I have used the exact same commands to first create the persistent volume and persistent volume chain and then deployed the contents of the mysql yaml file as per the documentation. The mysql pod is not running and is in RunContainerError state.
Checking the logs of this mysql pod shows:. This is because you do not need to create those volumes and storageclasses on GKE. Those yaml files are completely valid if you would want to use minikube or kubeadm, but not in case of GKE which can take care of some of the manual steps on its own. Learn more. Asked 11 months ago. Active 11 months ago. Viewed times.
Rajesh Gupta. Rajesh Gupta Rajesh Gupta 2, 2 2 gold badges 8 8 silver badges 19 19 bronze badges. Active Oldest Votes. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password.
Post as a guest Name. Email Required, but never shown.
The Overflow Blog. The Overflow How many jobs can be done at home? Featured on Meta. Community and Moderator guidelines for escalating issues via new response…. Feedback on Q2 Community Roadmap. Triage needs to be fixed urgently, and users need to be notified upon…. Dark Mode Beta - help us root out low-contrast and un-converted bits.
Technical site integration observational experiment live on Stack Overflow. Related Hot Network Questions.DevOps engineers wishing to troubleshoot Kubernetes applications can turn to log messages to pinpoint the cause of errors and their impact on the rest of the cluster. When troubleshooting a running application, engineers need real-time access to logs generated across multiple components.Kubernetes Audit Log - Gold Mine For Security
The challenge that engineers face is accessing comprehensive, live streams of Kubernetes log data. While some solutions exist today, these are limited in their ability to live tail logs or tail multiple logs.
When interacting with Kubernetes logs, engineers frequently use two solutions: the Kubernetes command line interface CLIor the Elastic Stack. The default logging tool is the command kubectl logs for retrieving logs from a specific pod or container.
Running this command with the --follow flag streams logs from the specified resource, allowing you to live tail its logs from your terminal. Using kubectl logs --follow [Pod name]we can view logs from the pod in real time:. The main limitation of kubectl logs is that it only supports individual Pods. If we deployed two Nginx pod replicas instead of one, we would need to tail each pod separately. For large deployments, this could involve dozens or hundreds of separate kubectl logs instances.
Using Papertrail, you can view real-time log events from your entire Kubernetes cluster in a single browser window. Papertrail shows all logs by default, but you can limit these to a specific pod, node, or deployment using a flexible search syntax. If we used kubectl logs -fwe would need to run it three times: one for each pod.
Subscribe to RSS
With Papertrail, we can open the Papertrail Event Viewer and create a search that filters the stream to logs originating from the papertrail-demo deployment. Not only does this show us output from each pod in the deployment, but also Kubernetes cluster activity related to each pod:.
The most effective way to send logs from Kubernetes to Papertrail is via a DaemonSet. DaemonSets run a single instance of a pod on each node in the cluster. The pod used in the DaemonSet automatically collects and forwards log events from other pods, Kubernetes, and the node itself to Papertrail. From a computer with kubectl installed, download fluentd-daemonset-papertrail. You can also change the Kubernetes namespace that the DaemonSet runs in by changing the namespace parameter. When you are done, deploy the DaemonSet by running:.
When deploying an application, make sure to route its logs to the standard output stream. The Logspout DaemonSet is limited to logging containers. The Fluentd DaemonSet, however, will log your containers, pods, and nodes. In addition to logging more resources, Fluentd also logs valuable information such as Pod names, Pod controller activity, and Pod scheduling activity. This way you can see the results of your actions after you execute them.
This also saves you from having to tail manually in your terminal. Kubernetes pods and containers in general are ephemeral and often have randomly generated names. Unless you specify fixed names, it can be hard to keep track of which pods or containers to filter on. A solution is to use log groupswhich let you group logs from a specific application or development team together. This helps you find the logs you need and hide everything else.
Papertrail lets you save your searches for creating custom Event Viewer sessions and alerts. You can reopen previously created live tail sessions, share your sessions with team members, or receive an instant notification when new log events arrive in the stream.As part of operating an AKS cluster, you may need to review logs to troubleshoot a problem. Occasionally, you may need to get kubelet logs from an AKS node for troubleshooting purposes.
This article shows you how you can use journalctl to view the kubelet logs on an AKS node. This article assumes that you have an existing AKS cluster. First, create an SSH connection with the node on which you need to view kubelet logs. Once you have connected to the node, run the following command to pull the kubelet logs:. If you need additional troubleshooting information from the Kubernetes master, see view Kubernetes master node logs in AKS.
You may also leave feedback directly on GitHub. Skip to main content. Exit focus mode. Learn at your own pace. See training modules. Dismiss alert. Before you begin This article assumes that you have an existing AKS cluster. Get kubelet logs Once you have connected to the node, run the following command to pull the kubelet logs: sudo journalctl -u kubelet -o cat The following sample output shows the kubelet log data: I Related Articles Is this page helpful? Yes No. Any additional feedback?
Skip Submit. Send feedback about This product This page. This page. Submit feedback. There are no open issues. View on GitHub. Is this page helpful?Maintaining a Kubernetes cluster is an ongoing challenge. While it tries to make managing containerized applications easier, it introduces several layers of complexity and abstraction.
