The Three Pillars of Kubernetes Troubleshooting

There are three aspects to effective troubleshooting in a Kubernetes cluster: understanding the problem, managing and remediating the problem, and preventing the problem from recurring.

Understanding the problem

In a Kubernetes context, it can be difficult to understand what happened and identify the core cause of the issue. This often includes:

• Review recent changes to the afflicted cluster, pod, or node to determine what caused the issue.
• Analyzing YAML configurations, Github repositories, and logs from VMs or bare metal machines executing the faulty components.
• Analyzing Kubernetes events and metrics such as disk pressure, memory pressure, and utilization. In a mature environment, dashboards should provide critical metrics for clusters, nodes, pods, and containers across time.
• Comparing similar components that behave similarly, as well as assessing dependency relationships between components, to determine whether they are related to the failure.

Managing and Remediating the Problem

In a microservices architecture, it is common for each component to be developed and managed by a separate team. Because production incidents often involve multiple components, collaboration is essential to remediate problems quickly.

Once the problem is identified, there are three techniques to resolving it:

• Ad hoc solutions: based on tribal knowledge among teams working on the impacted components. Often, the engineer who created the component will have unwritten knowledge of how to troubleshoot and resolve it.
• Manual runbooks: Manual runbooks are explicit, written procedures for resolving different types of incidents. A runbook ensures that each member of the team can swiftly tackle the issue.
• Automated runbooks: Automated runbooks are automated processes that are launched automatically when a problem is discovered. They can be implemented as a script, infrastructure as code (IaC) template, or Kubernetes operator. It can be difficult to automate reactions to all typical situations, but it can be extremely advantageous by minimizing downtime and eliminating human mistake.

Prevention

Successful teams make prevention their top priority. Over time, this will reduce the time invested in identifying and troubleshooting new issues. Preventing production issues in Kubernetes involves:

• Developing policies, regulations, and playbooks following each occurrence to guarantee effective remediation.
• Investigating if and how to automate a response to the issue.
• Defining how to quickly identify the issue next time and make the required data available—for example, by instrumenting the relevant components.
• Ensure that the issue is escalated to the proper teams, and that those teams can effectively communicate to resolve it.

Kubernetes (K8s) installations frequently present issues from multiple perspectives, including pods, services, ingress, non-responsive clusters, control planes, and high-availability configurations. Kubernetes pods are the smallest deployable units in the Kubernetes ecosystem, each containing one or more containers that share resources and a network. Pods are intended to execute a single instance of an app or process and are built and destroyed as required. Pods are essential for scaling, updating, and sustaining applications in a Kubernetes environment.

In this article, we will explore Pod troubleshooting strategies in Kubernetes, offering expert insights to help you ensure the seamless performance of your applications.