It&#x27;s a good chart if you want to teach people the commands needed for trouble shooting.

Flowchar looks pretty straightforward to me. Nothing I&#x27;d categorize as complicated.

Note that this flowchart includes monitoring, logging, and networking, in addition to typical app stuff. Of course it&#x27;s complicated.The article does contain a lot of useful information. I don&#x27;t think it was intended to ride the &quot;k8s is too complicated compared to vanilla X&quot; bandwagon, despite the huge flowchart at the top.

I like how it has quite a few boxes that say &quot;no idea what the reason might be&quot;. Each one of them hides another chart as big as this one, if not bigger.

This is true of anything, not just k8s. There is always a possibility of all system monitors to be green but the apps dead&#x2F;bad for some reason. This is why you need more than system monitors. You need app monitoring as well.

Fun fact, on GCP Kubernetes you can have green lightbulbs on every single dashboard, and your entire site can be down anyway.Our CI&#x2F;CD was leaking &quot;review&quot; deployments, I forgot about them until one day I upgraded a node and the entire site went down, even though everything was green. Turned out there is some sort of naximum amount of nginx entries in ingress and we were hitting it. That was some frantic debugging, solution was just to delete the spurious review deployments.

Try <a href="https:&#x2F;&#x2F;magick8sball.github.io&#x2F;" rel="nofollow">https:&#x2F;&#x2F;magick8sball.github.io&#x2F;</a> for those scenarios. :)

I enjoyed petulantly answering every question with “no” and the funding the final state to be “Consult Stackoverflow”

Yes, depending on why k8s kills and restarts your pod.If your pod&#x27;s `cmd` is the cause of the crash, simply replace it with `sleep 50000` which will allow you to then get a shell to debug the crashing cmd (granted your container image has a shell available).If your pod is getting killed by its Deployment (because of a scale down for example), simply &quot;edit&quot; the pod (`kubectl edit pod [pod-name]`) and change its deployment name to some inexistant deployment prior to exec-ing a shell. This basically orphans the pod from its deployment; you will need to manually delete it afterwards.If your pod is getting killed by k8s because it&#x27;s exceeding its resource `limits`, edit the pod manifest and remove the limits (again, using `kubectl edit pod`)In the end, it basically mostly comes down to editing the pod&#x27;s manifest file and removing the things that could instruct k8s to restart your pod. Another thing would be to remove the `livenessProbes`.

Depends on why it is getting restarted. If it&#x27;s exceeding mem limits and being oomkilled that&#x27;s the kernel, not k8s. If PID 1 inside the namespace is terminating then k8s will restart the pod. No way to prevent that I am aware of, but presumably you can&#x27;t do much debugging once that happens anyway. If the process is failing liveness probes and getting terminated for being unhealthy probably the simplest approach is just to patch away those probes until you have the workload stable.

If pod logs (`kubectl logs pod-name-hash`) and `kubectl describe` is not giving you useful info, then try checking the Event Logs with `kubectl get events` in the pod&#x27;s namespace [0].In OpenShift (I&#x27;m a Red Hat Consulting Architect), we have the ability to debug Pods (Failed, Running, or otherwise), DeploymentConfigs (Deployments), some other things, but not BuildConfigs. You just do something likes `oc debug pod-name-hash` or `oc debug deployment&#x2F;deployment-name` [1]. What this does is start up the Pod with all the configuration (ConfigMaps, Env Vars, Mounts, Secrets, etc.) but replaces CMD&#x2F;ENTRYPOINT with a shell using `&#x2F;bin&#x2F;sh`. This might be magic bits we&#x27;ve added to our `oc&#x2F;kubectl` (they&#x27;re one in the same in OpenShift) but I don&#x27;t see references for similar functionality in Kubernetes. Useful for identifying where a configuration may be slight off what you or CMD&#x2F;ENTRYPOINT are expecting.[0] <a href="https:&#x2F;&#x2F;kubernetes.io&#x2F;docs&#x2F;reference&#x2F;kubectl&#x2F;cheatsheet&#x2F;#viewing-finding-resources" rel="nofollow">https:&#x2F;&#x2F;kubernetes.io&#x2F;docs&#x2F;reference&#x2F;kubectl&#x2F;cheatsheet&#x2F;#vie...</a>[1] <a href="https:&#x2F;&#x2F;cookbook.openshift.org&#x2F;logging-monitoring-and-debugging&#x2F;how-do-i-debug-an-application-that-fails-to-start-up.html" rel="nofollow">https:&#x2F;&#x2F;cookbook.openshift.org&#x2F;logging-monitoring-and-debugg...</a>

Not as far as I can tell, and as far as I&#x27;m concerned it is the biggest pain point when debugging k8s problems. If your pods is cycling though CrashLoopBackOff and &#x27;describe&#x27; has no useful information and the &#x27;logs&#x27; don&#x27;t give you a clue, you are flat out of luck. That pod is gone before you can extract any useful information from it.I&#x27;d like to see some means of keeping a pod running even if the application is crashing. Sometimes logs are being sent to a file, sometimes running the application manually gives a clue. Lacking that - well I&#x27;ve found various tricks such as changing the image to &#x27;ubuntu&#x27; and replacing the command with &#x27;tail -f &#x2F;dev&#x2F;null&#x27; so a crashing pod will stay alive and I can exec into it and run the real command by hand. But it&#x27;s a hack and doesn&#x27;t always get the info you need.

