Monitoring and analyzing time-series data has become a crucial part of modern software systems. Tools like InfluxDB and Grafana are popular for handling and visualizing such data. InfluxDB is an open-source time-series database, and Grafana is an open-source platform for data visualization. In this blog post, we will walk through the process of setting up InfluxDB and Grafana using Docker Compose, and then show how to write data into InfluxDB using a Python script.

What Are InfluxDB and Grafana?

• InfluxDB: A time-series database optimized for storing high volumes of time-stamped data. It is designed for handling metrics and events such as application performance metrics, sensor data, and more.

• Grafana: A popular open-source platform for visualizing time-series data. Grafana integrates with various data sources, including InfluxDB, to create powerful and customizable dashboards for monitoring and alerting.

Together, InfluxDB and Grafana form a powerful monitoring solution for your applications and infrastructure.

Why Use Docker Compose?

Docker Compose simplifies the deployment and management of multi-container Docker applications. With Docker Compose, you can define multiple services (like InfluxDB and Grafana) in a single YAML file, which can be version-controlled and easily shared with others. In this case, we’ll use Docker Compose to set up and manage InfluxDB and Grafana.

Step 1: Setting Up InfluxDB and Grafana with Docker Compose

Let’s start by creating a docker-compose.yml file. This file will define both InfluxDB and Grafana containers.

docker-compose.yml:

version: "3.8"

services:

 grafana:

   image: grafana/grafana

   container_name: grafana

   ports:

     - "3000:3000"

   restart: unless-stopped

   volumes:

     - grafana-data:/var/lib/grafana

   environment:

#      - GF_INSTALL_PLUGINS=

     - GF_SECURITY_ADMIN_USER=username

     - GF_SECURITY_ADMIN_PASSWORD=password

 influxdb2:

   image: influxdb:latest

   ports:

     - 8086:8086

   environment:

     DOCKER_INFLUXDB_INIT_MODE: setup

     DOCKER_INFLUXDB_INIT_USERNAME: username

     DOCKER_INFLUXDB_INIT_PASSWORD: password

     DOCKER_INFLUXDB_INIT_ADMIN_TOKEN_FILE: /run/secrets/influxdb2-admin-token

     DOCKER_INFLUXDB_INIT_ORG: organization-name

     DOCKER_INFLUXDB_INIT_BUCKET: bucket-name

   secrets:

     - influxdb2-admin-username

     - influxdb2-admin-password

     - influxdb2-admin-token

   volumes:

     - type: volume

       source: influxdb2-data

       target: /var/lib/influxdb2

     - type: volume

       source: influxdb2-config

       target: /etc/influxdb2

secrets:

 influxdb2-admin-username:

   file: ./secrets/influxdb2-admin-username

 influxdb2-admin-password:

   file: ./secrets/influxdb2-admin-password

 influxdb2-admin-token:

   file: ./secrets/influxdb2-admin-token

volumes:

 influxdb2-data:

 influxdb2-config:

 grafana-data:

Step 2: Running Docker Compose

To start the services, navigate to the directory containing your docker-compose.yml file and run:  docker-compose up -d 

Step 3: Writing Data to InfluxDB Using Python

Now that we have InfluxDB and Grafana running, let’s move on to writing data into InfluxDB using a Python script.

import influxdb_client

from influxdb_client.client.write_api import SYNCHRONOUS

bucket = "bucket-name"

org = "organization-name"

token = "token-name"

url = "http://localhost:8086"

client = influxdb_client.InfluxDBClient(

   url=url,

   token=token,

   org=org

)

# Write script

write_api = client.write_api(write_options=SYNCHRONOUS)

p = influxdb_client.Point("service1_status").tag("service1", "Up").field("status", 77)

write_api.write(bucket=bucket, org=org, record=p)

client.close()

Step 4: Visualizing Data in Grafana

1. Access Grafana: After the containers are running, you can access Grafana by navigating to http://localhost:3000. Use the following credentials to log in:

   • Username: username

   • Password: password

2. Add InfluxDB as a Data Source:

   • In Grafana, go to Configuration > Data Sources.

   • Add InfluxDB as a new data source.

   • Set the URL to http://influxdb:8086, which refers to the InfluxDB service running in Docker.

   • Enter the username and password, along with the bucket and organization.

3. Create a Dashboard:

   • After configuring the data source, you can create a dashboard.

   • Add a Panel and use the query editor to fetch data from InfluxDB, such as:

SELECT "status" FROM "service1_status" WHERE "service1" = 'Up' 

1. • You can visualize the status field for the service1_status measurement.