Grafana for visualization in Kubernetes - Step-by-Step Execution

Process Flow - Grafana for visualization

Start Kubernetes Cluster

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Deploy Prometheus for Metrics

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Deploy Grafana Pod

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Configure Grafana Datasource -> Prometheus

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Create Dashboards in Grafana

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Visualize Metrics in Browser

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Monitor & Alert Based on Visuals

This flow shows how Grafana connects to Prometheus in Kubernetes to visualize metrics step-by-step.

Execution Sample

Kubernetes

kubectl apply -f prometheus.yaml
kubectl apply -f grafana.yaml
kubectl port-forward svc/grafana 3000:3000
# Open http://localhost:3000
# Add Prometheus as datasource
# Create dashboard to view metrics

Deploy Prometheus and Grafana in Kubernetes, forward Grafana port, then configure and view metrics dashboards.

Process Table

Step	Action	Command/Config	Result/Output
1	Deploy Prometheus	kubectl apply -f prometheus.yaml	Prometheus pods running, collecting metrics
2	Deploy Grafana	kubectl apply -f grafana.yaml	Grafana pod running, service created
3	Port-forward Grafana	kubectl port-forward svc/grafana 3000:3000	Local port 3000 forwards to Grafana service
4	Access Grafana UI	Open http://localhost:3000	Grafana login page appears
5	Add Prometheus datasource	Configure datasource URL to Prometheus service	Datasource connected successfully
6	Create dashboard	Use Grafana UI to add panels with Prometheus queries	Dashboard shows live metrics graphs
7	Visualize metrics	Interact with dashboard	Metrics update in real-time
8	Exit	Stop port-forward or pods	Visualization stops, pods terminate

💡 User stops port-forward or deletes pods, ending visualization session

Status Tracker

Component	Initial State	After Deployment	After Config	Final State
Prometheus	Not running	Running, scraping metrics	Running	Running, metrics available
Grafana	Not running	Running pod and service	Datasource connected	Dashboard showing metrics
Port-forward	Not active	Active forwarding localhost:3000	Active	Stopped after exit

Key Moments - 3 Insights

Why can't I see metrics in Grafana after deployment?

Check the execution_table step 5: Grafana datasource must be correctly configured to Prometheus URL. Without this, no data appears.

What happens if I stop the port-forward command?

Refer to execution_table step 8: Stopping port-forward breaks connection to Grafana UI on localhost, so visualization stops.

Why do I need Prometheus before Grafana?

Prometheus collects metrics; Grafana only visualizes them. Without Prometheus running (step 1), Grafana has no data source (step 5).

Visual Quiz - 3 Questions

Look at the execution_table at step 3. What does the port-forward command do?

A It configures Prometheus datasource

B It deploys Grafana pod

C It forwards local port 3000 to Grafana service in Kubernetes

D It creates a dashboard in Grafana

💡 Hint

See execution_table step 3 under Result/Output

At which step does Grafana get connected to Prometheus?

A Step 2

B Step 5

C Step 6

D Step 4

💡 Hint

Check execution_table step 5 Action and Result

If you stop the port-forward, what happens to the visualization?

A Visualization stops because connection is lost

B Metrics continue updating in browser

C Prometheus stops collecting metrics

D Grafana dashboard deletes automatically

💡 Hint

Refer to execution_table step 8 and variable_tracker Port-forward final state

Concept Snapshot

Grafana visualizes metrics by connecting to Prometheus in Kubernetes.
Deploy Prometheus and Grafana pods.
Use kubectl port-forward to access Grafana UI locally.
Configure Prometheus as Grafana datasource.
Create dashboards to see live metrics.
Stop port-forward to end visualization.

Full Transcript

This visual execution shows how to use Grafana for visualization in Kubernetes. First, Prometheus is deployed to collect metrics. Then Grafana is deployed as a pod with a service. Using kubectl port-forward, we forward local port 3000 to Grafana's service port. Opening http://localhost:3000 shows the Grafana UI. We add Prometheus as a datasource in Grafana to connect it to the metrics. Next, dashboards are created in Grafana to visualize live metrics from Prometheus. Metrics update in real-time on the dashboard. Finally, stopping the port-forward or deleting pods stops the visualization. Key points include ensuring datasource configuration and understanding port-forward's role in accessing Grafana UI.