Introduction
Managing a Kubernetes cluster on AWS EKS opens doors to scaling and deploying your applications with ease. But keeping track of tools, finding optimization opportunities, and ensuring overall health can be a complex task.
Enter Krs, a user-friendly command-line tool designed to simplify EKS cluster management. With Krs, you gain valuable insights and recommendations that streamline your cluster’s performance. This guide walks you through setting up Krs on your EKS cluster, empowering you to take full control of your Kubernetes environment.
Prerequisites
- AWS Account
- AWSCLI installed on your system
- Homebrew (if you’re on Mac)
Getting Started
1. Setup Amazon EKS Cluster
eksctl create cluster --name <cluster_name> --version <kubernetes_version> --region <aws_region_name e.g us-east-1> --nodegroup-name <linux_nodes> --node-type <node_type> --nodes <number_of_nodes> --zones=<zone_names, e.g: us-east-1a,us-east-1b>2. Authenticate your AWS account
aws configure
3. Extract the list of running clusters on AWS using this command:
aws eks list-clusters
4. Create a config file that permits KRS access to the EKS cluster using this command:
aws eks update-kubeconfig --name <cluster_name>
5. Setup KRS using these commands:
git clone https://github.com/kubetoolsca/krs.git
cd krs
pip install
6. Initialize KRS to permit it access to your cluster using the given command:
krs init
7. Get a view of all possible actions with KRS, by running the given command:
krs --help
Usage: krs [OPTIONS] COMMAND [ARGS]...
krs: A command line interface to scan your Kubernetes Cluster, detect errors,
provide resolutions using LLMs and recommend latest tools for your cluster
Options:
--install-completion Install completion for the current shell.
--show-completion Show completion for the current shell, to copy
it or customize the installation.
--help Show this message and exit.
Commands:
exit Ends krs services safely and deletes all state files from
system. Removes all cached data.
export Exports pod info with logs and events.
health Starts an interactive terminal using an LLM of your choice to
detect and fix issues with your cluster
init Initializes the services and loads the scanner.
namespaces Lists all the namespaces.
pods Lists all the pods with namespaces, or lists pods under a
specified namespace.
recommend Generates a table of recommended tools from our ranking
database and their CNCF project status.
scan Scans the cluster and extracts a list of tools that are
currently used.
8. Permit KRS to get information on the tools utilized in your cluster by running the given command:
krs scan
Scanning your cluster...
Cluster scanned successfully...
Extracted tools used in cluster...
The cluster is using the following tools:
+-------------+--------+-----------------------------+---------------+
| Tool Name | Rank | Category | CNCF Status |
+=============+========+=============================+===============+
| autoscaler | 5 | Cluster with Core CLI tools | unlisted |
+-------------+--------+-----------------------------+---------------+
| istio | 2 | Service Mesh | graduated |
+-------------+--------+-----------------------------+---------------+
| kserve | 3 | Artificial Intelligence | listed |
+-------------+--------+-----------------------------+---------------+
9. Get recommendations on possible tools to use in your cluster by running the given command:
krs recommend
+-----------------------------+------------------+-------------+---------------+
| Category | Recommendation | Tool Name | CNCF Status |
+=============================+==================+=============+===============+
| Cluster with Core CLI tools | Recommended tool | k9s | unlisted |
+-----------------------------+------------------+-------------+---------------+
| Service Mesh | Recommended tool | traefik | listed |
+-----------------------------+------------------+-------------+---------------+
| Artificial Intelligence | Recommended tool | k8sgpt | sandbox |
+-----------------------------+------------------+-------------+---------------+
10. Check the pod and namespace status in your Kubernetes cluster, including errors:
krs health
Starting interactive terminal...
Choose the model provider for healthcheck:
[1] OpenAI
[2] Huggingface
>> 1
Installing necessary libraries..........
openai is already installed.
Enter your OpenAI API key: sk-proj-xxxxxxxxxx
Enter the OpenAI model name: gpt-3.5-turbo
API key and model are valid.
Namespaces in the cluster:
1. cert-manager
2. default
3. istio-system
4. knative-serving
5. kserve
6. kserve-test
7. kube-node-lease
8. kube-public
9. kube-system
Which namespace do you want to check the health for? Select a namespace by entering its number: >> 9
Pods in the namespace kube-system:
1. aws-node-46hzm
2. aws-node-wdgnn
3. coredns-586b798467-54t6h
4. coredns-586b798467-jmlrp
5. kube-proxy-hfmjl
6. kube-proxy-n8lc6
Which pod from kube-system do you want to check the health for? Select a pod by entering its number: >> 1
Checking status of the pod...
Extracting logs and events from the pod...
Logs and events from the pod extracted successfully!
Interactive session started. Type 'end chat' to exit from the session!
>> The provided log entries are empty, so there is nothing to analyze. Everything looks good!
>> Wonderful, so what next
>> If you have any specific questions or another set of log entries you would like me to analyze, feel free to provide them. I'm here to help with any DevOps or Kubernetes-related queries you may have. Just let me know how I can assist you further!
Conclusion
Congratulations! You’ve successfully installed and configured Krs on your AWS EKS cluster. Now, you can utilize Krs functionalities like scanning for deployed tools, receiving recommendations for improvement, and even leveraging AI for in-depth health checks on your pods. Remember, Krs offers a wider range of features beyond what we’ve covered. Explore the krs –help command to unlock its full potential and become a Kubernetes management master!
