBackOff state. 

In this article, we have studied the in-depth guide on Kubernetes CrashLoopBackOff. Which is not in itself an error but a state. 

We dig into the common CrashLoopBackOff state, analyze a sample case, and provide fixes to get your pods back on track. Everything you need to troubleshoot and resolve this error.

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CrashLoopBackOff errors slowing your K8s deployments? This comprehensive guide examines the K8s CrashLoopBackOff state, a real-world example, and proven fixes.
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