What is Prometheus Agent

Prometheus is considered an open-source monitoring system that is popular for event monitoring and alerting. Over time, the components and features of the ecosystem change as new ones are added to increase the system’s capabilities. One of such features is the Prometheus Agent, which allows organizations to keep track of what is going on in their environment. This article aims to give detailed explanations regarding Prometheus Agent: the foundational concepts, relevant terminologies, installation process, and configuration rules, as well as real-world scenarios.

What is Prometheus Agent?

Prometheus Agent is a relatively recent component of Prometheus, existing from the second version of Prometheus. 30. 0. In contrast to a full Prometheus server, the agent is used for scrapping and the remote writing of metrics as well as for simplistic data visualization, but it lacks some built-in functionalities such as local relational database or rule engine. In such cases, when resources are scarce or if the tasks require aggregation across instances and the results are to be stored in a Prometheus server, this is the best solution to use.

Key Features of Prometheus Agent

• Lightweight: It consumes much fewer resources than a full Prometheus server.
• Scraping: Collect metrics from targets that have been configured for it to analyze.
• Remote Write: Sends collected metrics to a Prometheus server or another appropriate data storage platform in an asynchronous manner.
• No Local Storage: It does not store the metrics locally, which can greatly decrease disk I/O and storage.

Primary Terminologies

• Scraping: Scraping is the method by which metrics are gathered from targets (like applications or services) at regular time intervals.
• Remote Write: Remote Write is one of the features of Prometheus that actually causes the collected metrics to be written to other systems.
• Targets: Targets are machines from which Prometheus gathers metrics to analyze. These can be services, applications, or exporters.
• Configuration File: Prometheus and Prometheus Agent both work with the help of YAML configuration files for target scraping, remote writing, and other configurations.

Installation and Setup

Step 1: Download and Install Prometheus Agent

For Linux/macOS: Download the latest release

wget https://release-assets.githubusercontent.com/github-production-release-asset/6838921/6538e824-92d8-46f9-830c-7d81a91ff6fe?sp=r&sv=2018-11-09&sr=b&spr=https&se=2025-07-23T13%3A05%3A03Z&rscd=attachment%3B+filename%3Dprometheus-2.30.0.linux-amd64.tar.gz&rsct=application%2Foctet-stream&skoid=96c2d410-5711-43a1-aedd-ab1947aa7ab0&sktid=398a6654-997b-47e9-b12b-9515b896b4de&skt=2025-07-23T12%3A04%3A22Z&ske=2025-07-23T13%3A05%3A03Z&sks=b&skv=2018-11-09&sig=SXLUN%2Fx4qqDB5jaTSQymmPw40KZ1VD%2B8xMkR7E0l5Bs%3D&jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmVsZWFzZS1hc3NldHMuZ2l0aHVidXNlcmNvbnRlbnQuY29tIiwia2V5Ijoia2V5MSIsImV4cCI6MTc1MzI3MzM0NywibmJmIjoxNzUzMjczMDQ3LCJwYXRoIjoicmVsZWFzZWFzc2V0cHJvZHVjdGlvbi5ibG9iLmNvcmUud2luZG93cy5uZXQifQ.ryCtWV7KoFS8kCTAJwnsD2yu7bxnnDKHS7-COajVAE0&response-content-disposition=attachment%3B%20filename%3Dprometheus-2.30.0.linux-amd64.tar.gz&response-content-type=application%2Foctet-stream
tar -xvf prometheus-2.30.0.linux-amd64.tar.gz
cd prometheus-2.30.0.linux-amd64

Rename the binary to distinguish it as the agent:

mv prometheus prometheus-agent

For Windows: Download the latest release from the Prometheus download page.

• Extract the ZIP file and navigate to the extracted directory.
• Rename the binary to distinguish it as the agent:

ren prometheus.exe prometheus-agent.exe

Step 2: Configure Prometheus Agent

Create a configuration file named prometheus-agent.yml. Below is a basic example configuration:

global:
 scrape_interval: 15s

scrape_configs:
 - job_name: 'node_exporter'
 static_configs:
 - targets: ['localhost:9100']

remote_write:
 - url: 'http://central-prometheus-server:9090/api/v1/write'

Step 3: Run Prometheus Agent

Ensure Prometheus Agent is running with the specified configuration file.

