The ultimate weapon for Kubernetes debugging: K8sGPT

With the continuous development of artificial intelligence and machine learning technologies, enterprises and organizations have begun to actively explore innovative strategies to use these technologies to enhance competitiveness.

K8sGPT[2] is one of the most powerful tools in this field. It is a GPT model based on k8s, which combines the advantages of k8s orchestration with the excellent natural language processing capabilities of the GPT model.

##According to K8sGPT Official website explanation:

K8sgpt is a tool designed for scanning, diagnosing and classifying kubernetes cluster problems. It integrates SRE experience into its analysis engine. to provide the most relevant information. Through the application of artificial intelligence technology, K8sgpt continues to enrich its content and help users solve problems more quickly and accurately.

What is K8sGPT used for?

K8sGPT has recently been submitted to the Cloud Native Computing Foundation (CNCF) as a sandbox project , demonstrating its potential value to the cloud native community.

The CNCF is currently conducting a preliminary evaluation of it, which is encouraging progress and demonstrates the dedication to creating tools that meet the needs of Kubernetes users.

K8sGPT can be used as:

Workload health analysis: Find key issues of the workload

Quick classification, AI analysis: Inspect or drill down into clusters with AI

Assisted understanding: Transform complex signals into easy-to-understand recommendations

Security CVE review: Connect to scanners like Trivy and classify issues

How does K8sGPT work?

K8sGPT uses a set of analyzers specifically designed to detect and simplify the task of diagnosing and resolving issues in a Kubernetes cluster. Based on SRE's intelligent experience coding, these analyzers excel at providing highly accurate and relevant information.

Here are some of the built-in analyzers:

• PVCAnalyzer: This tool examines the configuration of a Persistent Volume Claim (PVC), searching for any differences that could lead to data loss or other storage-related challenges.
• ServiceAnalyzer: This tool probes service settings, looking for any potential issues that may cause service interruption or performance degradation.
• DeploymentAnalyzer: This tool examines the Deployment configuration to identify any issues that may lead to inefficient resource utilization.
• NodeAnalyzer: This tool examines K8s cluster nodes and identifies any potential issues related to node health, usage, and capacity.
• How to install K8sGPT?

(1) Prerequisites:

• Ready-made K8s cluster
• OpenAI provides the API key as the default AI provider
• Homebrew:

Install K8sGPT using the following command:

$ brew install k8sgpt

$ curl -LO https://github.com/k8sgpt-ai/k8sgpt/releases/download/v0.2.7/k8sgpt_amd64.rpm$ sudo rpm -ivh -i k8sgpt_amd64.rpmPreparing...################################# [100%]Updating / installing... 1:k8sgpt-0:0.2.7-1 ################################# [100%]

$ curl -LO https://github.com/k8sgpt-ai/k8sgpt/releases/download/v0.2.7/k8sgpt_amd64.deb$ sudo dpkg -i k8sgpt_amd64.deb

$ curl -LO https://github.com/k8sgpt-ai/k8sgpt/releases/download/v0.2.7/k8sgpt_amd64.apk$ apk add k8sgpt_amd64.apk

$ k8sgpt versionk8sgpt version 0.2.7

Note: It is assumed that you already have OpenAI API-key

$ k8sgpt authUsing openai as backend AI providerEnter openai Key: New provider addedkey added

Once you complete OpenAI authentication, you can start using K8sGPT by entering the following command:

$ k8sgptKubernetes debugging powered by AIUsage:k8sgpt [command]Available Commands:analyze This command will find problems within your Kubernetes clusterauthAuthenticate with your chosen backendcompletionGenerate the autocompletion script for the specified shellfilters Manage filters for analyzing Kubernetes resourcesgenerateGenerate Key for your chosen backend (opens browser)helpHelp about any commandintegration Intergrate another tool into K8sGPTserve Runs k8sgpt as a serverversion Print the version number of k8sgptFlags:--config stringconfig file (default is $HOME/.k8sgpt.yaml)-h, --help help for k8sgpt--kubeconfig stringPath to a kubeconfig. Only required if out-of-cluster. (default "/mnt/efs/data/home/txu/.kube/config")--kubecontext string Kubernetes context to use. Only required if out-of-cluster.Use "k8sgpt [command] --help" for more information about a command.

$ k8sgpt analyze --explain

You can also output JSON format:

View available filters Filter:

$ k8sgpt filters listActive:> Service> CronJob> Node> Pod> Deployment> Ingress> StatefulSet> ReplicaSet> PersistentVolumeClaimUnused:> HorizontalPodAutoScaler> PodDisruptionBudget> NetworkPolicy

filters:

$ k8sgpt analyze --filter=Service $ k8sgpt analyze --namespace=default

$k8sgpt analyze --anonymize

$k8sgpt auth -b

## As businesses and organizations continue to explore creative ways to leverage AI and With the power of machine learning, K8sGPT is becoming a powerful tool to help them achieve their goals. Leveraging superior natural language processing capabilities and K8s orchestration advantages, K8sGPT has the potential to revolutionize the way we analyze and understand text data, thereby promoting innovation in many fields.

Reference materials:

[1]K8s Tools — K8sGPT: https://blog.devgenius.io/k8s-tools-k8sgpt-1fd35e6affc

[2]K8sGPT: https://docs.k8sgpt.ai