Kubernetes is powerful, but when things break, finding the root cause can be tough. This guide cuts through the noise, giving you a clear, step-by-step approach to diagnosing and fixing common Kubernetes issues: From m crashing pods to failing nodes and networking problems.
Understanding the Basics of Kubernetes Troubleshooting Kubernetes troubleshooting can be challenging due to its distributed nature. When issues arise, it's crucial to approach debugging methodically. This starts with understanding the core components of Kubernetes, including Pods, Nodes, Deployments, Services, and ConfigMaps. Identifying where failures occur within these components is the first step toward resolution.
At a high level, Kubernetes issues typically fall into 3 categories:
Application-Level Issues : Problems such as container crashes, misconfigurations, or incorrect environment variables.Cluster-Level Problems : Node failures, networking issues, or insufficient resources disrupting workloads.Configuration & Policy Errors : Misconfigured YAML files, incorrect role-based access control (RBAC), or failed autoscaling can prevent smooth operation.
A structured debugging approach involves identifying symptoms, isolating affected components, and using built-in tools like kubectl to inspect logs, events, and resource statuses.
What Makes Kubernetes Troubleshooting Challenging? Troubleshooting Kubernetes differs from debugging traditional applications because of its dynamic and distributed nature. Here are key challenges:
Ephemeral and Distributed Nature Pods and containers can start, stop, and be rescheduled dynamically, making it difficult to track transient issues. Logging solutions must capture events before they disappear.Multi-Layered Complexity Issues can arise at different layers: Application, pod, node, network, and cluster infrastructure. A failure in one layer can manifest as an issue elsewhere, making root cause analysis tricky.Interdependencies Between Components Kubernetes services depend on each other. A problem in one part of the system (e.g., a failing node) can cascade, affecting seemingly unrelated workloads.Limited Observability by Default Basic Kubernetes tools (kubectl logs, kubectl describe) provide insights, but often require additional observability solutions like Prometheus, Fluentd, or OpenTelemetry to diagnose deeper issues efficiently. Misconfigurations & RBAC Challenges YAML-based configurations can be error-prone, leading to issues like incorrect resource limits, improper service selectors, or insufficient permissions that disrupt operations.Understanding these challenges is the first step in troubleshooting efficiently. Next, we will explore core principles that help mitigate these complexities. For more information on this topic, check out: Best Practices for Writing Kubernetes YAML Manifests.
5 Core Principles of Kubernetes Troubleshooting Effective troubleshooting in Kubernetes requires a systematic approach. These core principles help streamline debugging and minimize downtime.
1. Start with the Symptoms, Not Assumptions Instead of guessing, begin by gathering evidence. Identify what isn’t working: Failed deployments, crashing pods, or connectivity issues – and use Kubernetes tools (kubectl get pods, kubectl describe pod, etc.) to collect relevant data before forming a hypothesis.
2. Follow a Layered Debugging Approach Address issues systematically by checking each layer:
Application Layer : Are containers crashing due to code errors or missing dependencies?Pod & Node Layer : Are there scheduling issues, resource constraints, or node failures?Networking Layer : Are services communicating properly? Is DNS resolving correctly?Cluster Infrastructure : Are control plane components (API server, scheduler) functioning correctly?Debugging one layer at a time prevents confusion and speeds up issue resolution.
3. Leverage Built-In Kubernetes Tools Use Kubernetes' native debugging commands before turning to external tools:
kubectl logs <pod-name> – View container logs for errors.kubectl describe <resource> – Get detailed information about a resource, including events and status.kubectl get events – Identify recent failures and warnings across the cluster.kubectl exec -it <pod-name> -- /bin/sh – Access a running container for real-time troubleshooting.
4. Check Dependencies and External Factors Sometimes Kubernetes itself isn’t the problem: External dependencies like cloud providers, storage backends, or CI/CD pipelines might be the root cause. Verify that all supporting services (databases, APIs, authentication systems) are functioning properly before troubleshooting Kubernetes.
5. Use Logging and Monitoring for Proactive Troubleshooting A strong observability setup makes troubleshooting easier. Implement tools such as:
Logging: Fluentd, Loki, or Elasticsearch for capturing pod logs.Metrics: Prometheus + Grafana for monitoring CPU, memory, and network usage.Tracing: OpenTelemetry or Jaeger to analyze request flows across microservices.Monitoring historical trends and real-time alerts can help detect and resolve problems before they escalate.
By following these principles, Kubernetes troubleshooting becomes more structured, reducing time wasted on trial and error. In the next sections, we will dive into specific issues and their resolutions.
