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Elevate Your PostgreSQL Skills: The Ultimate Guide to Database Administration Certification

Introduction

PostgreSQL is a robust, open-source database management system renowned for its power and flexibility. As its popularity soars, the demand for skilled PostgreSQL Database Administrators (DBAs) is skyrocketing. Certification is the gold standard that validates your expertise, setting you apart in a competitive job market. In this blog post, we’ll dive into:

  • The Value of PostgreSQL Database Administration Certification
  • Top Certification Programs
  • Exam Preparation Strategies
  • Expert Insights for Success

Why Pursue PostgreSQL Database Administration Certification?

  • Increased Earning Potential: Certified PostgreSQL professionals command higher salaries.
  • Enhanced Credibility: Earn industry recognition and boost your professional reputation.
  • Career Advancement: Certifications open doors to leadership roles and exciting opportunities.
  • Mastery Validation: Demonstrate in-depth PostgreSQL administration skills to employers and clients.

Reputable PostgreSQL Certification Programs

Conquering the PostgreSQL Certification Exam

  • Enroll in Courses: Choose training programs tailored to your preferred certification.
  • Practice, Practice, Practice: Hands-on experience with PostgreSQL administration is essential.
  • Mock Exams: Hone your exam-taking skills and identify areas for improvement with mock tests.
  • Join Online Communities: Get support, ask questions, and learn from fellow PostgreSQL professionals.

Expert Tips for PostgreSQL Certification Success

  • Industry Experience: Real-world experience is invaluable. Work on database projects to solidify your understanding.
  • Study Groups: Form study groups with others preparing for the exam to share knowledge.
  • Know the Exam Blueprint: Understand the exam format and topics covered.
  • Manage Time Wisely: Practice effective time management during the exam.

Conclusion

PostgreSQL Database Administration Certification is a game-changer for your career. By understanding the benefits, choosing the right program, and preparing strategically, you’ll unlock your potential and achieve success in the exciting world of PostgreSQL database administration.

Monitor Database Server using Prometheus & Grafana

Prometheus is an open-source monitoring system that collects metrics from different sources, stores them, and provides a query language and visualization capabilities to analyze and alert on them. It is designed for monitoring distributed systems and microservices architectures, and provides a time-series database to store the collected data.

Grafana is also an open-source data visualization and analytics platform. It allows users to create customizable and interactive dashboards, reports, and alerts for a wide variety of data sources, including Prometheus. Grafana provides a user-friendly interface to explore and analyze the data, and supports various visualization types, such as graphs, tables, and heatmaps. It is often used as a complement to Prometheus, as it enables users to create custom dashboards and alerts based on the collected metrics.

				
					root@ip-172-31-22-198:~/monitroing# cat docker-compose.yml
version: '3.7'
services:
  prometheus:
    image: prom/prometheus:latest
    container_name: prometheus
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
    command:
      - '--config.file=/etc/prometheus/prometheus.yml'
    ports:
      - '9090:9090'

  grafana:
    image: grafana/grafana:latest
    container_name: grafana
    ports:
      - '3000:3000'

  node_exporter:
    image: prom/node-exporter:latest
    container_name: node_exporter
    volumes:
      - /proc:/host/proc:ro
      - /sys:/host/sys:ro
      - /:/rootfs:ro
    command:
      - '--path.procfs=/host/proc'
      - '--path.sysfs=/host/sys'
      - '--collector.filesystem.ignored-mount-points=^/(sys|proc|dev|host|etc)($$|/)'
    ports:
      - '9100:9100'



root@ip-172-31-22-198:~/monitroing# cat prometheus.yml
global:
  scrape_interval: 15s

scrape_configs:
  - job_name: 'prometheus'
    static_configs:
      - targets: ['localhost:9090']

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

The Docker Compose file defines three containers: prometheus, grafana, and node_exporter. The Prometheus configuration file specifies the global scrape interval and the targets for two jobs: prometheus and node_exporter.

The prometheus container runs the Prometheus server, and mounts the prometheus.yml file into the container as its configuration file. The container is exposed on port 9090 and mapped to the same port on the host machine (localhost:9090).

The grafana container runs the Grafana server, and is exposed on port 3000. Grafana is a popular open-source visualization platform that is often used with Prometheus to create custom dashboards and visualizations.

The node_exporter container runs the Prometheus node_exporter service, which collects system metrics from the host machine and makes them available to Prometheus. The container is exposed on port 9100 and mapped to the same port on the host machine (node_exporter:9100).

Overall, this Docker Compose file and Prometheus configuration should set up a basic monitoring stack that collects system metrics from the host machine using node_exporter, stores them in Prometheus, and allows you to visualize them using Grafana.

To start the Docker Compose stack defined in your docker-compose.yml file, you can use the docker-compose up command in the directory where the file is located.

Here are the steps to do this:

  1. Open a terminal window and navigate to the directory where your docker-compose.yml file is located (~/monitroing in your case).

  2. Run the following command:

    docker-compose up
  • This will start all the containers defined in the docker-compose.yml file and output their logs to the terminal window.

  • Once the containers are running, you should be able to access the Prometheus server at http://localhost:9090 and the Grafana server at http://localhost:3000.

    Note that the node_exporter container is not directly accessible from the host machine, but its metrics should be available to Prometheus via its internal network.

  • To stop the containers, press Ctrl+C in the terminal window where you ran the docker-compose up command. This will stop and remove all the containers.

    If you want to stop the containers without removing them, you can use the docker-compose stop command. To start the containers again after stopping them, you can use the docker-compose start command.