A failure in any one of these layers could result in crashed applications, resource overutilization, and failed deployments.
Fortunately, Kubernetes keeps comprehensive logs of cluster activity and application output. Kubernetes logging provides valuable insight into how containers, nodes, and Kubernetes itself is performing. Meticulously logging everything from Pods to ReplicaSets, it allows you to trace problems back to their source. Kubernetes maintains two types of logs: application logs and cluster logs. Pods generate application logs, and include application code running in a container. The Kubernetes engine and its components, such as the kubelet agent, API server, and node scheduler, generate cluster logs.
Kubernetes Deployments can fail for a number of reasons, and the effects can be seen immediately. The cluster log documents most deployment-related errors. Using the wrong image in a Pod declaration can prevent an entire Deployment from completing successfully. An image error can be as simple as a misspelled image name or tag, or it could indicate a failure to download the image from a registry. Private registries are more complicated, since each node in your cluster must authenticate with the registry before pulling images.
Kubernetes tries to schedule Pods in a way that optimizes CPU and RAM usage, but once a resource is exhausted across the cluster, nodes can start to become unstable. New Pods can no longer be deployedand Kubernetes will start evicting existing Pods. This can cause significant problems for applications, nodes, and the cluster itself. To demonstrate this, we used the docker-stress container to exhaust RAM on our node. As node resources become exhausted, Kubernetes will try rescheduling Pods to higher capacity nodes.
If none are available, Kubernetes will start to evict Pods, which places Pods in the Pending state. Errors can still occur long after the deployment is complete.
Kubernetes automatically collects logs that containerized applications print to stdout and stderr. Each event is logged to a Pod-specific file, which can be accessed using kubectl logs. The Pod builds and runs without any issues, but the application fails with a status of Error. Kubernetes uses a powerful overlay network with its own DNS service. It automatically assigns Pods a DNS record based on their name and the namespace where they were created.
For example, a Pod named my-pod in the namespace kube-cluster can be accessed from another Pod using kube-cluster. The DNS service itself runs as a Pod, which you can access using kubectl :. This Pod hosts three containers: kubedns monitors the Kubernetes master for changes to Services and Endpoints; dnsmasq adds caching; and sidecar performs health checks on the service. For example, if the dnsmaq container is unavailable, the sidecar container will print a message like the following:.
Kubernetes has a built-in API for monitoring node events called the node problem detector. You can also set up alerts to automatically notify you in case of unexpected problems or unusual behavior.
Sending your Kubernetes logs to Papertrail is easy.Edit This Page. This doc is about cluster troubleshooting; we assume you have already ruled out your application as the root cause of the problem you are experiencing. See the application troubleshooting guide for tips on application debugging.
You may also visit troubleshooting document for more information. And verify that all of the nodes you expect to see are present and that they are all in the Ready state. For now, digging deeper into the cluster requires logging into the relevant machines. Here are the locations of the relevant log files. This is an incomplete list of things that could go wrong, and how to adjust your cluster setup to mitigate the problems.
Action: Use IaaS providers reliable storage e. Thanks for the feedback. If you have a specific, answerable question about how to use Kubernetes, ask it on Stack Overflow. Open an issue in the GitHub repo if you want to report a problem or suggest an improvement. Edit This Page Troubleshoot Clusters This doc is about cluster troubleshooting; we assume you have already ruled out your application as the root cause of the problem you are experiencing.
Listing your cluster Looking at logs A general overview of cluster failure modes Listing your cluster The first thing to debug in your cluster is if your nodes are all registered correctly.
Run kubectl get nodes. Create an Issue Edit This Page. Page last modified on March 31, at PM PST by doc: clean up the federation and kubefed federation v1 cli references.I am writing a series of blog posts about troubleshooting Kubernetes.
One of the reasons why Kubernetes is so complex is because troubleshooting what went wrong requires many levels of information gathering. Your pod can fail in all kinds of ways. One failure status is CrashLoopBackOff. You will usually see this when you do a kubectl get pods. That is a lot of output. The first thing I would look at in this output are the Events. This will tell you what Kubernetes is doing. Reading the Events section from top to bottom tells me: the pod was assigned to a node, starts pulling the images, starting the images, and then it goes into this BackOff state.
This message says that it is in a Back-off restarting failed container. This most likely means that Kubernetes started your container, then the container subsequently exited. As we all know, the Docker container should hold and keep pid 1 running or the container exits.
Subscribe to RSS
When the container exits, Kubernetes will try to restart it. After restarting it a few times, it will declare this BackOff state. However, Kubernetes will keep on trying to restart it. If you get the pods again, you can see the restart counter is incrementing as Kubernetes restarts the container but the container keeps on exiting. In our case, if you look above at the Commandwe have it outputting some text and then exiting to show you this demo. However, if you had a real app, this could mean that your application is exiting for some reason and hopefully the application logs will tell you why or give you a clue to why it is exiting.