Learn more: Kubernetes Monitoring Best Practices
Common Kubernetes Issues and How to Troubleshoot Them 1. Pods - The Heart of Kubernetes Pods are the fundamental building blocks of Kubernetes, encapsulating one or more containers that share storage, network, and runtime configurations. They act as the smallest deployable unit in a Kubernetes cluster, ensuring that applications run as expected. Given their central role, any issues with pods can lead to disruptions in your application. Understanding how they work and how to diagnose problems is essential for maintaining a healthy cluster.
How to Troubleshoot Kubernetes Pods When a pod misbehaves, the first step is gathering information. Start by checking its status using kubectl get pods to identify whether it's pending, running, or in an error state. If the pod is stuck in a crash loop, use kubectl describe pod <pod-name> to review event logs and understand what’s happening. Logs from kubectl logs <pod-name> can provide further insights, especially if an application inside the pod is failing. Additionally, checking resource limits and node availability ensures that the pod has enough CPU and memory to function properly.
Why Do Pods Fail in Kubernetes? Pod failures can result from various issues, including insufficient resources, misconfigured environment variables, failing liveness or readiness probes, and networking problems. If a pod is frequently restarting, it may be due to an application-level crash or a missing dependency. In some cases, a pod may remain stuck in a "ContainerCreating" state, often caused by image pull errors or underlying node issues. Debugging requires analyzing logs, events, and resource constraints to pinpoint the root cause and apply the necessary fixes.
2. Kubernetes Services and DNS Kubernetes Services enable communication between different components within a cluster, providing stable networking for pods and external access when needed. They abstract away the dynamic nature of pod IPs by offering a consistent way to reach applications. Kubernetes DNS complements this by resolving service names into cluster IPs, allowing seamless service discovery. However, when networking issues arise, they can lead to broken connections, failed requests, or unreachable services. Identifying and fixing these problems ensures smooth communication within your cluster.
Kubernetes Service Troubleshooting When a Kubernetes Service isn’t working as expected, the first step is verifying that it exists and is properly defined using kubectl get svc. If a service is not routing traffic correctly, inspect its associated endpoints with kubectl get endpoints <service-name>. Missing endpoints usually indicate that no pods are correctly backing the service. Additionally, checking pod labels and selector configurations ensures that they match the service definition. For external access issues, confirm that NodePort or LoadBalancer services have the expected IPs and ports open.
Kubernetes DNS Troubleshooting DNS failures in Kubernetes can prevent services from resolving properly, leading to connectivity issues between pods. To diagnose this, start by running a simple DNS query from within a pod using nslookup <service-name> or dig <service-name>. If the resolution fails, check whether the CoreDNS pods are running with kubectl get pods -n kube-system | grep coredns. A misconfigured kube-dns or missing ndots settings in resolv.conf can also cause issues. If necessary, restarting CoreDNS pods or reviewing ConfigMaps under kube-system may help restore proper DNS functionality.
3. Cluster Level Issues While troubleshooting individual pods or services is common, sometimes the root cause lies at the cluster level. Problems with nodes, the control plane, or etcd can lead to instability, degraded performance, or even complete failure of the cluster. Understanding how to diagnose and fix these broader issues is crucial for maintaining a healthy Kubernetes environment.
Kubernetes Node Not Ready When a node enters a NotReady state, it means that Kubernetes has marked it as unavailable for scheduling. This can be caused by high resource usage, network failures, or issues with the kubelet. To troubleshoot, start by running kubectl get nodes to check node statuses. If a node is NotReady , use kubectl describe node <node-name> to review recent events. Checking system logs with journalctl -u kubelet can reveal errors related to kubelet failures. Additionally, running kubectl get pods -A -o wide can help identify workloads stuck on the affected node. If necessary, restarting kubelet or draining and rejoining the node may resolve the issue.
Kubernetes ETCD Troubleshooting ETCD is the backbone of Kubernetes, storing all cluster state information. If etcd becomes slow or unstable, the entire cluster can experience delays or failures. To diagnose issues, check the etcd pod status with kubectl get pods -n kube-system | grep etcd. Performance problems are often caused by high disk latency or excessive database size—running etcdctl endpoint health can verify if etcd is responding properly. Logs from journalctl -u etcd provide deeper insights into potential failures. If etcd is struggling, consider adding more storage, defragmenting the database, or scaling up the control plane.
How to Inspect a Kubernetes Cluster Regularly inspecting a Kubernetes cluster helps detect and prevent issues before they impact workloads. A good starting point is running kubectl cluster-info to check overall health and verify component statuses. For node-specific details, kubectl get nodes -o wide shows conditions and resource usage. To analyze running workloads, kubectl get pods -A provides a complete list of pod statuses across namespaces. When deeper debugging is needed, using kubectl logs <pod-name> and kubectl describe <resource> can reveal application-specific failures. Additionally, monitoring tools like Prometheus and Grafana offer real-time insights into cluster performance and health trends.
