docs(review): neda suggestions

Author: nerda-codes

observability/cockpit/how-to/send-log-from-k8s-to-cockpit.mdx

@@ -76,7 +76,7 @@ alloy-singleton:
   enabled: true
 ```
 
-<Message type="info">
+<Message type="note">
 The template above is for sending logs to your Cockpit. You can also configure it to send metrics to Cockpit using this Helm chart.
 Refer to our dedicated doucumentation to [send metrics from your cluster to Cockpit](/observability/cockpit/how-to/send-metrics-froms-k8s-to-cockpit).
 </Message>
@@ -88,9 +88,9 @@ Once you have configured your `values.yml` file, you can use Helm to deploy the
 1. [Connect](/containers/kubernetes/how-to/connect-cluster-kubectl/) `kubectl` to your Kubernetes cluster
 2. Run the command below to install the `k8s-monitoring` Helm chart:
   ```
-  helm install -f /your-path/to/values.yml your-log-ingester k8s-monitoring --version 1.6.16
+  helm install -f /your-path/to/values.yml name-of-your-choice-for-your-log-ingester k8s-monitoring --version 1.6.16
   ```
-    The `-f` flag specifies the path to your `values.yml` file, which contains the configuration for the Helm chart. Make sure that you replace `/your-path/to/values.yml` with the correct path where your `values.yml` file is stored. Make sure that you also replace `your-log-ingester` with the log ingester of your choice. In our configuration we are using `alloy-lm-ingester`.
+    The `-f` flag specifies the path to your `values.yml` file, which contains the configuration for the Helm chart. Make sure that you replace `/your-path/to/values.yml` with the correct path where your `values.yml` file is stored. Make sure that you also replace `name-of-your-choice-for-your-log-ingester` with a clear name (ex. `alloy-logs-ingester`). In our configuration we are using `alloy-lm-ingester`.
 
     Helm installs the `k8s-monitoring` chart, which includes the Alloy DaemonSet configured to collect logs from your Kubernetes cluster.
     The DaemonSet ensures that a pod is running on each node in your cluster, which collects logs and forwards them to the specified Loki endpoint in your Cockpit.
@@ -119,8 +119,8 @@ You can also use Terraform to manage and deploy Helm charts, providing you with
   ```
 2. Create a `maint.tf` file and paste the following template to create a Helm release resource. Make sure that you replace `/your-path/to/values.yml` with the actual path to your values file.
   ```
-  resource "helm_release" "log-ingester" {
-    name = "your-log-ingester"
+  resource "helm_release" "alloy" {
+    name = "name-of-your-log-ingester"
     repository = "https://grafana.github.io/helm-charts"
     chart = "k8s-monitoring"
     version = "2.0.2"

observability/cockpit/how-to/send-metrics-from-k8s-to-cockpit.mdx

@@ -65,14 +65,14 @@ alloy-singleton:
   enabled: true
 ```
 
-<Message type="info">
+<Message type="note">
 The template above is for sending metrics to your Cockpit. You can also configure it to send logs to Cockpit using this Helm chart.
 Refer to our dedicated doucumentation to [send logs from your cluster to Cockpit](/observability/cockpit/how-to/send-logs-from-k8s-to-cockpit)
 </Message>
 
 ## Add annotations for auto-discovery
 
-Annotations in Kubernetes provide a way to attach metadata to your resources. For `k8s-monitoring`, these annotations signal which pods should be scraped for metrics, and what port to use. For the sake of this documentation, we are adding annotations to specify we want `k8s-monitoring` to scrape the pods from your deployment. Make sure that you replace $METRICS_PORT with the port where your application exposes Prometheus metrics.
+Annotations in Kubernetes provide a way to attach metadata to your resources. For `k8s-monitoring`, these annotations signal which pods should be scraped for metrics, and what port to use. For the sake of this documentation, we are adding annotations to specify we want `k8s-monitoring` to scrape the pods from your deployment. Make sure that you replace `$METRICS_PORT` with the port where your application exposes Prometheus metrics.
 
 ### Kubernetes deployment template
 
@@ -125,8 +125,8 @@ resource "kubernetes_deployment_v1" "your_application_deployment" {
   ```
 2. Create a `maint.tf` file and paste the following template to create a Helm release resource. Make sure that you replace `/your-path/to/values.yml` with the actual path to your values file.
   ```
-  resource "helm_release" "metrics-ingester" {
-    name = "my-metrics-ingester"
+  resource "helm_release" "alloy" {
+    name = "name-of-your-metrics-ingester"
     repository = "https://grafana.github.io/helm-charts"
     chart = "k8s-monitoring"
     version = "2.0.2"
@@ -148,9 +148,9 @@ Once you have configured your `values.yml` file, you can use Helm to deploy the
 1. [Connect](/containers/kubernetes/how-to/connect-cluster-kubectl/) `kubectl` to your Kubernetes cluster
 2. Run the command below to install the `k8s-monitoring` Helm chart:
   ```
-  helm install -f /your-path/to/values.yml your-metrics-ingester k8s-monitoring --version 1.6.16
+  helm install -f /your-path/to/values.yml name-of-your-choice-for-your-metric-ingester k8s-monitoring --version 1.6.16
   ```
-    The `-f` flag specifies the path to your `values.yml` file, which contains the configuration for the Helm chart. Make sure that you replace `/your-path/to/values.yml` with the correct path where your `values.yml` file is stored. Make sure that you also replace `your-metrics-ingester` with the metric ingester of your choice. In our configuration we are using `alloy-lm-ingester`.
+    The `-f` flag specifies the path to your `values.yml` file, which contains the configuration for the Helm chart. Make sure that you replace `/your-path/to/values.yml` with the correct path where your `values.yml` file is stored. Make sure that you also replace `name-of-your-choice-for-your-metric-ingester` with a clear name (ex. `alloy-metrics-ingester`). In our configuration we are using `alloy-lm-ingester`.
         
         Helm installs the `k8s-monitoring` chart, which includes the Alloy DaemonSet configured to collect metrics from your Kubernetes cluster.
         The DaemonSet ensures that a pod is running on each node in your cluster, which collects metrics and forwards them to the specified Prometheus endpoint in your Cockpit.