The SRE Learning Platform is an open-source hub designed to help IT engineers effectively prepare for the CKA (Certified Kubernetes Administrator), CKS (Certified Kubernetes Security Specialist), and CKAD (Certified Kubernetes Application Developer) exams. Additionally, this platform offers invaluable hands-on experience with AWS EKS (Elastic Kubernetes Service), equipping users with practical insights for real-world applications. Whether you're aiming to validate your skills, boost your career prospects in Kubernetes administration, security, application development, or delve into AWS EKS, this platform provides hands-on labs, practice tests, and expert guidance to ensure certification success.
- Prepare for the CKA: Certified Kubernetes Administrator Exam
- Enhance your skills for the CKS: Certified Kubernetes Security Specialist Exam
- Excel in the CKAD: Certified Kubernetes Application Developer Exam
Master Kubernetes concepts, gain practical experience, and excel in the CKA, CKS, and CKAD exams with the SRE Learning Platform.
The repository is organized into the following sections:
- Makefile - File contains scenarios for launching hands-on labs and mock exams.
- tasks - Directory contains lab scenarios and mock exam scripts.
- terraform - Directory contains modules and Terraform environments.
- environments - Directory contains terragrunt (terraform) environments.
- modules - Directory contains terraform modules.
- terrafrom >= v1.1.7
- terragrunt >= v0.36.1
- aws IAM user + Access key (or IAM role ) with Admin privilege for VPC, EC2, IAM, EKS
- aws profile
- the platform uses aws to create following resources : vpc, subnets, security groups, ec2 (spot ), s3
- after you launch the scenarios the platform will create all the necessary resources and give access to k8s clusters.
- to create clusters the platform uses kubeadm
- you can easily add your own scenario using the already existing terraform module k8s_self_managment
- k8s_self_managment module supports versions:
k8s version : [ 1.21 , 1.27 ] https://kubernetes.io/releases/
Rintime :
docker [1.21 , 1.23]
cri-o [1.21 , 1.28]
containerd [1.21 , 1.28] # cks default 1.27
containerd_gvizor [1.21 , 1.28]
OS for nodes :
ubuntu : 20.04 LTS , 22.04 LTS # cks default 20.04 LTS
CNI : calico
- change backend_bucket ( region , backend_region optional ) in terragrunt.hcl :
- create aws ec2 key-pair with name=cks in our region (default region = eu-north-1)
Every command should be run from the project's root directory.
CKA
make run_cka_vpc- create vpc for CKA hands-on labsTASK=01 make run_cka_k8s_task- create cka hands-on labs number 01make delete_cka_k8s- delete cka hands-on labsmake delete_cka_vpc- delete vpc for CKA hands-on labsTASK=01 make run_cka_k8s_mock- create mock CKA exam number 01make delete_cka_k8s_mock- delete mock CKA exam
CKS
make run_cks_vpc- create vpc for CKS hands-on labsTASK=10 make run_cks_k8s_task- create cks hands-on labs number 10make delete_cks_k8s- delete cks hands-on labsmake delete_cks_vpc- delete vpc for CKS hands-on labsTASK=01 make run_cks_k8s_mock- create mock CKS exam number 01make delete_cks_k8s_mock- delete mock CKS exam
EKS
TASK={lab_number} make run_eks_taskcreate hands-on labmake delete_eks_taskdelete eks lab cluster
Video instruction for launching CKA mock exam
CKA hands-on lab
- create vpc for CKA hands-on labs
make run_cka_vpc - choose a hands-on lab number
- change ami_id in
{lab_number}/scripts/terragrunt.hclif you changed region - create cka lab cluster
TASK={lab_number} make run_cka_k8s_task - find {master_external_ip} in terraform output
- log in to master node via ssh
ssh ubuntu@{master_external_ip} -i {key} - check init logs
tail -f /var/log/cloud-init-output.log - read lab descriptions in
{lab_number}/README.MD - check solution in
{lab_number}/SOLUTION.MD - delete cka lab cluster
make delete_cka_k8s_task - clean cka lab cluster
.terraformfoldermake clean_cka_k8s
mock CKA exam
- choose a mock exam number
- change ami_id in
{mock_number}/env.hclif you changed region - change instance type from
spottoon-demandin{mock_number}/env.hclif you need - create mock CKA exam
TASK={mock_number} make run_cka_k8s_mock - find
worker_pc_ipinterraform output - connect to
worker_pc_ipwith your ssh key and userubuntu - open questions list
{mock_number}/README.MDand do tasks - use
ssh {kubernetes_nodename}from work pc to connect to node - run
time_lefton work pc to check time - run
check_resulton work pc to check result - delete mock CKA exam
make delete_cka_k8s_mock - find exam solutions in
{mock_number}/worker/files/solutions)and * Video for mock 01 . - find exam tests in
{mock_number}/worker/files/tests.bats)
CKS hands-on lab
- create vpc for CKA hands-on labs
make run_cks_vpc - choose a hands-on lab number
- change ami_id in
{lab_number}/scripts/terragrunt.hclif you changed region - create cka lab cluster
TASK={lab_number} make run_cks_k8s_task - find {master_external_ip} in terraform output
- log in to master node via ssh
ssh ubuntu@{master_external_ip} -i {key} - check init logs
tail -f /var/log/cloud-init-output.log - read lab descriptions in
{lab_number}/README.MD - check solution in
{lab_number}/SOLUTION.MD - delete cks lab cluster
make delete_cks_k8s_task - clean cks lab cluster
.terraformfoldermake clean_cks_k8s
mock CKS exam
- choose a mock exam number
- change ami_id in
{mock_number}/env.hclif you changed region - change instance type from
spottoon-demandin{mock_number}/env.hclif you need - create mock CKA exam
TASK={mock_number} make run_cks_k8s_mock - find
worker_pc_ipinterraform output - connect to
worker_pc_ipwith your ssh key and userubuntu - open questions list
{mock_number}/README.MDand do tasks - use
ssh {kubernetes_nodename}from work pc to connect to node - run
time_lefton work pc to check time - run
check_resulton work pc to check result - delete mock CKA exam
make delete_cks_k8s_mock - find exam solutions in
{mock_number}/worker/files/solutions - find exam tests in
{mock_number}/worker/files/tests.bats
EKS hands-on lab
- choose labs number
- create hands-on lab
TASK={lab_number} make run_eks_task - find
worker_pc_ipinterraform output - log in to worker_pc node via ssh
ssh ubuntu@{worker_pc_ip} -i {key} - read lab descriptions in
{lab_number}/README.MD - check solution in
{lab_number}/SOLUTION.MD - delete eks lab cluster
make delete_eks_task
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