A collection of lambda functions to collect data from Cloudwatch, Kinesis, VPC Flow logs, S3, security-hub and AWS Inspector

Sample code to append additional information (e.g. Security Group IDs and geolocation data) to VPC Flow Logs for analysis in Elasticsearch.

This course will teach you AWS basics right through to advanced cloud computing concepts. Ideal for beginners - absolutely no cloud computing experience is required! There are lots of hands-on exercises using an AWS free tier account to give you practical experience with Amazon Web Services. Visual slides and animations will help you gain a deep understanding of Cloud Computing. This is the perfect course for Beginners to the Cloud who want to learn the fundamentals of AWS - putting you in the perfect position to launch your AWS Certification journey and career in cloud computing. 👍 Download the course code and files here: https://digitalcloud.training/aws-bas... 👍 Access your free Guide to AWS Certifications (ebook) here: https://digitalcloud.training/aws-fre... 🎥 Course developed by Neal Davis - Founder of Digital Cloud Training 🔗 Check out the Digital Cloud Training YouTube channel: https://www.youtube.com/c/digitalclou... ⭐️ Course Contents ⭐️ (00:00:00) Course Introduction Section 1 - AWS Basics (00:00:53) Introduction (00:01:19) Amazon Web Services Overview (00:04:26) AWS Global Infrastructure (00:07:35) AWS Pricing (00:15:37) Setup your AWS Free Tier Account (00:21:19) Create a Billing Alarm (00:27:34) IAM Overview (00:32:47) Create IAM User and Group (00:37:38) Amazon Virtual Private Cloud (VPC) (00:48:36) Security Groups and Network ACLs (00:58:40) AWS Public and Private Services (01:00:51) Install the AWS Command Line Interface Section 2 - Amazon Elastic Compute Cloud (EC2) (01:02:08) Introduction (01:02:36) Amazon EC2 Overview (01:08:00) Launching an Amazon EC2 Instance (01:16:42) Connecting to Amazon EC2 Instances (01:27:48) Create a Website Using User Data (01:33:52) Using Access Keys with EC2 (01:34:50) Using IAM Roles with EC2 (01:39:05) Scale Elastically with Amazon EC2 Auto Scaling (01:47:47) Create a Target Tracking Scaling Policy (01:55:43) Add Load Balancing with Amazon ELB Section 3 - AWS Storage Services (02:09:52) Introduction (02:10:28) AWS Storage Services Overview (02:12:40) Create an Attach EBS Volume (02:20:47) Instance Store Volumes (02:23:34) EBS Snapshots and AMIs (02:31:38) Create Amazon EFS File System (02:40:26) Amazon S3 Create Bucket and Make Public (02:47:32) Working with S3 Objects from the AWS CLI Section 4 - AWS Databases (02:52:49) Introduction (02:53:28) Amazon RDS Overview (02:59:52) Create Amazon RDS Multi-AZ (03:10:35) Add an Amazon RDS Read Replica (03:16:18) Install WordPress on EC2 with RDS Database (03:23:56) Amazon DynamoDB Section 5 - Automation on AWS (03:34:34) Introduction (03:35:34) How to Deploy Infrastructure Using AWS CloudFormation (03:37:36) Create Simple Stacks with AWS CloudFormation (03:47:52) Create Complex Stack with AWS CloudFormation (03:56:45) Deploy an Application Using AWS Elastic Beanstalk Section 6 - DevOps on AWS (04:02:00) Introduction (04:02:43) Continuous Integration and Continuous Delivery (CI/CD) (04:05:55) AWS CodePipeline with AWS Elastic Beanstalk (04:15:26) Create AWS CodeStar Project Section 7 - DNS Services and Content Delivery (04:25:47) Introduction (04:26:23) Amazon Route 53 Overview and Routing Policies (04:30:22) Register Domain Using Route 53 (04:35:44) Create Amazon CloudFront Distribution with S3 Static Website (04:44:30) Add an SSL/TLS Certificate and Route 53 Alias Record Section 8 - Docker Containers and Serverless Computing (04:53:35) Introduction (04:54:34) Docker Containers on Amazon ECS (05:06:06) Serverless with AWS Lambda Section 9 - Application Integration and Loose Coupling (05:13:12) Introduction (05:14:01) Amazon SNS and Amazon SQS (05:16:32) AWS Lambda to Amazon SQS Event Source Mapping (05:22:49) Serverless Application - Amazon SQS, SNS, and Lambda 🔗 Digital Cloud Training: https://digitalcloud.training/ 🔗 LinkedIn: https://www.linkedin.com/in/nealkdavis/ 🔗 Twitter: https://twitter.com/nealkdavis 🔗 Instagram: https://www.instagram.com/digitalclou... 👍 AWS Cloud Practitioner - https://digitalcloud.training/amazon-... 👍 AWS Solutions Architect Associate - https://digitalcloud.training/amazon-...