What if you docker exec the container? Kubernetes is running docker containers anyway, right? The environment would be very similar

restartPolicy is set to Always by default in the podspec. So, change it to Never, and see whether it helps.

Is there a way to prevent Kubernetes from killing and restarting a pod (from a deployment) when you are debugging it with kubectl exec -it? I.E. inform Kubernetes I am using this pod, don’t restart it automatically.

All the CLI commands used have been in for quite a few “minor” versions. I’d say it’s probably valid for the foreseeable future for debugging k8s _primitive_ resources.With the customization you can do to k8s the debugging can get a bit more weird when dealing with operators and web hooks.

Haven&#x27;t had to work with k8s yet, but that flow chart looks really detailed. It must have taken much effort to make it, that makes me wonder, for how long shall it remain current? Will 6 months down the line it become invalid in subtle manner that it can only add to the confusion.

Kubectl randomly hanging sounds like a problem with the Metrics api. You can use -v9 on kubectl and see what it’s pausing on. Note that metrics aren’t refreshed every single run - instead on a timer - hence the “random” feel

What about kubectl randomly hanging and some PLEG errors in the kubelet log?

Looking at this I think it would be really cool for someone to build a Wheel of Misfortune to help dry run some of these scenarios for debugging.

Tickles my funny bone every time I see the industry jump on a new bandwagon that starts simple and then inevitably adapts to the real world that the old technology was addressing. When are we gonna learn folks?Props to the author for the chart. He&#x27;s actually providing real value to all the suckers, err, SREs stuck dealing with this stuff.

It’s 11 commands to debug everything about an application deployment... from downloading the docker image all the way to debugging the load balancer. Most git cheat sheets have 3 times the number of commands.Most of the diamonds listed here aren’t things you have to remember, they’re statuses that are explicitly called out in the responses of those commands. This is an over-complicated chart that in reality is summed up as: look at the pod, look at the service, look at ingress.

Every other large-ish product I&#x27;ve maintained would have a chart at least this large. Complex systems are complicated to maintain, regardless of platform.

I dunno, I did an install using the k8s install instructions, and got to a point where I could access the containers locally but not from other nodes in the cluster. I could see a bunch of routing and iptables rules, but I didn&#x27;t have any model for what it SHOULD look like, so I was at a loss for untangling all that spaghetti.

&gt; manually done &#x2F; bash script powered &#x2F; ansible deploymentsSure but I am not comparing it against manually done &#x2F; bash script powered &#x2F; Ansible deployments. Even if I was the CI&#x2F;CD pipeline would capture many of the problems early and than I have an immutable AMI with autoscaling groups that is very easy to debug, networking setup is super simple and load-balancing is also straightforward to troubleshoot. Cramming all of these into a simple project that is not as easy to debug is not worth the effort for us.

There are for sure a few concepts you need to learn with k8s, however I wonder if it would be much shorter if you did a guide like this for manually done &#x2F; bash script powered &#x2F; ansible deployments

Yeah, but I also happened to run into production problems non of the k8s exports could fix or even pinpoint why it was happening.

&gt; I guess I can just print this out and show to people any time somebody wants to move to k8s.A complete flow chart of all the possible states for any non-trivial thing appears complex. In practice the actual problems you run into are part of a much smaller set of possibilities.

I&#x27;m somewhat sure you could make a similarly complicated looking chart that would entail:- using ping- sshing into a box- using ssh port forwarding- using ps aux- understanding system load- understanding oom killer messages- is this systemd? use systemctl, otherwise figure it out- is this systemd? use journalctl, otherwise figure out where an app is logging- is nginx running? what box is it running on?- is the nginx config okay?- what about haproxy? are health checks going through?Plus dealing with whatever configuration management system you&#x27;re using, credential store you&#x27;re using, etc.Kubernetes, while complex, does take over a huge chunk of responsibilities from existing deployments. As such, a large part of any debugging will be done via kubectl and on a much different level of abstraction than if you were dealing with individual machines and services deployed on them via Ansible.Yes, there&#x27;s new things to learn. But for many cases (not even just scale!) it&#x27;s quite worth it.

Well yes, people who already pay for external cloud providers running k8s for little business value is a meme at this point. If you are creating a cloud provider though then you&#x27;re very much welcome to use k8s.

I understand that Kubernetes is a complex project, but I struggle to see how this comment adds to the discourse.For those that do need a solution like Kubernetes, charts like this are helpful, and the knowledge requirements certainly aren&#x27;t too steep relative to comparable platforms.What about Kubernetes makes it especially worth going in and commenting that you don&#x27;t have a use case for it, in a thread dedicated to Kubernetes? Would you make similar comments about other platforms&#x2F;libraries&#x2F;technologies that you, for whatever reason, don&#x27;t have a use case for?

My thoughts exactly. It&#x27;s too complex for anything I&#x27;v ever needed.

Well HN turned into this place where you cannot have a decent discussion anymore, there is the downvoter crew and if you dare to disagree with them they nuke your comments. Unfortunate.

Only sane response here and being downvoted to Oblivion.

I guess I can just print this out and show to people any time somebody wants to move to k8s.

A visual guide on troubleshooting Kubernetes deployments