This guide walks you through:

• Installing and configuring Fail2Ban to block ssh attacks malicious requests to sensitive files

Efficient log management helps in maintaining disk space and improving observability. This guide covers how to find, inspect, and manage old Nginx logs.

• Check available disk space

df -h /

• Verify gzip is installed

• Git version 2.34.0 or higher
• Git Bash (Windows users)

Important: ✅ Use SSH when working locally.

If you accidentally committed a .env file to your Git repository, you cannot remove it directly through GitHub’s web interface. You must use Git commands to rewrite history.

GitHub officially recommends using git filter-repo instead of git filter-branch because it's faster and safer.

Check if git filter-repo is installed:

This guide explains how to set up a pipeline where files uploaded to multiple S3 bucket folders trigger specific DBT jobs in DBT Core. The pipeline uses AWS Lambda to validate each uploaded data file, send a mail notification if needed and trigger DBT jobs through Control-M.

This guide explains how to set up a pipeline where files uploaded to multiple S3 bucket folders trigger specific DBT jobs in DBT Core. The pipeline uses AWS EventBridge for event routing and AWS Lambda for triggering DBT jobs.

1. S3 Bucket Folders: Up to 7 folders in an S3 bucket (e.g., folder1/, folder2/, ... folder7/).

This guide explains how to set up a DBT environment using Docker Compose with PostgreSQL as the database. It includes SQL and Python models to transform data, fetch data from an external API (ASPIRE), and export it to AWS S3.

my_dbt_project/
├── docker-compose.yml

This document provides a comprehensive guide to working with Snowflake tasks. It includes SQL code examples, detailed instructions, and best practices for creating, managing, and executing tasks in Snowflake.

You have data files from 2-3 different suppliers. These files are uploaded to an AWS S3 bucket and are then loaded into the respective database tables in Snowflake using Snowpipe. The Snowpipe is triggered automatically whenever new files arrive in the S3 bucket via S3 SNS (Simple Notification Service). After loading the data into Snowflake tables, a stored procedure is triggered for further data processing and distribution into other tables.