This solution demonstrates the setup and deployment of Amazon SageMaker Studio into a private VPC and implementation of multi-layer security controls, such as data encryption, network traffic monitoring and restriction, usage of VPC endpoints, subnets and security groups, IAM resource policies.

⚙️ FLI is a powerful command-line tool that simplifies AWS VPC Flow Logs analysis with intuitive commands, smart filtering, and automatic annotations, turning raw network data into actionable insights in seconds

Spinifex – Open source AWS-compatible platform for secure edge deployments. Run EC2, VPC, S3, and EBS-like services on bare metal with full control. Built for environments where running in the cloud isn’t an option. Whether you’re deploying to edge sites, private data-centers, or operating in low-connectivity or highly contested environments.

A few terraform examples for building simple VPCs, including variables and data for the AWS provider.

A highly available, secure VPC for hosting Atlassian Data Center products

No description available

AI-Driven Social Media Dashboard monitors and ingests specified tweets using stream processing and leverages a serverless architecture and ML services (Amazon Translate and Amazon Comprehend) to translate and extract insights from those tweets. The diagram below presents the architecture you can build using the example code on GitHub. AI-Driven Social Media Dashboard architecture AI-Driven Social Media Dashboard deploys an Amazon Elastic Compute Cloud (Amazon EC2) instance running in an Amazon Virtual Private Cloud (Amazon VPC) that ingests tweets from Twitter. An Amazon Kinesis Data Firehose delivery stream loads the streaming tweets into the raw prefix in the solution's Amazon Simple Storage Service (Amazon S3) bucket. Amazon S3 invokes an AWS Lambda function to analyze the raw tweets using Amazon Translate to translate non-English tweets into English, and Amazon Comprehend to use natural-language-processing (NLP) to perform entity extraction and sentiment analysis. A second Kinesis Data Firehose delivery stream loads the translated tweets and sentiment values into the sentiment prefix in the Amazon S3 bucket. A third delivery stream loads entities in the entities prefix using in the Amazon S3 bucket. The Guidance also deploys a data lake that includes AWS Glue for data transformation, Amazon Athena for data analysis, and Amazon QuickSight for data visualization. AWS Glue Data Catalog contains a logical database which is used to organize the tables for the data on Amazon S3. Athena uses these table definitions to query the data stored on Amazon S3 and return the information to an Amazon QuickSight dashboard.

No description available

Using Terraform to create an AWS VPC with an EC2 Instance and a MariaDB RDS Data Base

Learn best practices, patterns, and processes for designing and implementing data security with the Amazon Web Services (AWS) cloud. This course can also help to prepare you for the AWS Certified Solutions Architect – Associate exam. Your instructor, Lynn Langit, covers how to use AWS design patterns, tools, and best practices for security, governance, and validation of data used in AWS Identity and Access Management (IAM), Virtual Private Cloud (VPC), and Route 53. She also goes over other AWS tools, such as AWS CloudWatch, CloudTrail, and Inspector; explores encryption concepts; looks at working with security scenarios; and reviews common patterns and practices for implementing disaster recovery processes.

