> ## Documentation Index
> Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Solution Monitoring optional
> Learn to monitor your Kubernetes cluster by inspecting Pods and deploying a metrics server for resource usage tracking.
In this lesson, you will learn how to monitor your Kubernetes cluster by inspecting deployed Pods and deploying a metrics server to track resource usage.
***
## Inspecting Deployed Pods
Begin by verifying the running Pods in your cluster. Execute the following command:
```bash theme={null}
kubectl get pods
```
You should see output similar to the following:
```bash theme={null}
NAME READY STATUS RESTARTS AGE
elephant 1/1 Running 0 20s
lion 1/1 Running 0 20s
rabbit 0/1 ContainerCreating 0 20s
```
At this point, the "elephant" and "lion" Pods are running, while "rabbit" is still initializing.
***
## Deploying the Metrics Server
To monitor resource usage, you'll deploy the metrics server. This lab uses a preconfigured Git repository containing all the necessary configurations.
Do not use these configurations in a production environment. Always refer to the official documentation before deploying to production.
### Step 1: Clone the Repository
Clone the repository by running:
```bash theme={null}
git clone https://github.com/kodekloudhub/kubernetes-metrics-server.git
```
After cloning, you should see output similar to this:
```git theme={null}
Cloning into 'kubernetes-metrics-server'...
remote: Enumerating objects: 24, done.
remote: Counting objects: 100% (12/12), done.
remote: Compressing objects: 100% (12/12), done.
remote: Total 24 (delta 4), reused 0 (delta 0), pack-reused 12
Unpacking objects: 100% (24/24), done.
```
### Step 2: Review the Repository Contents
First, check the directory structure:
```bash theme={null}
ls
```
You should see a directory named `kubernetes-metrics-server` and possibly a file like `sample.yaml`. Next, navigate into the repository directory and list its files:
```bash theme={null}
cd kubernetes-metrics-server/
ls
```
You will find key configuration files such as:
* README.md
* aggregated-metrics-reader.yaml
* auth-delegator.yaml
* metrics-server-deployment.yaml
* metrics-server-service.yaml
* resource-reader.yaml (if present)
### Step 3: Deploy the Metrics Server
Deploy the metrics server by creating all required objects with the following command:
```bash theme={null}
kubectl create -f .
```
You should see output indicating that roles, role bindings, deployments, and services have been created successfully:
```text theme={null}
clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created
clusterrole.rbac.authorization.k8s.io/system:metrics-server:system:auth-delegator created
clusterrole.rbac.authorization.k8s.io/system:metrics-server:auth-reader created
clusterrole.apiresources.k8s.io created
deployment.apps/metrics-server created
service/metrics-server created
clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created
```
It may take a few minutes for the metrics server to start gathering and reporting data. Verify this by listing the Pods again:
```bash theme={null}
kubectl get pods
```
***
## Verifying Metrics Collection
After deployment, you can view resource usage by using the `kubectl top` commands.
### Check Node Resource Utilization
Run the following command:
```bash theme={null}
kubectl top node
```
Expected output:
```bash theme={null}
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
controlplane 470m 1% 1252Mi 0%
node01 57m 0% 349Mi 0%
```
### Check Pod Resource Utilization
To view the resource allocation for each Pod, execute:
```bash theme={null}
kubectl top pod
```
Expected output:
```bash theme={null}
NAME CPU(cores) MEMORY(bytes)
elephant 20m 32Mi
lion 1m 18Mi
rabbit 131m 252Mi
```
***
## Analyzing Resource Consumption
Use the collected metrics to identify resource usage by both nodes and Pods.
### Node Resource Analysis
1. **Identifying the Node with the Highest CPU Consumption**
From the `kubectl top node` output, the "controlplane" node shows a CPU usage of approximately 470 milli cores, which is significantly higher than node01's 57 milli cores.
**Answer:** The controlplane node consumes the most CPU.
2. **Identifying the Node with the Highest Memory Consumption**
The controlplane node also consumes 1252Mi of memory compared to node01's 349Mi.
**Answer:** The controlplane node consumes the most memory.
### Pod Resource Analysis
1. **Identifying the Pod with the Highest Memory Consumption**
The "rabbit" Pod consumes 252Mi of memory, which is higher than the other two Pods.
**Answer:** The "rabbit" Pod consumes the most memory.
2. **Identifying the Pod with the Lowest CPU Consumption**
The "lion" Pod uses only 1m of CPU, making it the least resource-intensive among the Pods.
**Answer:** The "lion" Pod consumes the least CPU.
***
## Recap
In this lesson, you performed the following steps:
* Inspected running Pods using the `kubectl get pods` command.
* Cloned and explored a preconfigured metrics server repository.
* Deployed the metrics server using `kubectl create -f .`.
* Verified node and Pod resource usage utilizing the `kubectl top` commands.
* Analyzed resource consumption to identify which nodes and Pods were consuming the most or least CPU and memory.
### Final Verification
Run the following commands one more time to confirm metrics collection:
```bash theme={null}
kubectl top node
```
Expected output:
```bash theme={null}
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
controlplane 470m 1% 1252Mi 0%
node01 57m 0% 349Mi 0%
```
```bash theme={null}
kubectl top pod
```
Expected output:
```bash theme={null}
NAME CPU(cores) MEMORY(bytes)
elephant 20m 32Mi
lion 1m 18Mi
rabbit 131m 252Mi
```
This concludes the lesson on monitoring cluster components using the metrics server. For additional Kubernetes monitoring resources, consider visiting the [Kubernetes Documentation](https://kubernetes.io/docs/).
Happy monitoring!