Another possibility is that the pod is crashing because of a liveness probe not returning a successful status. It will be in the same CrashLoopBackOff state in the get pods output and you have to describe pod to get the real information. It has about the same items as last time but then we encounter:. Kubernetes is backing off on restarting the container so many times. Then the next event tells us that the Liveness probe failed. This gives us an indication that we should look at our Liveness probe.
Either we configured the liveness probe incorrectly for our appplicatoin or it is indeed not working. We should start with checking on one and then the other.
Contact me if you have any questions about this or want to chat, happy to start a dialog or help out: blogs managedkube. Share this: twitter reddit linkedin email.
Type Reason Age From Message Warning BackOff 1s x2 over 19s kubelet, gke-garpoolbecc-bdb3 Back-off restarting failed container. Container will be killed and recreated. Normal Pulled 38s x2 over 79s kubelet, gke-garpoolbecc-bdb3 Successfully pulled image "gcr. Tired of troubleshooting and integrating common Kubernetes apps together? Check out my new open source project that sets up and integrates ningx-ingress, prometheus, external-dns, cert-manager, and more.Kubernetes has become the de-facto solution for container orchestration.
While it has, in some ways, simplified the management and deployment of your distributed applications and services, it has also introduced new levels of complexity.
When maintaining a Kubernetes cluster, one must be mindful of all the different abstractions in its ecosystem and how the various pieces and layers interact with each other in order to avoid failed deployments, resource exhaustion, and application crashes.
When it comes to troubleshooting your Kubernetes cluster and your applications running on it, understanding and using logs are a must! Like most systems, Kubernetes maintains thorough logs of activities happening in your cluster and applications, which you can leverage to narrow down root causes of any failures.
Logs in Kubernetes can give you insight into resources such as nodes, pods, containers, deployments and replica sets. This insight allows you to observe the interactions between those resources and see the effects that one action has on another.
Generally, logs in the Kubernetes ecosystem can be divided into the cluster level logs outputted by components such as the kubelet, the API server, the scheduler and the application level logs generated by pods and containers. The built-in way to view logs on your Kubernetes cluster is with kubectl. This, however, may not always meet your business needs or more sophisticated application setups. In this article, we will look into the inner workings of kubectl, how to view Kubernetes logs with kubectl, explore its pros and cons, and look at alternate solutions.
Other interesting concepts to note is that Kubernetes is designed to be a declarative resource-based system. This means that there is a centralized state of resources maintained internally which you can perform CRUD operations against.
By manipulating these resources with the API, you control Kubernetes. To further illustrate how central the API is to the Kubernetes system, all the components except for the API server and etcd, use the same API in order to read and write to the resources in etcd, the storage system. For more details on the latest version of the Kubernetes API, go here. As you can observe in the config file, the address of the API server endpoint is located next to the server field.
This information tells kubectl how to connect to the cluster. Also included in this file are the credentials used to communicate with the API server, so you can effectively use this same file on a different machine to communicate with the same cluster.
In Kubernetes terminology, files that contain configuration information on how to connect to a cluster are referred to as kubeconfig files. You can also have multiple cluster information in the kubeconfig file.
A caveat to note is that if you pass a deployment or a replica set, the logs command will get the logs for the first pod, and only logs for the first container in that pod will be shown as a default. For example, to view and live tail the logs since the last log line for the etcd container in the etcd-minikube pod in the kube-system namespace, you would run:. The output of all kubectl commands is in plain text format by default but you can customize this with the --output flag.
For example, to get information on the services in the default namespace in json format, you would run:. Logs in a distributed containerized environment will be comprehensive and overwhelming. While kubectl is great for basic interactions with your cluster, and viewing logs with kubectl suffices for ad-hoc troubleshooting, it has a lot of limitations when the size or complexity of your cluster grows.
The biggest limitation of viewing logs with kubectl is in live tailing and streaming multiple logs, and obtaining a comprehensive overview of live streams for multiple pods. Selectors are a core grouping mechanism in Kubernetes that you can use to select pods.
Troubleshoot Kubernetes Deployments
For example, to view the last line of the logs for all the pods matching this selector, you would do:. This is all very useful, but if you try to use the --follow flag with this command, you will encounter an error.
This is because --follow streams the logs from the API server. You are opening one connection to the API server per pod, which will open a connection to the corresponding kubelet itself in order to stream the logs continuously. This does not scale well and translates to a lot of inbound and outbound connections to the API server; therefore, it became a design decision to limit multiple connections.
So you can either stream the logs of one pod, or select a bunch of pods at the same time without streaming. Other shortcomings with this solution are that logs from different pods are mixed together, which prohibits you from knowing which log line came from which pod; logs from newly added pods are not shown, and the log streaming comes to a halt when pods get restarted or replaced.
Stern is an open-source tool that can help solve part of this problem by allowing you to tail multiple pods on your cluster and multiple containers on each pod.
It achieves this by connecting to the Kubernetes API, gets a list of pods, and then streams the logs of all these pods by opening multiple connections. However, on large clusters, the impact and stress on the Kubernetes API can be noticeable. This is why it is an external tool.