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AWS Cheat Sheets

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Amazon SageMaker Data Wrangler

2025-12-12T05:15:52+00:00

Amazon SageMaker Data Wrangler Cheat Sheet Amazon SageMaker Data Wrangler streamlines data preparation and feature engineering for machine learning.  Amazon SageMaker Data Wrangler is a feature in Amazon SageMaker Studio Classic. It integrates data from various sources, allows you to explore, clean, transform, and visualize data, and automates these steps in your machine-learning workflow. Amazon SageMaker Data Wrangler Core Functionalities Data Wrangler provides core functionalities to facilitate data analysis and preparation in machine learning. Import Easily access and import data stored in cloud-based data warehouses and data lakes, such as Amazon S3, Athena, Redshift, Snowflake, and Databricks. The dataset you import [...]

Amazon SageMaker Data Wrangler2025-12-12T05:15:52+00:00

How to Install Docker on Ubuntu using Amazon EC2

2024-09-20T08:10:46+00:00

This tutorial will assist in setting up Docker on an Amazon EC2 Ubuntu instance. Docker's containerization and Ubuntu's user-friendliness make cloud application deployment and management simple. Amazon EC2 provides scalable infrastructure for hosting Docker containers, allowing for smooth app management and scaling. To easily set up Docker on your EC2 instance, just follow this tutorial. What is Docker? Docker is an open-source platform that simplifies the process of building, deploying, and managing applications within isolated containers. These containers bundle the application code along with all its dependencies, ensuring the software behaves the same across different environments, whether on a local [...]

How to Install Docker on Ubuntu using Amazon EC22024-09-20T08:10:46+00:00

Amazon SageMaker Feature Store

2025-12-12T05:11:22+00:00

Amazon SageMaker Feature Store Cheat Sheet Amazon SageMaker Feature Store is a centralized repository for managing machine learning features. It simplifies the process of data exploration, model training, and batch predictions by providing a unified view of your features. Enhances ML model development and deployment efficiency. How does it work? SageMaker Feature Store stores features in feature groups. A feature group is a collection of related features that can be used for a specific task. Feature groups can be created from various data sources, such as Amazon S3, Amazon RDS, and Amazon DynamoDB. There are three modes that a feature [...]

Amazon SageMaker Feature Store2025-12-12T05:11:22+00:00

Migration Evaluator Cheat Sheet

2026-01-05T14:18:38+00:00

Bookmarks Use Cases Features Business Case Pricing Migration Evaluator Cheat Sheet Migration Evaluator is a service that helps organizations assess their on-premises infrastructure and plan a migration to AWS. It provides insights into the costs of running current workloads on AWS and recommends optimized AWS resources based on usage patterns.   Migration Evaluator Use Cases Use the Agentless Collector for broad discovery of your infrastructure or securely upload existing inventory data for analysis and insights. Capture a snapshot of your current on-premises environment to optimize software licensing, map server dependencies, [...]

Migration Evaluator Cheat Sheet2026-01-05T14:18:38+00:00

Email Sender Application with Amazon SES

2024-08-28T11:39:59+00:00

Whether you’re part of a business or organization, sending out emails is crucial for connecting with people. More often than not, you’ll find yourself needing to send similar emails to a group and sometimes, they need to be dynamic. Yes, you can send out one email and just add everyone to the BCC but having a dynamic and more personalized email helps create a better connection between you and the recipient. This is a tutorial on how you can create your very own Batch Email Sender Application with just AWS and Python.   Prerequisites In order to follow this tutorial, [...]

Email Sender Application with Amazon SES2024-08-28T11:39:59+00:00

Amazon EKS vs Amazon ECS

2024-08-27T11:41:51+00:00

    Elastic Container Service (ECS) Elastic Kubernetes Service (EKS) Overview AWS’s fully managed container orchestration service for Docker containers. Designed for simplicity and ease of use. Seamless integration with AWS services and minimal management overhead. Tightly coupled with AWS, making it a cloud-native service. AWS’s managed Kubernetes service. Offers Kubernetes flexibility with AWS’s management and scaling. Ideal for teams needing Kubernetes features and ecosystem. Kubernetes is cloud-agnostic and has a loosely coupled architecture, allowing it to run across various cloud providers like Google Cloud, Azure, and others. Features Simplifies container management without the need for control plane management. Deeply [...]

Amazon EKS vs Amazon ECS2024-08-27T11:41:51+00:00

Amazon Redshift Serverless

2024-07-19T00:24:57+00:00

Bookmarks Use Cases Features Components Monitoring Security Pricing Amazon Redshift Serverless Cheat Sheet Amazon Redshift Serverless allows users to run and scale analytics without managing the underlying data warehouse infrastructure. It dynamically adjusts compute capacity to handle fluctuating query loads, delivering high performance and efficiency for analytical workloads. Amazon Redshift Serverless Use Cases Ideal for workloads with unpredictable usage patterns, where traditional data warehousing solutions may need to be more cost-effective and practical. Supports integration with BI tools like Tableau and Amazon QuickSight for real-time and historical data analysis. Seamlessly integrates [...]

Amazon Redshift Serverless2024-07-19T00:24:57+00:00

Amazon Q

2025-11-25T11:49:38+00:00

Bookmarks Features Sub-modules Security Pricing References Amazon Q Cheat Sheet Amazon Q is an AI assistant that’s designed to be generative, meaning it can generate content, solve problems, and perform tasks using the data and expertise within your company. Use Cases Amazon Q is designed to provide quick and relevant answers to questions, streamline tasks, speed up decision-making, and foster creativity and innovation at work. Business Insights: With QuickSight integration, Q can combine unstructured (docs) + structured data (dashboards / databases) to answer questions like “What's our revenue trend + narrative?”. Customer Service: [...]

Amazon Q2025-11-25T11:49:38+00:00

Amazon Managed Workflows for Apache Airflow

2025-11-22T09:19:33+00:00

Bookmarks Key Features Security Pricing References Amazon Managed Workflows for Apache Airflow (MWAA) Cheat Sheet Amazon MWAA is a service that helps you manage and automate your data workflows using Apache Airflow. Workflows are designed as Directed Acyclic Graphs (DAGs) using Python. Use Cases Complex Data Workflows: Handles complex data processing tasks. ETL Jobs: Coordinates Extract, Transform, Load (ETL) processes. Machine Learning: Prepares datasets for machine learning models. Data Orchestration Across AWS Services: Easily integrates with S3, Redshift, Lambda, and RDS for orchestrated workflows. Event-Driven Workflows: Can trigger DAGs based on events from EventBridge [...]

Amazon Managed Workflows for Apache Airflow2025-11-22T09:19:33+00:00

AWS Glue Data Quality

2026-01-07T16:51:16+00:00

Bookmarks Features Pricing References AWS Glue Data Quality Cheat Sheet AWS Glue Data Quality is a service that provides a way to monitor and measure the quality of your data. It’s part of the AWS Glue service and is built on the open-source DeeQu framework. Supports data quality checks on AWS Lake Formation managed Iceberg, Delta Lake, and Hudi tables. Integrates with Amazon SageMaker AI Lakehouse tables for unified analytics and governance. Can be used alongside zero ETL integrations to validate data ingested from supported AWS services. Use Cases Analyzing data sets that are [...]

AWS Glue Data Quality2026-01-07T16:51:16+00:00

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