How to Test Disk Throughput on Linux using shell script

Here is a shell script that you can use to test disk throughput using 1MB, 10MB, 100MB, 1000MB, and 10000MB:

				
					#!/bin/bash

# Define variables for file sizes in MB
sizes=(1 10 100 1000 10000)

# Define a function to perform the disk throughput test
function test_disk_throughput() {
    # Create a temporary file of the specified size
    dd if=/dev/zero of=tempfile bs=1M count=$1 conv=fdatasync

    # Measure the write speed of the temporary file
    write_speed=$(dd if=tempfile of=/dev/null bs=1M count=$1 2>&1 | awk '/copied/ {print $8 " " $9}')

    # Measure the read speed of the temporary file
    read_speed=$(dd if=tempfile of=/dev/null bs=1M count=$1 iflag=direct 2>&1 | awk '/copied/ {print $8 " " $9}')

    # Print the results
    echo "File size: $1 MB"
    echo "Write speed: $write_speed"
    echo "Read speed: $read_speed"
    echo ""

    # Remove the temporary file
    rm tempfile
}

# Loop through the file sizes and perform the disk throughput test for each size
for size in ${sizes[@]}; do
    test_disk_throughput $size
done

				
			

Save the script to a file, for example disk_throughput_test.sh, and make it executable by running chmod +x disk_throughput_test.sh in the terminal. Then, you can run the script by typing ./disk_throughput_test.sh in the terminal.

The script will create a temporary file of each size, measure the write and read speeds of the file, and print the results to the terminal. The dd command is used to perform the disk I/O operations, and the awk command is used to extract the relevant information from the output of the dd command.

Linux Command List most used by Database Administrator (DBA)

    ls – Lists the contents of the current directory.
    cd – Changes the current working directory.
    pwd – Prints the current working directory.
    mkdir – Creates a new directory.
    touch – Creates a new file or updates the timestamp of an existing file.
    rm – Removes a file or directory.
    rmdir – Removes an empty directory.
    cp – Copies a file or directory.
    mv – Moves or renames a file or directory.
    cat – Displays the contents of a file.
    head – Displays the first few lines of a file.
    tail – Displays the last few lines of a file.
    grep – Searches for a pattern in a file.
    find – Searches for files or directories in a directory hierarchy.
    ps – Displays information about running processes.
    top – Displays information about system resources and processes.
    kill – Sends a signal to a process to terminate it.
    ping – Tests network connectivity to a server.
    ssh – Connects to a remote server over SSH.
    scp – Copies files between hosts over SSH.
    tar – Creates or extracts a tar archive.
    gzip – Compresses or decompresses files using gzip compression.
    chmod – Changes the permissions of a file or directory.
    chown – Changes the owner of a file or directory.
    su – Switches to the superuser or another user account.
    sudo – Executes a command with elevated privileges.
    df – Displays information about disk usage.
    du – Displays information about file and directory sizes.
    ifconfig – Displays information about network interfaces.
    iwconfig – Displays information about wireless network interfaces.
    mount – Mounts a file system.
    umount – Unmounts a file system.
    ssh-keygen – Generates SSH public and private key pairs.
    scp – Copies files between hosts over SSH.
    wget – Downloads files from the internet.
    curl – Transfers data from or to a server using various protocols.
    netstat – Displays network connections, routing tables, and network interfaces.
    route – Manipulates network routing tables.
    uname – Displays information about the operating system.
    date – Displays or sets the system date and time.
    whoami – Displays the current user.
    id – Displays information about a user or group.
    groups – Displays a user’s group memberships.
    passwd – Changes a user’s password.
    adduser – Adds a new user account.
    userdel – Deletes a user account.
    visudo – Edits the sudoers file for configuring sudo access.
    crontab – Schedules tasks to run at specified intervals.
    systemctl – Controls the system’s systemd system and service manager.
    journalctl – Views and manages system logs.

These commands are just a few of the many commands available in Linux, but they should be enough to get you started with basic file and system management tasks.

 

How to start PostgreSQL on Windows

To start PostgreSQL on Windows, you can follow these steps:

  1. Open the PostgreSQL installation directory. By default, it is installed in “C:\Program Files\PostgreSQL{version}”.
  2. Navigate to the “bin” subdirectory.
  3. Double-click on the “pg_ctl.exe” file to open the PostgreSQL control panel.
  4. Select the PostgreSQL service you want to start from the drop-down menu.
  5. Click on the “Start” button to start the service.

Alternatively, you can start PostgreSQL from the command line:

  1. Open the command prompt.

  2. Navigate to the “bin” subdirectory of the PostgreSQL installation directory.

  3. Type the following command to start the PostgreSQL service:

    pg_ctl.exe start -D "C:\Program Files\PostgreSQL\{version}\data"

    Replace “{version}” with the version number of PostgreSQL you have installed.

          Hit Enter.

After starting PostgreSQL, you can connect to it using a PostgreSQL client such as psql, pgAdmin, or any other client of your choice.

How to Start and Stop the PostgreSQL Database

AWS

				
					aws rds start-db-instance --db-instance-identifier <instance_name>
				
			
				
					aws rds stop-db-instance --db-instance-identifier <instance_name>

				
			

Linux

				
					--Run as postgresql linux user
pg_ctl start -D <data_directory>

				
			
				
					--Run as postgresql linux user
pg_ctl stop -D <data_directory>

				
			
				
					sudo systemctl start postgresql

				
			
				
					sudo systemctl stop postgresql

				
			

Azure

				
					az login
az postgres server stop --resource-group <resource-group-name> --name <server-name>

				
			
				
					az postgres server start --resource-group <resource-group-name> --name <server-name>