Course Introduction

Welcome to the Prometheus Certified Associate course. If you’re here, you already know observability is essential in today’s cloud-native world. Prometheus is the de facto standard for monitoring and alerting—used across organizations such as Google, Red Hat, and GitLab—and demand for Prometheus expertise continues to grow. This course is practical and hands-on. Each topic includes labs, command-line exercises, and real-world examples so you learn by doing and build skills that transfer to production. I’m Sanjeev, your instructor. I’ll guide you through Prometheus, observability concepts, and the tooling you need to operate reliable monitoring at scale. How this course is structured

We follow a progressive, task-focused path: foundations → Prometheus fundamentals → instrumentation and metrics → alerting and operations → scaling and long-term storage.
Every module includes examples and lab exercises so you can practice the concepts immediately.

Course modules at-a-glance

Module	What you’ll learn	Example / Commands
Foundations	Observability fundamentals: what observability means, why it matters, and how SLOs, SLAs, and SLIs help measure and ensure system reliability.	Concepts, measurement approaches, and SLO examples.
Prometheus fundamentals	Prometheus use cases, core concepts, architecture, and installation options (packages, systemd, Docker, etc.).	Install and run Prometheus; learning architecture patterns.
Node Exporter & system metrics	Install and run `node_exporter` to collect host-level metrics and run it as a `systemd` service.	Edit the unit file: `sudo vi /etc/systemd/system/node_exporter.service`
Example systemd unit for node_exporter	Service unit to run node_exporter as a systemd-managed process.	See unit below.
Configuring Prometheus	How scraping, relabeling, auth/encryption for remote endpoints, and dynamic config reloads work.	`prometheus --config.file=/etc/prometheus/prometheus.yml` and SIGHUP/`/-/reload` endpoints.
Metrics & data model	Prometheus metric format, labels, and cardinality best practices.	Example metric: `node_cpu_seconds_total 258277.86`
PromQL	Selectors, matchers, operators, vector matching, aggregation, and subqueries.	Build queries for alerting and dashboard panels.
Visualization & dashboards	Using the Prometheus expression browser, console templates, and dashboard tooling.	Grafana panels, Prometheus console templates.
Application instrumentation	Instrument apps using Prometheus client libraries and follow best practices.	Example Flask app exposing an endpoint (below).
Service discovery	Static, cloud, and Kubernetes service discovery; file-based SD, relabeling, and dynamic config updates.	Example static scrape config (below).
Pushgateway & short-lived jobs	Patterns for capturing metrics from short-lived batch jobs using Pushgateway.	Example push using `curl` (below).
Alerting & Alertmanager	Writing alerting rules, Alertmanager configuration, notification routing, silences, and deduplication.	Alerting flow diagram and examples below.
Kubernetes monitoring	Deploying Prometheus on Kubernetes (including Helm charts), monitoring workloads, and dynamic scrape config in clusters.	`PrometheusRule` CRD example (below).
Scaling & long-term storage	Horizontal scaling patterns, remote write/receive, and integrations with Thanos, Cortex, and other long-term stores.	Architecture patterns and retention strategies.
Community & continued learning	Connect with peers, join forums, and leverage community resources to accelerate your learning.	KodeKloud forums and community labs.

Node Exporter systemd unit example

[Unit]
Description=Node Exporter
Wants=network-online.target
After=network-online.target

[Service]
User=node_exporter
Group=node_exporter
Type=simple
ExecStart=/usr/local/bin/node_exporter

[Install]
WantedBy=multi-user.target

Metrics example

Prometheus records metrics in a text exposition format. Example sample: node_cpu_seconds_total{cpu="0",mode="idle"} 258277.86

Prometheus configuration example (static targets)

scrape_configs:
  - job_name: "web"
    static_configs:
      - targets: ["localhost:9090"]
  - job_name: "node"
    static_configs:
      - targets: ["192.168.1.168:9100"]
  - job_name: "docker"
    static_configs:
      - targets: ["localhost:9323"]

Application instrumentation example (Flask)

from flask import Flask, jsonify

app = Flask(__name__)

@app.get("/cars")
def get_cars():
    return jsonify(["toyota", "honda", "mazda", "lexus"])

if __name__ == '__main__':
    app.run(port=5001)

Pushgateway example (curl)

echo "example_metric 4421" | curl --data-binary @- http://pushgateway:9091/metrics/job/db_backup

Alerting: Prometheus vs Alertmanager

Prometheus evaluates alerting rules and emits alerts.
Alertmanager receives those alerts and handles notification delivery (email, Slack, PagerDuty, etc.), grouping, inhibition, and silencing.

The image explains that Prometheus triggers alerts but does not send notifications, a task handled by Alertmanager. It includes a diagram showing the alert flow and an inset of a person speaking.

Prometheus evaluates alerting rules and emits alerts. Delivery of those alerts (email, Slack, PagerDuty, etc.) is handled by Alertmanager.

Kubernetes PrometheusRule example (Kubernetes CRD)

apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
  name: api-rules
  labels:
    release: prometheus
spec:
  groups:
  - name: api
    rules:
    - alert: down
      expr: up == 0
      for: 0m
      labels:
        severity: critical
      annotations:
        summary: Prometheus target missing {{ $labels.instance }}

Scaling and long-term storage

Learn remote write/receive, how Thanos and Cortex provide horizontally scalable storage and long-term retention, and strategies for retention vs. cost trade-offs.

Community learning and next steps

Join KodeKloud forums to connect with peers, practice labs, ask questions, and collaborate on challenges.
Work through the labs in sequence and use the community to accelerate learning.

Links and references

Prometheus: https://prometheus.io
PromQL basics: https://prometheus.io/docs/prometheus/latest/querying/basics/
Node Exporter: https://github.com/prometheus/node_exporter
Pushgateway: https://github.com/prometheus/pushgateway
Alertmanager: https://prometheus.io/docs/alerting/latest/alertmanager/
Kubernetes: https://kubernetes.io
Helm: https://helm.sh
Thanos: https://thanos.io
Cortex: https://cortexmetrics.io

Together we’ll tackle real-world monitoring challenges and build Prometheus skills you can apply in production.

Introduction

Observability Fundamentals

Prometheus Fundamentals

PromQL

Dashboarding & Visualization

Application Instrumentation

Service Discovery

Push Gateway

Alerting

Monitoring Kubernetes

Conclusion

Scaling & Long Term Storage

Course Introduction

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