Troubleshooting Advanced Kubernetes Scenarios Beyond basic troubleshooting, Kubernetes administrators often face complex networking issues that impact cluster communication and application availability. Whether it's networking policies, pod connectivity failures, or ingress routing problems, resolving these issues requires a deep understanding of Kubernetes internals. In this section, we will explore some of the most common networking challenges and how to diagnose and fix them effectively.
Kubernetes Networking Challenges Kubernetes networking is designed to provide seamless communication between pods, services, and external resources. However, issues like misconfigured network policies, overlapping IP ranges, or problems with the Container Network Interface (CNI) can disrupt connectivity. When troubleshooting, it’s important to check the networking layer step by step, from pod-to-pod communication to service routing and external ingress. Using tools like ping, curl, and traceroute inside Kubernetes clusters can help pinpoint where the failure occurs.
Kubernetes Calico Troubleshooting Calico is a popular CNI plugin that provides networking and network policies for Kubernetes clusters. When Calico-related issues arise, they often manifest as pods being unable to communicate, network policies blocking traffic unexpectedly, or Calico nodes not syncing properly. Start by checking the Calico pods with kubectl get pods -n calico-system. If a pod is failing, inspecting its logs with kubectl logs <calico-pod-name> -n calico-system can provide insights. Additionally, running calicoctl node status helps verify if all nodes are correctly registered. Misconfigured IP pools or conflicting network policies can also cause disruptions, so reviewing Calico’s configuration is essential.
Kubernetes Network Troubleshooting Pod When a pod experiences network issues, isolating the root cause is crucial. Start by running a busybox or netshoot pod for diagnostics:
kubectl run -it --rm --image=busybox network-debug -- /bin/sh
From inside the pod, test connectivity to other pods and services using ping <pod-ip> or curl http://<service-name>:<port>. If a pod cannot reach its destination, verify that it is assigned the correct IP by running kubectl get pod <pod-name> -o wide. Additionally, checking kubectl describe pod <pod-name> can reveal network-related errors. If using NetworkPolicies, ensure they are not unintentionally blocking traffic by reviewing kubectl get networkpolicy -A.
Kubernetes Ingress Troubleshooting Ingress controllers enable external access to services within a Kubernetes cluster, but misconfigurations can lead to unreachable applications or incorrect routing. If an ingress is not working, start by inspecting the ingress resource with kubectl get ingress -A. Running kubectl describe ingress <ingress-name> can reveal issues with backend mappings, TLS settings, or missing annotations. Logs from the ingress controller (e.g., NGINX Ingress Controller) can be checked with kubectl logs -n ingress-nginx <controller-pod-name>. Additionally, ensuring that the ingress service is correctly exposing its ports and that DNS settings are resolving to the right external IP can help diagnose connectivity failures.
How to Troubleshoot Kubernetes Performance Issues Performance problems in Kubernetes can manifest as slow applications, high resource consumption, or delayed responses from services. These issues often stem from inefficient resource allocation, high node utilization, or misconfigured workloads. A structured troubleshooting approach helps identify and resolve bottlenecks efficiently.
1. Check Node and Pod Resource Usage
Start by analyzing cluster-wide resource utilization with:
kubectl top nodes
kubectl top pods -A
If nodes are overutilized, consider adding more capacity or optimizing workloads. If specific pods consume excessive CPU or memory, review their resource requests and limits using:
kubectl describe pod <pod-name> If pods have adequate resources but are still slow, check application logs with:4
kubectl logs <pod-name> Look for error messages or timeouts that may indicate database latency, dependency failures, or inefficient code execution.
3. Analyze Kubernetes Scheduler Delays Pods stuck in a Pending state could indicate scheduling issues. Run:
kubectl describe pod <pod-name> If the event logs show "Insufficient CPU" or "Insufficient Memory," adjust resource requests or distribute workloads more evenly.
4. Network Performance Troubleshooting If services are slow, test network latency between pods using:
kubectl exec -it <pod-name> -- ping <target-pod-ip> Reviewing service and ingress configurations (kubectl describe svc <service-name>) can also help diagnose slow responses.
5. Use Monitoring Tools Tools like Prometheus and Grafana can provide real-time insights into cluster performance. Enable metrics-server in Kubernetes to collect detailed performance data and analyze trends.