For Linux/macOS:

./prometheus-agent --config.file=prometheus-agent.yml --web.listen-address=:9095 --agent.mode

For Windows:

prometheus-agent.exe --config.file=prometheus-agent.yml --web.listen-address=:9095 --agent.mode

Step 4: Verify Prometheus Agent Operation

Access the Prometheus Agent web interface by navigating to http://localhost:9095 in your web browser. Here, you can check the status of targets and remote write operations.

Advanced Configuration

Dynamic Service Discovery

Prometheus Agent can use service discovery mechanisms to dynamically discover and scrape targets. Below is an example configuration using DNS-based service discovery:

scrape_configs:
 - job_name: 'node_exporter'
 dns_sd_configs:
 - names:
 - 'node-exporter.example.com'
 type: 'A'
 port: 9100

Advanced Remote Write Configuration

You can configure multiple remote write endpoints and specify advanced options such as queue configuration:

remote_write:
 - url: 'http://central-prometheus-server:9090/api/v1/write'
 queue_config:
 capacity: 2500
 max_shards: 100
 min_shards: 1
 max_samples_per_send: 500
 batch_send_deadline: 5s
 min_backoff: 30ms
 max_backoff: 100ms

Example: Monitoring a Custom Application

In this example, we will monitor metrics from a custom web application that exposes Prometheus metrics.

Step 1: Expose Metrics in Your Application

Ensure your web application exposes metrics at an endpoint (e.g., /metrics). Here is an example using a simple Python web application with the prometheus_client library:

from flask import Flask
from prometheus_client import start_http_server, generate_latest, Summary

app = Flask(__name__)
REQUEST_TIME = Summary('request_processing_seconds', 'Time spent processing request')

@app.route('/')
def hello():
 return "Hello, World!"

@app.route('/metrics')
def metrics():
 return generate_latest()

if __name__ == '__main__':
 start_http_server(8080)
 app.run(port=8081)

Install the necessary Python libraries:

Make sure you have Flask and prometheus_client installed. You can install them using pip:

pip install Flask prometheus_client

Run the Python Application:

Navigate to your project directory and run the application:

python app.py

Your application should now be running on localhost:8081, with metrics exposed at localhost:8081/metrics.

Step 2: Create Prometheus Agent Configuration

Create the Configuration File:

File Name: prometheus-agent.yml

Directory: Place this file in the same directory where you will run the Prometheus Agent. For example, this could be ~/prometheus_agent.

global:
 scrape_interval: 15s

scrape_configs:
 - job_name: 'custom_app'
 static_configs:
 - targets: ['localhost:8081']

remote_write:
 - url: 'http://central-prometheus-server:9090/api/v1/write'

This configuration tells Prometheus Agent to scrape metrics from your custom application running on localhost:8081 and forward them to a central Prometheus server at http://central-prometheus-server:9090/api/v1/write.

Step 3: Run Prometheus Agent

Navigate to the directory where you placed prometheus-agent.yml and run the Prometheus Agent:

prometheus-agent.exe agent --config.file=prometheus-agent.yml --web.listen-address=:9095

Step 4: Verify Prometheus Agent Operation

Access Prometheus Agent Web Interface:

Open your browser and navigate to http://localhost:9095. You should see the Prometheus Agent status page.

Check Target Status

Navigate to http://localhost:9095/targets. You should see the custom_app target listed as UP if it is being successfully scraped.

Generate Traffic to Your Application

Run the script to generate traffic:

import requests
import time

for _ in range(100):
 requests.get('http://localhost:8081/process')
 time.sleep(1)

Verify Metrics Forwarding

On the central Prometheus server (specified in remote_write), use the query up{job="custom_app"} in the Prometheus expression browser to verify that metrics from your custom application are being forwarded correctly.

Example Queries

Once the setup is verified and metrics are being scraped and forwarded correctly, you can query metrics using the Prometheus expression browser. Here are a few example queries:

1. Check if the application is up:

up{job="custom_app"}

2. Get the count of requests processed:

rate(request_processing_seconds_count{job="custom_app"}[5m])

3. Get the average request processing time:

rate(request_processing_seconds_sum{job="custom_app"}[5m]) / rate(request_processing_seconds_count{job="cust

Conclusion

So, Prometheus Agent is an interesting addition to the Prometheus universe that adds the ability to scrape and forward metrics without requiring a heavy amount of local storage and rule evaluation capabilities. With these understanding of the primary terminologies, installation process and configuration, one will be in a better place to use Prometheus Agent in environments that have restricted access to resources or distributed monitoring frameworks. Prometheus Agent is convenient when it comes to discovering and managing services with options like dynamic SSD and sophisticated remote write features and configurations needed for a stable and scalable monitoring system.