Prometheus for Docker monitoring - Step-by-Step Execution

Process Flow - Prometheus for Docker monitoring

Start Docker Containers

↓

Run Prometheus Container

↓

Configure Prometheus to scrape Docker metrics

↓

Prometheus collects metrics

↓

Metrics stored in Prometheus database

↓

User queries metrics via Prometheus UI or API

↓

Visualize or alert based on Docker metrics

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End

This flow shows how Prometheus runs alongside Docker containers, collects metrics from them, stores data, and allows users to query or visualize Docker performance.

Execution Sample

Docker

version: '3'
services:
  prometheus:
    image: prom/prometheus
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
    ports:
      - "9090:9090"

This Docker Compose snippet runs Prometheus with a custom config file and exposes its web UI on port 9090.

Process Table

Step	Action	Result	Notes
1	Start Docker containers including app and Prometheus	Containers running	Docker daemon manages container lifecycle
2	Prometheus container reads prometheus.yml config	Config loaded	Config includes Docker metrics scrape targets
3	Prometheus scrapes Docker metrics endpoint	Metrics collected	Metrics include CPU, memory, network stats
4	Metrics stored in Prometheus time-series database	Data stored	Data ready for queries
5	User accesses Prometheus UI at localhost:9090	UI loads	User can query and visualize metrics
6	User runs query for Docker container CPU usage	Query result shown	Real-time CPU usage displayed
7	User stops Prometheus container	Prometheus stops	Metrics collection ends

💡 Prometheus container stopped, monitoring ends

Status Tracker

Variable	Start	After Step 3	After Step 4	After Step 6	Final
Prometheus Status	Not running	Running	Running	Running	Stopped
Metrics Data	None	Partial metrics collected	Stored in DB	Queried and displayed	Stored but no new data
User Query Result	None	None	None	CPU usage data shown	Last query result

Key Moments - 3 Insights

Why does Prometheus need a config file to monitor Docker?

Prometheus uses the config file (prometheus.yml) to know which Docker endpoints to scrape for metrics, as shown in step 2 of the execution table.

What happens if the Prometheus container stops?

Metrics collection stops immediately, but stored data remains until Prometheus restarts, as shown in step 7.

How does Prometheus get metrics from Docker containers?

Prometheus scrapes exposed metrics endpoints from Docker containers or Docker daemon, collecting data like CPU and memory usage (step 3).

Visual Quiz - 3 Questions

Look at the execution table, at which step does Prometheus start collecting Docker metrics?

A Step 2

B Step 4

C Step 3

D Step 5

💡 Hint

Check the 'Action' column for when metrics are scraped.

According to the variable tracker, what is the status of Prometheus after step 6?

A Running

B Not running

C Stopped

D Starting

💡 Hint

Look at the 'Prometheus Status' row under 'After Step 6'.

If the prometheus.yml config is missing the Docker scrape target, what changes in the execution table?

A Step 5 UI would not load

B Step 3 would not collect metrics

C Step 7 would not stop Prometheus

D Step 4 would store more data

💡 Hint

Refer to step 3 where metrics collection depends on config.

Concept Snapshot

Prometheus monitors Docker by running as a container alongside Docker apps.
It uses a config file to know which Docker endpoints to scrape.
Prometheus collects and stores metrics like CPU and memory usage.
Users query metrics via Prometheus UI on port 9090.
Stopping Prometheus stops metric collection but keeps stored data.

Full Transcript

This visual execution shows how Prometheus monitors Docker containers. First, Docker containers including Prometheus start. Prometheus reads its configuration file to find Docker metrics endpoints. Then it scrapes these endpoints to collect metrics such as CPU and memory usage. The collected data is stored in Prometheus's time-series database. Users can access the Prometheus web UI on port 9090 to query and visualize these metrics. When Prometheus stops, metric collection ends but stored data remains. Variables like Prometheus status and metrics data change step-by-step as shown in the tables.