Essential Kubernetes Troubleshooting Tools Diagnosing and resolving issues in Kubernetes requires the right set of tools. Whether it's inspecting logs, monitoring resource usage, or debugging networking issues, these tools help streamline troubleshooting and ensure smooth cluster operations. Below are some essential tools that every Kubernetes administrator should have in their toolkit.
1. kubectl – The Swiss Army Knife The primary CLI tool for interacting with Kubernetes, kubectl , provides a wide range of commands for inspecting, managing, and debugging clusters. Key troubleshooting commands include:
Check pod status: kubectl get pods -A Describe a problematic resource: kubectl describe pod <pod-name> View logs of a pod: kubectl logs <pod-name> Debug a running container interactively: kubectl exec -it <pod-name> -- /bin/sh
2. k9s – Kubernetes UI in the Terminal k9s is a terminal-based UI that provides real-time insights into Kubernetes resources. It simplifies navigation, monitoring, and troubleshooting with a more interactive approach compared to kubectl.
Installation:
brew install k9s # macOS or
snap install k9s # Linux
3. stern – Advanced Log Aggregation When debugging multiple pods at once, stern allows you to tail logs from all pods in a namespace simultaneously. This is useful for troubleshooting microservices where logs are spread across multiple containers.
Example:
stern <pod-prefix> -n <namespace>
3. kubectl-debug – Deep Container Debugging This plugin enables users to create ephemeral debugging containers inside pods, allowing for deeper analysis without modifying the original container.
Install the plugin:
kubectl krew install debug Usage:
kubectl debug pod/<pod-name> -it --image=busybox
5. netshoot – Kubernetes Network Debugging A specialized pod used for diagnosing network issues within a Kubernetes cluster. It comes with tools like ping, curl, traceroute, and tcpdump.
Deploy a temporary debugging pod:
kubectl run netshoot --rm -it --image=nicolaka/netshoot -- /bin/sh Here you can find the tool.
6. Prometheus & Grafana – Performance Monitoring For ongoing cluster observability, Prometheus collects metrics, while Grafana provides dashboards for visualizing cluster performance. These tools help identify trends, bottlenecks, and resource anomalies.
Deploy Prometheus & Grafana:
helm install prometheus prometheus-community/kube-prometheus-stack
7. mogenius – The Developer Self Service Platform Troubleshooting Kubernetes doesn’t have to be overwhelming. mogenius offers a fully integrated self-service platform that simplifies monitoring, debugging, and optimizing your workloads. Whether you’re dealing with crash loops, network failures, or scaling issues, mogenius provides real-time alerts and insights, automated diagnostics, and intuitive dashboards: So you can resolve issues faster and focus on building, not fixing.
Choosing the Right Tool Each of these tools serves a unique purpose in Kubernetes troubleshooting. For quick CLI-based analysis, kubectl, stern, and k9s are excellent choices. For deeper debugging, kubectl-debug and netshoot help analyze container and network issues. Meanwhile, Prometheus and Grafana provide ongoing monitoring and visualization. By leveraging the right combination of tools, diagnosing and resolving Kubernetes issues becomes much more efficient.
If you're looking for an all-in-one solution that automates much of the troubleshooting process, mogenius stands out as a fully integrated developer self-service platform.
Master Kubernetes Troubleshooting Effortlessly with mogenius Managing Kubernetes shouldn’t slow your development teams down. With mogenius , you can streamline Kubernetes troubleshooting , automation, and monitoring: All while providing a seamless self-service experience for developers. Our platform eliminates complexity, enabling teams to focus on shipping code, not managing infrastructure.
Why Choose mogenius? Self-Service Kubernetes Workspaces – Abstract and automate Kubernetes environments, eliminating setup and configuration time for developers.Built-in Troubleshooting Dashboards – Gain real-time insights into logs, metrics, and status changes for fast issue resolution.Seamless CI/CD & GitOps Integration – Connect your existing Git workflows or use the built-in mogenius pipeline to deploy straight to your cluster.One-Click Deployments & Templates – Pre-configured, secure, and reusable service templates for standardized environments.Automated Alerting & Policies – Get notified instantly about pod errors, failed pipelines, and resource limits while enforcing best practices.Multi-Tenant Support & RBAC – Easily manage multiple organizations, projects, and clusters with fine-grained access control.Integrated Secrets & Storage Management – Securely store secrets and provide persistent storage with a user-friendly interface.Cluster Sync & Infrastructure as Code – Sync your Kubernetes clusters with Git for backup, disaster recovery, and seamless migrations.With mogenius, you get more than just a Kubernetes troubleshooting tool : You get a developer-first Kubernetes experience. Whether you’re a DevOps engineer or developer, mogenius empowers your team to deploy, monitor, and troubleshoot with confidence.
Want to learn more? Then request a personal demo.
