Kubernetes is an open-source container orchestration system. Teams use Kubernetes to automate deploying, managing, and scaling containerized applications. As with any software, Kubernetes also run into problems and errors, which can slow down your team’s development speed, which brings us to troubleshooting.
Troubleshooting is the process of scanning, identifying, diagnosing, and resolving problems, errors, and bugs in software. This article shows why teams use troubleshooting tools on Kubernetes. Also, it describes six high-level Kubernetes troubleshooting tools for your team: their features, what they offer, how they work, etc.
Why use troubleshooting tools?
Orchestrating containers in the backend of distributed microservices is not straightforward. Keeping track of the many moving parts in so many places is almost impossible.
Since Kubernetes manages your containerized application processes, troubleshooting tools help:
- Monitor and keep track of changes across your entire Kubernetes cluster.
- Find information from your Kubernetes clusters.
- Help you investigate issues related to Kubernetes and much more.
Troubleshooting is HARD. Troubleshooting tools save time and operational cost of managing your Kubernetes clusters by detecting issues faster, increasing performance and availability of services in the cluster.
Kubernetes Troubleshooting tools
Komodor is a Kubernetes-native (specifically designed to run on Kubernetes platforms) troubleshooting tool. Komodor provides your team with the ability to trace changes across your entire Kubernetes stack so that you can quickly troubleshoot and independently resolve issues.
Komodor is a unified platform designed to give your team the context they need when an issue happens so they can quickly identify what changes occurred and what was affected.
- The ability to track the system end-to-end.
- A complete activity timeline, including code and config changes, deployments, and alerts.
- A complete drill-down of your Kubernetes diff.
- The Komodor Slackbot to get alerts and information on changes via Slack by writing /komodor.
- Insightful data that is most relevant for troubleshooting.
How it works:
- Komodor gives your team a complete overview of all system services with filter services for particular interest groups.
- Komodor lets you construct a coherent view that includes relevant deploys, configuration changes, alerts on each service, etc.
- It also includes a full timeline of service activities and metadata. The timeline includes:
- Deploy events in which Komodor collects both the Kubernetes changes and app changes, giving your team a unified view of the deploy process.
- Relevant health changes and alerts.
- For each service, you can see relevant tags and helpful links.
PowerfulSeal is a chaos and resiliency testing tool for Kubernetes clusters. PowerfulSeal brings chaos into your Kubernetes clusters by injecting failures so that you can detect problems as early as possible. The main feature of PowerfulSeal is to introduce chaos experiments/engineering on Kubernetes clusters.
- Write simple YAML policies to describe chaos experiments.
- Target specific pods and deployments (Kubernetes integration).
- Target specific nodes and take them up and down.
- Discover things in interactive mode with excellent auto-complete.
3. Weave Scope
Weave Scope is a troubleshooting tool for Kubernetes clusters. It can automatically generate application and infrastructure topologies, helping your team quickly identify performance bottlenecks in your application.
- A real-time interactive display to see your containers and services and quickly identify and correct issues.
- Quickly find node types, containers, and processes by name, label, or even path through their powerful search capability.
- A plugin API to generate and integrate custom metrics with the Scope UI, etc.
How it works:
You can deploy Weave Scope as a standalone application on your local environment or server, or you can choose its software as a Service (SaaS) solution on Weave Cloud. After installation, Weave Scope doesn’t require configuration.
4. Crash Diagnostics
Crash Diagnostics is a tool designed to help your team easily investigate, analyze, and troubleshoot crashed or unresponsive Kubernetes clusters.
- Automate interaction with infrastructures running Kubernetes.
- Capture information from computing resources such as machines (via SSH).
- Automatically execute commands on compute nodes to capture results.
- Capture object and cluster logs from the Kubernetes API server.
- Easily extract data from Cluster-API managed clusters.
How it works:
Crash Diagnostics executes script files written in Starlark language, a Python dialect, that interacts with a specified infrastructure along with its cluster resources. Starlark script files contain pre-defined Starlark functions capable of interacting and collecting diagnostics and other information from the servers in the cluster.
KubeEye aims to find various problems on your Kubernetes cluster—issues such as application misconfiguration, unhealthy cluster components, and node problems.
- KubeEye can locate problems in your cluster control plane.
- KubeEye helps you detect all kinds of node problems.
- KubeEye validates your workload YAML specs against industry best practices and helps you make your cluster stable.
How it works:
KubeEye gets your cluster diagnostic data by:
- Calling the Kubernetes API.
- Regular matching of key error messages in logs.
- Rule matching of container syntax. See Architecture on Github for details.
In this article, you saw five Kubernetes troubleshooting tools and what they offer. Many people think that running a Kubernetes cluster without any troubleshooting tool installed/deployed is fine. However, they don’t take into account the ease such tools bring and the reduced costs in terms of reduced manpower that has to perform troubleshooting functions manually.
On the other hand, you should not think of these tools as a replacement for human expertise. Instead, think of them as assistants who help free up time and focus.