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Automation

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

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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

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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.

Automate Postgresql Daily Database Backup using Pgbackreast and bash

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To automate daily backups of your PostgreSQL database using PGBackRest and bash, you can create a bash script that runs the pgbackrest command and schedule it to run daily using a cron job. Here’s an example script that performs a full backup and stores it in a local directory:
				
					#!/bin/bash

# Set the backup directory
BACKUP_DIR=/backups

# Set the PGBackRest configuration file path
PGCONF=/etc/pgbackrest.conf

# Set the date format for the backup file name
DATE=$(date +%Y-%m-%d)

# Create the backup directory if it doesn't exist
if [ ! -d "$BACKUP_DIR" ]; then
  mkdir -p $BACKUP_DIR
fi

# Perform a full backup and store it in the backup directory
pgbackrest backup --type=full --target=$BACKUP_DIR/$DATE --config=$PGCONF

Save this script to a file (e.g., pgbackup.sh), and make it executable using the chmod command:

				
					chmod +x pgbackup.sh

Then, schedule the script to run daily using a cron job. To do this, open the crontab file using the following command:

				
					crontab -e

Add the following line to the crontab file to run the backup script at 2:00 AM every day:

				
					0 2 * * * /path/to/pgbackup.sh

Replace /path/to/pgbackup.sh with the full path to the backup script file.

Save and exit the crontab file. The backup script will now run daily at the scheduled time and store the backups in the specified directory.

Note that this is a basic example, and you may need to modify the script and cron job settings depending on your specific needs and environment. For more information on cron jobs and scheduling tasks in Linux, you can refer to the Linux man pages or online resources.

How to Take PostgGreSQL Database Backup on AWS S3 bucket using PGBackRest ?

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To take a backup of your PostgreSQL database using PGBackRest and store it in an Amazon S3 bucket, you can follow these general steps:

  1. Set up an Amazon S3 bucket to store your backups. Make sure you have the necessary access keys and permissions to access the bucket.

  2. Create a PGBackRest configuration file (pgbackrest.conf) that specifies the S3 bucket as the backup storage location. Here’s an example configuration:

				
					[global]
log-level-console=info
repo1-path=/pgbackrest
repo1-retention-full=2
repo1-retention-archive=1
repo1-s3-bucket=<bucket_name>
repo1-s3-endpoint=<s3_endpoint>
repo1-s3-key=<access_key>
repo1-s3-key-secret=<access_secret>
repo1-s3-region=<region>
repo1-s3-uri-style=path

  • Replace <bucket_name> with the name of your S3 bucket, <s3_endpoint> with the endpoint URL for your S3 region, <access_key> and <access_secret> with your AWS access key and secret access key, and <region> with your S3 region.

  • Run the following command to perform a full backup and store it in the S3 bucket:

				
					pgbackrest backup --type=full --target=s3:<backup_directory>

    1. Replace <backup_directory> with the directory path in the S3 bucket where you want to store the backup.

    2. Monitor the backup progress by looking at the output of the command. PGBackRest provides detailed information about the backup progress, including the size of the backup, the number of files being backed up, and the backup speed.

    3. Once the backup is complete, you can verify it by running the pgbackrest info command with the --output=json option to display the backup information in JSON format.

    Note that these are general steps, and the exact command and options may differ depending on your specific needs and environment. For more detailed instructions and examples, you can refer to the PGBackRest documentation.

How to Start and Stop the PostgreSQL Database

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AWS

In Amazon RDS for PostgreSQL, you can control the state of your database instance (start or stop) using the AWS Management Console, AWS CLI, or AWS API. The following are the two modes for starting and stopping a PostgreSQL database instance:

  1. “Start” mode: This mode starts the database instance and makes it available for use. In this mode, you can connect to the database and perform read and write operations. To start a database instance using the AWS Management Console, you can select the instance and click the “Start” button. You can also start a database instance using the AWS CLI with the following command:
				
					aws rds start-db-instance --db-instance-identifier <instance_name>

“Stop” mode: This mode stops the database instance and makes it unavailable for use. In this mode, you cannot connect to the database or perform any read or write operations. To stop a database instance using the AWS Management Console, you can select the instance and click the “Stop” button. You can also stop a database instance using the AWS CLI with the following command:

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

Note: When you stop a database instance, data stored in memory is lost, but data stored on disk is preserved. When you start the instance again, it will be in the same state as when it was stopped.

Linux

In a Linux environment, you can control the state of a PostgreSQL database using the pg_ctl command. The following are the two modes for starting and stopping a PostgreSQL database:

“Start” mode: This mode starts the PostgreSQL database server and makes it available for use. To start the PostgreSQL database server, you can use the following command:

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

“Stop” mode: This mode stops the PostgreSQL database server and makes it unavailable for use. To stop the PostgreSQL database server, you can use the following command:

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

where <data_directory> is the directory where the PostgreSQL data files are stored.

Note: The exact location of the PostgreSQL data directory may vary depending on the operating system and installation method. You can typically find it by looking in the PostgreSQL configuration file (e.g., postgresql.conf) or by using the pg_config command.

systemctl command if you have installed PostgreSQL as a service. The following are the two modes for starting and stopping a PostgreSQL database using systemctl:

“Start” mode: This mode starts the PostgreSQL database server and makes it available for use. To start the PostgreSQL database server using systemctl, you can use the following command:

				
					sudo systemctl start postgresql

“Stop” mode: This mode stops the PostgreSQL database server and makes it unavailable for use. To stop the PostgreSQL database server using systemctl, you can use the following command:

				
					sudo systemctl stop postgresql

Note: The exact name of the PostgreSQL service may vary depending on the operating system and installation method. You can check the name of the service by using the systemctl list-units command and searching for a service with a name starting with postgresql.

Azure

You can stop and start an Azure PostgreSQL server using the Azure portal or the Azure CLI.

Here are the steps to stop and start a PostgreSQL server using the Azure portal:

Go to the Azure portal.
Navigate to the Azure PostgreSQL server that you want to stop.
Click on the “Stop” button to stop the server.
To start the server, click on the “Start” button.

And here are the steps to stop and start a PostgreSQL server using the Azure CLI:

Open a terminal or command prompt.
Run the following command to log in to your Azure account:

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

Start the PostgreSQL server by running the following command:

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

Note: Replace <resource-group-name> and <server-name> with the names of your resource group and PostgreSQL server, respectively.

awscli Command to Find PostgreSQL rds Free and Used Space

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To determine the free and used disk space of a PostgreSQL RDS instance using the AWS CLI, you can use the describe-db-instances command and filter the output to show the FreeStorageSpace and AllocatedStorage fields:

				
					aws rds describe-db-instances --query 'DBInstances[*].{ID:DBInstanceIdentifier, Free:FreeStorageSpace, Allocated:AllocatedStorage}' --output table

This will give you a table with the ID of the RDS instance, the Free disk space in GB, and the Allocated disk space in GB. You can use these values to calculate the used disk space by subtracting the free disk space from the allocated disk space.