This project covers the implementation of building a ETL data pipeline using Python and AWS Services for financial stocks trade transactions. Tools & Technologies: Python, Boto3 SDK, AWS CLI, AWS Virtual Private Cloud (VPC), AWS VPC Endpoint, AWS S3, AWS Glue, AWS Glue Crawler, AWS Athena, AWS Redshift

Care about your data leaving your VPC/environment in SaaS mode? With our self-hosted option you can run our privacy focused Data Plane in your own Kubernetes Cluster. Just (1) sign-up, (2) request a self-hosted installation, (3) use our values.yaml on your own k8s clusters and (4) run your (customer) data inside your own cloud like 🪄

Frontend application for visualizing AWS Network activity. Uses Cognito for authentication. VPC Flow Logs for data

Creates an entire environment within its own VPC on AWS to stream data from a MariaDB RDS instance to Kafka using Debezium with Avro serialization. Apicurio provides a schema registry for the data.

This project covers the implementation of building an automated ETL data pipeline using Python and AWS Services with Spark transformation job for financial stocks trade transactions. The ETL Data Pipeline is automated using AWS Lambda Function with a Trigger defined. Whenever a new file is ingested into the AWS S3 Bucket; then the AWS Lambda Function gets triggered and will implement the further action to execute the AWS Glue Crawler ETL Spark Transformation Job. The Spark Transformation Job implemented using Python PySpark transforms the trade transactions data stored in the AWS S3 Bucket; further to filter a sub-set of trade transactions for which the total number of shares transacted are less than or equal to 100. Tools & Technologies: Python, Boto3, PySpark, SDK, AWS CLI, AWS Virtual Private Cloud (VPC), AWS VPC Endpoint, AWS S3, AWS Glue, AWS Glue Crawler, AWS Glue Jobs, AWS Athena, AWS Lambda, Spark

A Terraform powered AWS setup with two VPCs Ingestion and Analytics designed for secure, scalable data engineering. It uses public/private subnets, VPC peering, and avoids NAT Gateways for tighter control and cost-efficiency.

Three-tier AWS infrastructure for a Book Review App, built with Terraform and Claude Code. Provisions VPC, security groups, public and internal ALBs, web and app EC2 instances, and RDS MySQL. EC2 user_data scripts auto-bootstrap the frontend (Next.js) and backend (Node.js) on deploy.

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Data transformation function to stream VPC Flowlogs to Splunk via Firehose

Simple terraform module to deploy a 3 Tier (public/private/data) AWS VPC

data service for VPC High Scores. Other data could be included in the future....

Demonstrates data security in GCP with VPC SC, IAP and OS Login

Provision a POC lab for Arista vRouter in multi-cloud setup (using multiple AWS VPCs, initially). Terraform defines the infrastructure with various provisioners including Ansible and templated User Data.

📊🌈🏛 This project develop a data warehouse for a bank using Amazon Redshift, VPC, Glue, S3 and DBT, following a ⭐ Star Schema architecture. The goal is to storage, manage, and optimize data to support decision making and reporting 🏵️

👷🌇 Set up and build a big data processing pipeline with Apache Spark, 📦 AWS services (S3, EMR, EC2, IAM, VPC, Redshift) Terraform to setup the infrastructure and Integration Airflow to automate workflows🥊

A Terraform-based project to deploy a real-time MySQL Change Data Capture (CDC) pipeline on Google Cloud Platform (GCP). It uses Debezium Server running on a GCE VM to stream data changes from a private Cloud SQL instance directly to a Redis sink, all within a secure, private VPC.

demokit quickly and easily creates fully configured demo environments in the cloud (AWS today). It will create a VPC, launch instances, configure security groups, install software, configure settings and populate with demo data. You can also easily shut down instances and restart them to minimize costs.